DETAILED ACTION
A summary of this action:
Claims 1-20 have been presented for examination.
This action is Final.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments
Following Applicants amendments to the Claims, the objections of the Claims is Withdrawn.
Following Applicants arguments and amendments, the 112 rejection of the claims is Withdrawn in part Maintained in part.
Applicant’s Argument: Applicant’s arguments directed the 112 rejection are based on newly amended subject matter and because Applicant alleges the rejection because the claim amendments submitted herewith have rendered this rejection moot.
Examiner’s Response: Examiner agrees that the majority of Applicant’s newly proposed amendments were modified to render the rejection moot. However, Examiner respectfully disagrees with Applicant’s argument is still maintained because the “design reference storage” term was not defined rendering the claim term indefinite. Therefore, the 112 rejection of the claims is Withdrawn in part and Maintained in part. All arguments are addressed in the 112 rejection of the claims below.
Following Applicants arguments and amendments, and in light of the 2019 Patent Eligibility guidance, the 101 rejection of the Claims is Maintained.
Applicant’s Argument 1: Applicant’s arguments directed to 101 rejection are based on newly amended subject matter." Here, Applicant argues that the newly proposed amendments encompass features of a design support system that searches for a relaxed design constraint so as to allow final performance of the design target to reach a target value without excessively surpassing the target value to determine the relaxed design constraint and that independent claims 1, 2, and 16 do not recite mental processes. More specifically, Applicant argues that the newly proposed claim amendments require at least setting a design constraint based on an analysis of a frequency distribution of a variable of the design data in each of plural groups in which the variable is classified and because there is no practical way in which a human could perform this process given the volume of calculations required for setting the design constraint and no practical way for a human to generate a file that can be sent to a design device.
Examiner’s Response 1: Examiner respectfully disagrees with Applicant’s arguments that the newly proposed claim amendments overcome the 101 rejection and do not recite mental processes because although Applicant’s arguments that the volume of calculations required for setting the design constraint cannot practically be performed in the human mind, Applicant fails to consider that this task or activity can be reduced down to writing with the aid of a pencil and paper, which may also trigger a mental process. All arguments are addressed in the 101 rejection of the claims below.
Applicant’s Argument 2: Here, Applicant submits more elements, which Applicant argues transforms the claim limitation abstract ideas into a practical application as the combination of features recited in the independent claims go well beyond reciting additional limitations at a high level of generality.
Examiner’s Response 2: Examiner respectfully disagrees with Applicant’s arguments because the newly proposed claim limitation elements of “access” and “output” are mere data gathering/output necessary to perform the abstract idea (MPEP 2106.05(g)) and is not sufficient to integrate the judicial exception into a practical application. Additionally, Applicant’s newly proposed claim limitation elements of “extract” , “identify” , “determine”, and “generate” are mental processes because they can be performed in the human mind including observation, evaluation, judgment, and opinion or can be performed with the aid of a pencil and paper and further narrow the abstract idea identified in the independent claims. All arguments are addressed in the 101 rejection of the claims below.
Therefore, the 101 rejection of the claims is Maintained.
Following Applicants arguments and amendments, the 103 rejection of the claims is Maintained.
Applicant’s Argument: Applicant’s arguments directed the 103 rejection are based on newly amended subject matter. Here, Applicant argues that the prior art references used to reject Applicant’s independent claims fails to disclose or suggest at least "extract from the verified design data a variable that defines a design constraint of plural elements in the design data" as recited in the context of claims 1, 2, and 16 and that Applicant's claims, as the physical elements can have different design constraints that must be accounted for in setting the design constraint value. Furthermore, Applicant argues and implies that because the subject claims are distinguishable over the prior art combinations by virtue of their respective dependency from base claim 1, for dependent claims 13, 14, 17, and 18, withdrawal of the rejection is proper.
Examiner’s Response: Examiner respectfully disagrees because Applicant proposed newly amended subject matter requiring a search for prior art based on the prior references already used and possibly new prior art to determine if the newly proposed claim limitations are taught by additional prior art. Here, Applicant argues that Deng, Miura, and Pandey when applied individually and/or collectively as alleged, fail to disclose or suggest every feature and/or the combination of features recited in Applicant's claims. However, these prior art references teaches
All arguments are addressed in the 103 rejection of the claims below.
Therefore, the 103 rejection is Maintained.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are:
a design reference storage in claim 7
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
For the purposes of examination of the claim limitations, the Examiner will be interpreting the hardware structure associated with “design reference storage” as in claim 7.” The spec illustrates in [Figures 1 and 23] and defined in specification paragraph [0154-0155] as a “design support system” (labeled 1 in the spec) is a “computer” (labeled 6 in the spec) that may include a central processing unit (CPU) 302 that executes command codes of a program, a memory 304 including a random access memory (RAM), a read only memory (ROM), and the like, a storage 306 including a hard disk drive (HDD), a solid state drive (SSD), and the like, a display device, a mouse, and the like, and an input/output device 308 usable as the UI device 10 is connected through a bus 300. By the computer, executing a method from the design support system, illustrated in Figure 23, is attained. The Examiner will also be interpreting the hardware structure associated with “design reference storage” 306 as hard disk drive in accordance with specification paragraph [0154].
The corresponding algorithm of the “receiver that receives ...” is noted in MPEP 2181 (II) (A), where "Clearly, a unit which receives digital data, performs complex mathematical computations and outputs the results to a display must be implemented by or on a general or special purpose computer." This is to be the structure and algorithm required for the claim, or equivalents thereof. For, the remaining units, the specification is devoid of an algorithm to perform the claimed functions.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention. As described above, the disclosure does not provide adequate structure to perform the claimed functions of “design reference storage” as in claim 7. The specification does not demonstrate that applicant has made an invention that achieves the claimed function because the invention is not described with sufficient detail such that one of ordinary skill in the art can reasonably conclude that the inventor had possession of the claimed invention. All claims dependent on a 112 rejected base claim are rejected based on their dependency.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. Claim limitations “design reference storage” as in claim 7, invokes 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function and to clearly link the structure, material, or acts to the function. While the specification discloses a “computer” (labeled as 6) in specification paragraph [0154], it is devoid of the algorithms that provide structures to convert the generic “computer” into a special purpose “computer” to perform the claimed functions. (MPEP 2181.11.(B)) There is no disclosure of any particular algorithms, either explicitly or inherently, to perform the actions of the units, analyzer and determiner. The use of the term "computer" alone is not adequate structure because it does not describe a special purpose “computer” for performing the functions. As such, the specification does not provide sufficient details such that one of ordinary skill in the art would understand which structure performs the claimed function. Therefore, the claim is indefinite and is rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph. All claims dependent on a 112 rejected base claim are rejected based on their dependency.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea of a mental process or mathematical concept without significantly more.
Step 1: Claims 1-18 are directed to a design support system, which is a system and is a statutory category invention. Claim 19 is directed to a method, which is a process and is a statutory category invention. Claim 20 is directed to a non-transitory computer-readable medium, which is a manufacture and a statutory invention. Therefore, claims 1-20 are directed to patent eligible categories of invention.
Claim 1
Step 2A, Prong 1: Independent claims 1, 2 and 16 similarly recite an abstract idea because the claims are derived from Mental Processes based on concepts performed in the human mind or with the aid of pencil and paper or in the alternative Mathematical Concepts using mathematical relationships, mathematical formulas or equations, or mathematical calculations.
Claims 1 recites classify the extracted variable into a plurality of groups, the limitation covers mental processes of classifying the received variables into the plurality of groups using the clustering method as described in [0132] of the specification.
Claims 1 recites generate an electronic file including the design constraint set for each of the plurality of groups;, the limitation covers mental processes of generating an output file with the goal of making a judgment on the output file results as described in [0086] of the specification.
Claims 1, 2, and 16 similarly recite extract from the verified design data a variable that defines a design constraint of plural physical elements of a device in the design data, the limitation covers mental processes of assessing the verified design data for which commercialization is reached as described in [0039] of the specification.
Claims 1, 2, and 16 similarly recite extract from the verified design data a variable that defines a design constraint of the plural physical elements of the device in the design data, the limitation covers mental processes of assessing the design data A, B, C,…all the variables that define the design constraints regardless of whether the variables satisfy the first design constraint as described in [0161] of the specification.
Claims 1, 2, and 16 similarly recite set for each of the plurality of groups, the design constraint by analyzing, using statistical processing or machine learning, a frequency distribution of the classified variable for each of the one or more groups, the limitation covers mental processes of assessing analyzing the frequency distribution of the variables in each of the plurality of groups using machine learning as described in [0131] of the specification.
Claim 2 recites determine an existence probability of the extracted variable, the limitation covers mental processes of finding the existence probability ρd of the extracted variable dij as described in [0039] of the specification.
Claim 2 recites determine a cumulative existence probability of the determined existence probability, the limitation covers mental processes of determining the cumulative existence probability of Ơ that indicates a cumulate value of the discrete existence probability ρd as described in [0035] of the specification.
Claim 2 recites identify a value of the variable that is a value when the cumulative existence probability matches a preset reference value and set the identified value to a design constraint value of the design constraint, the limitation covers mental processes of identifying a value of the variable dij as described in [0039] of the specification.
Claim 2 recites generate an electronic file including the design constraint value of the design constraint, the limitation covers mental processes of generating an output file with the goal of making a judgment on the output file results as described in [0086] of the specification.
Claims 16 recites set the design constraint by analyzing, using statistical processing or machine learning, a frequency distribution of the extracted variable, the limitation covers mental processes of assessing the design constraint based on the existence probability extracted from the design data as described in [0104] of the specification.
Claims 16 similarly recite verify whether or not a variable included in new design data satisfies the design constraint, the limitation covers mental processes of verifying new design data that is acquired in the design reference DB 23 and the design constraint of the new design data as described in [0041] of the specification.
Claims 16 similarly recite verify whether or not the variable included in the new design data satisfies the received design constraint, the limitation covers mental processes of assessing the verification result received from the output file 32 as described in [0146] of the specification.
Claim 16 recites generate an electronic file including the design constraint value when the variable satisfies the received design constraint, the limitation covers mental processes of generating an output file with the goal of making a judgment on the output file results as described in [0146] of the specification.
Thus, the claims recite the abstract idea of a mental process performed in the human mind, or with the aid of pencil and paper.
Dependent claims 3-10, 11-15, and 17-20 further narrow the abstract ideas, identified in the independent claims. See analysis below.
Step 2A, Prong 2: The judicial exception is not integrated into a practical application. Claim 1 recites the additional limitation “design reference storage” as in dependent claim 7, and “non-transitory computer-readable recording medium” as in dependent claim 20, this limitation does not integrate the judicial exception into a practical application because it is nothing more than generally linking the use of the judicial exception to a particular technological environment. See MPEP 2106.05(h). Alternatively, this additional element merely uses a computer device as a tool to perform the abstract idea. (MPEP 2106.05(f)).
The limitation memory storing executable instructions which cause the processor to receive verified design data for a device to be manufactured, in independent claims 1 and 2, can be viewed as use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., mental process or certain methods of organizing human activity) does not integrate a judicial exception into a practical application. See MPEP 2106.05(f).
The limitation output the electronic file to a design device for providing information to the design device for arranging the plural physical elements so that a target value of a design is met, in independent claims 1, 2, and 16, can be viewed as is insignificant extra-solution activity, specifically pertaining to mere data gathering/output necessary to perform the abstract idea (MPEP 2106.05(g)) and is not sufficient to integrate the judicial exception into a practical application. This is akin to selecting information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display, which has been identified as extra solution activity. Therefore, the judicial exception is not integrated into a practical application
The limitation store the first design constraint defining that the value of the variable is equal to or greater than a first design constraint value or equal to or less than the first design constraint value, in dependent claim 7, can be viewed as merely use a computer as a tool to perform the abstract idea. (MPEP 2106.05(f)). Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a mental process or a mathematical concept) does not integrate a judicial exception into a practical application.
Claims 16 similarly recite receive a choice of the design constraint to be applied to the new design data from a plurality of design constraints, the limitation covers mental processes of assessing a choice of variables for defining the design constraints from among the variables included in the design data A, B, C, as described in [0132] of the specification.
The limitation of update the design constraint based on a verification result of whether or not the verified variable and included in the new design data satisfies the design constraint, in dependent claims 17, only amounts to mere instructions to apply as it only recites the idea of a solution or outcome and fails to recite details of how a solution to a problem is accomplished MPEP 2106.05(f).
The limitation receive modification to the verification result from a user, and update the design constraint based on the verification result to which the modification is added, in dependent claim 18, can be viewed as merely use a computer as a tool to perform the abstract idea. (MPEP 2106.05(f)). Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a mental process or a mathematical concept) does not integrate a judicial exception into a practical application.
The limitation of executable by the design support system, in dependent claims 19, only amounts to mere instructions to apply as it only recites the idea of a solution or outcome and fails to recite details of how a solution to a problem is accomplished MPEP 2106.05(f).
The limitation storing a program, the program causing a computer to function as the design support system, in dependent claim 20, can be viewed as merely use a computer as a tool to perform the abstract idea. (MPEP 2106.05(f)). Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a mental process or a mathematical concept) does not integrate a judicial exception into a practical application.
Dependent claims 3-10, 11-15, and 17-20 further narrow the abstract ideas, identified in the independent claims, and do not introduce further additional elements for consideration beyond those addressed above. The additional elements have been considered both individually and as an ordered combination in to determine whether they integrate the exception into a practical application. Therefore, the dependent claims do not integrate the claimed invention into a practical application.
Step 2B: The claims do not amount to significantly more. The judicial exception does not amount to significantly more. Claim 1 recites the additional limitation “design reference storage” as in dependent claim 7, and “non-transitory computer-readable recording medium” as in dependent claim 20, this limitation does not amount to significantly more because it is nothing more than generally linking the use of the judicial exception to a particular technological environment. See MPEP 2106.05(h). Alternatively, this additional element merely uses a computer device as a tool to perform the abstract idea. (MPEP 2106.05(f)).
The limitation memory storing executable instructions which cause the processor to receive verified design data for a device to be manufactured, in independent claims 1 and 2, can be viewed as use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., mental process or certain methods of organizing human activity) does not amount to significantly more. See MPEP 2106.05(f).
The limitation output the electronic file to a design device for providing information to the design device for arranging the plural physical elements so that a target value of a design is met, in independent claims 1, 2, and 16, can be viewed as is insignificant extra-solution activity, specifically pertaining to mere data gathering/output necessary to perform the abstract idea (MPEP 2106.05(g)) and does not amount to significantly more. This is akin to selecting information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display, which has been identified as extra solution activity. Therefore, the judicial exception does not amount to significantly more.
The limitation store the first design constraint defining that the value of the variable is equal to or greater than a first design constraint value or equal to or less than the first design constraint value, in dependent claim 7, can be viewed as merely use a computer as a tool to perform the abstract idea. (MPEP 2106.05(f)). Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a mental process or a mathematical concept) does not amount to significantly more.
The limitation receive a choice of the design constraint to be applied to the new design data from a plurality of design constraints, in independent claim 16, can be viewed as merely use a computer as a tool to perform the abstract idea. (MPEP 2106.05(f)). Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a mental process or a mathematical concept) does not amount to significantly more.
The limitation of update the design constraint based on a verification result of whether or not the verified variable and included in the new design data satisfies the design constraint, in dependent claims 17, only amounts to mere instructions to apply as it only recites the idea of a solution or outcome and fails to recite details of how a solution to a problem is accomplished MPEP 2106.05(f) and does not amount to significantly more.
The limitation receive modification to the verification result from a user, and update the design constraint based on the verification result to which the modification is added, in dependent claim 18, can be viewed as merely use a computer as a tool to perform the abstract idea. (MPEP 2106.05(f)). Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a mental process or a mathematical concept) does not amount to significantly more.
The limitation of executable by the design support system, in dependent claims 19, only amounts to mere instructions to apply as it only recites the idea of a solution or outcome and fails to recite details of how a solution to a problem is accomplished MPEP 2106.05(f) and does not amount to significantly more.
The limitation storing a program, the program causing a computer to function as the design support system, in dependent claim 20, can be viewed as merely use a computer as a tool to perform the abstract idea. (MPEP 2106.05(f)). Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a mental process or a mathematical concept) does not amount to significantly more.
Dependent claims 3-10, 11-15, and 17-20 further narrow the abstract ideas, identified in the independent claims, and do not introduce further additional elements for consideration beyond those addressed above. The additional elements have been considered both individually and as an ordered combination in to determine whether they amount to significantly more. Therefore, the dependent claims does not amount to significantly more.
Therefore, the claims as a whole does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements, when considered alone or in combination, do not amount to significantly more than the judicial exception.
As stated in Section I.B. of the December 16, 2014 101 Examination Guidelines, “[t]o be patent-eligible, a claim that is directed to a judicial exception must include additional features to ensure that the claim describes a process or product that applies the exception in a meaningful way, such that it is more than a drafting effort designed to monopolize the exception.”
The dependent claims include the same abstract ideas recited as recited in the independent claims, and merely incorporate additional details that narrow the abstract ideas and fail to add significantly more to the claims.
Dependent claim 3 recites “extract a plurality of variables that define the design constraint,” which further narrows the abstract idea identified in the independent claim, which is directed to “Mental Processes.”
Dependent claim 3 recites “determine the existence probability of each variable of the extracted plurality of variables,” which further narrows the abstract idea identified in the independent claim, which is directed to “Mental Processes.”
Dependent claim 3 recites “determine the cumulative existence probability of the existence probability of each of the plurality of variables,” which further narrows the abstract idea identified in the independent claim, which is directed to “Mental Processes.”
Dependent claim 3 recites “set to the design constraint value of the design constraint, each value of the plurality of variables when the cumulative existence probability matches the preset reference value,” which further narrows the abstract idea identified in the independent claim, which is directed to “Mental Processes.”
Dependent claim 4 recites “determine, from the existence probability, one or more new existence probabilities based on an attribute, determine a cumulative existence probability of the new existence probabilities,” which further narrows the abstract idea identified in the independent claim, which is directed to “Mental Processes.”
Dependent claim 5 recites “determine, when the determined existence probability has a plurality of extreme values, which further narrows the abstract idea identified in the independent claim, which is directed to a “Mental Processes.”
Dependent claim 5 recites determine cumulative existence probability of each of the plurality of new existence probabilities, which further narrows the abstract idea identified in the independent claim, which is directed to a “Mental Processes.”
Dependent claim 5 recites identify a value of the variable that is a value when each of the cumulative existence probabilities matches the preset reference value and sets the identified value to the design constraint value of the design constraint ,” which further narrows the abstract idea identified in the independent claim, which is directed to a “Mental Processes.”
Dependent claim 6 recites “extract from the verified design data, as a variable that defines the design constraint, a variable that does not satisfy a first design constraint set at a design phase, which further narrows the abstract idea identified in the independent claim, which is directed to a “Mental Processes.”
Dependent claim 6 recites set a second design constraint that is more relaxed than the first design constraint, by analyzing, using the statistical processing or the machine learning, the frequency distribution of the variable extracted by the variable extractor,” which further narrows the abstract idea identified in the independent claim, which is directed to a “Mental Processes” or in the alternative a “Mathematical Concept.”
Dependent claim 7 recites “extract from the verified design data the variable having a value less than or greater than the first design constraint value, which further narrows the abstract idea identified in the independent claim, which is directed to a “Mental Processes” or in the alternative a “Mathematical Concept.”
Dependent claim 8 recites “determine a share of a plurality of components in an area of a device to be designed and adjust a design constraint value in accordance with the share of the plurality of components,” which further narrows the abstract idea identified in the independent claim, which is directed to a “Mental Processes.”
Dependent claim 9 recites “determine a share of a plurality of components in an area of a device to be designed, for each of a plurality of areas and adjust a design constraint value for each of the plurality of areas in accordance with a share of the plurality of components for each of the plurality of areas,” which further narrows the abstract idea identified in the independent claim, which is directed to a “Mental Processes.”
Dependent claim 10 recites “adjust the design constraint value to be higher for a higher share of the plurality of components, which further narrows the abstract idea identified in the independent claim, which is directed to a “Mental Processes.”
Dependent claim 11 recites “classify the variable extracted from the verified design data into a plurality of groups,” which further narrows the abstract idea identified in the independent claim, which is directed to a “Mental Processes.”
Dependent claim 11 recites “set, for each of the plurality of groups, the design constraint based on a frequency distribution of the classified variable of the plurality of groups,” which further narrows the abstract idea identified in the independent claim, which is directed to a “Mental Processes.”
Dependent claim 12 recites “classify the extracted variable from the verified design into the plurality of groups using a clustering method,” which further narrows the abstract idea identified in the independent claim, which is directed to a “Mental Processes.”
Dependent claim 13 recites “set the design constraint by analyzing, using unsupervised machine learning, the frequency distribution of the variable extracted by the variable extractor,” which further narrows the abstract idea identified in the independent claim, which is directed to a “Mental Processes.”
Dependent claim 14 recites “extract the variable from each of design data determined as a pass through verification and design data determined as a fail through the verification, which further narrows the abstract idea identified in the independent claim, which is directed to a “Mental Processes.”
Dependent claim 14 recites sets the design constraint by analyzing, using the unsupervised machine learning, a frequency distribution of variable extracted from the design data determined as the pass and a frequency distribution of variable extracted from the design data determined as the fail,” which further narrows the abstract idea identified in the independent claim, which is directed to a “Mental Processes.”
Dependent claim 15 recites “verify whether or not a variable included in new design data satisfies the design constraint set by the setter,” which further narrows the abstract idea identified in the independent claim, which is directed to a “Mental Processes.”
Dependent claim 19 recites “a design support method executable by the design support system according to claim 1,” which further narrows the abstract idea identified in the independent claim, which is directed to a “Mental Processes.”
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1, 6-9, 10, 15, 16, 19, and 20 are rejected under are rejected under 35 U.S.C. 103 as being unpatentable over DENG (Constraint-based functional design verification for conceptual design), herein DENG, in view of MIURA (WO 2010024022 A1), herein MIURA, and in view of PANDEY (US 7962886 B1), herein PANDEY.
Claim 1
Claim 1 is rejected because DENG teaches extract from the verified design data a variable that defines a design constraint of plural physical elements of a device in the design data DENG ([Section 3.3. | User Interface of the Verification Design Environment] “The implemented design verification environment is described in this section. The process starts with a designer entering a causal behavioral process (CBP). We shall use a CBP from a paper separation device design as an example. The function of the device (device) is to separate a pack of paper into individual pieces (design constraint) . One possible physical structure is shown in Fig. 3.”) See also DENG ([Section 4.2 Approaches for VDG Development |pdf page 8 of 11] “Furthermore, a constraint graph (CG) (design constraint) can be developed from the reduced VDG (variable dependency graph) (design data) by connecting each constraint node (a design constraint) with its related variables (variables that define a design constraint). The combined graph is called VDG-CG graph. Fig. 8 shows the VDG-CG graph for the paper separation device (device) design produced (extract from the verified design data) by our design verification environment (verified design data). The left-most column of nodes (plural physical elements) is input variables (design data) for deriving output variables (variables that define a design constraint), that is, the input variables (variables that define a design constraint) used as part of the VDG (verified design data). The right-most column of nodes (plural physical elements) is input variables (variables that define a design constraint) not used in the VDG (verified design data), but required by the CG (constraint graph).”)
DENG does not explicitly teach classify the extracted variable into a plurality of groups or a frequency distribution of the classified variable for each of the one or more groups.
However, MIURA teaches classify the extracted variable into a plurality of groups MIURA ([Description | pdf page 5 of 11] “Returning to FIG. 1, the device load calculation unit (classifier) 19 reads the "class value” (classify the extracted variable) of each class (plurality of groups) from the content load distribution information 151, reads the "number of contents (extracted variable) selected by each device from the content number information 171 ", and based on these values to calculate "device load" (classified variable). The "device load" (classified variable) is a distribution load applied to a device by distributing (extracted) the content (classified variable) stored in the device. Even if the number of contents (classified variable) stored in each device is determined, the device load varies depending on the combination of the content loads (classified variables) of the stored contents. For example, if the stored content includes content with a high content load (classified variable), the device load becomes a high value. A high content load means high popularity (plurality of groups). Here, when the content load is represented by a class value (classify the variable), all possible device load values (variable) are extracted.”)
MIURA also teaches a frequency distribution of the classified variable for each of the one or more groups MIURA ([Description | pdf page 5 of 11] “Specifically, the allocation probability calculation unit 15 classifies content (a frequency distribution of the classified variable) into a plurality of classes (each of the one or more group) based on the value of "content load", and calculates the number of contents (frequency) belonging to each class. In other words, a frequency distribution (histogram) (frequency distribution of the classified variable) using the content as a sample is created. Then, the allocation probability calculation unit 15 calculates the probability (allocation probability) that content belonging to each class is allocated to the device for each class value using the following equation (1). (Class Allocation Probability)= (Class Frequency)/ (Total Content) (1).”)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of MIURA with DENG as the references deal with relates to a design support system that verifies design and enables easy setting of a design constraint. MIURA would modify DENG wherein a frequency distribution of the classified variable for each of the one or more groups. The benefits of doing so aim to provide a technique that facilitates the design of an appropriate distribution system. (MIURA [Description | pdf page 3 of 11]).
The combination of DENG and MIURA does not explicitly set the design constraint by analyzing, using statistical processing or machine learning, memory storing executable instructions, and receive verified design data for a device to be manufactured.
However, PANDEY teaches set the design constraint by analyzing, using statistical processing or machine learning PANDEY ([Column 4 | Lines 38-40] “some embodiments of methodology of the invention select a set of candidates (set the design constraint) by structural analysis of the design (analyzing a design constraint).”) See also PANDEY ([Column 5 | Lines 49-57] “FIG. 1 shows one embodiment of a high-level process flow 100 of an automatic constraint generation process. As shown, inputs 110, 112, 114 to process 100 are received from an RTL or a gate-level design, existing design constraint specifications (if any), and/or timing reports (if they exist). Given the RTL or gate level design, the design constraint process 100 collects information about path statistics (using statistical processing), such as a number of paths in the design, a path distribution by delays, a number of logic levels, etc., and outputs an design constraint file 130.”)
PANDEY also teaches memory storing executable instructions PANDEY ([Column 10 | Lines 47-54] “The computer system 800 also includes a main memory 806. Such as a random access memory (RAM) or other dynamic storage device, coupled to the bus 802 for storing information and instructions (memory storing executable instructions) to be executed by the processor 804. The main memory 806 also may be used for storing temporary variables or other inter mediate information during execution of instructions to be executed by the processor 804.”)
PANDEY also teaches receive verified design data for a device to be manufactured PANDEY ([Column 5 | Lines 49-53] “FIG. 1 shows one embodiment of a high-level process flow 100 of an automatic constraint generation process (verified design data). As shown, inputs 110, 112, 114 to process 100 are received (receive verified design data) from an RTL or a gate-level design (for a device to be manufactured), existing design constraint specifications (if any), and/or timing reports (if they exist).”)
PANDEY also teaches generate an electronic file including the design constraint set for each of the plurality of groups PANDEY ([Column 10 | Lines 47-54] “Integration of block level constraints into a full-chip constraint set is a delicate task, because the constraints taken from a block, and in particular the timing exceptions, may take on an unexpected meaning at the top-level. It is of particular importance to avoid manipulating constraints purely at the textual level. In one aspect of the invention, the meaning of the constraints is propagated to top-level entities (set for each of the plurality of groups), and then written out as new commands (generate an electronic file including the design constraint) that may or may not resemble the original ones.”)
PANDEY also teaches output the electronic file to a design device for providing information to the design device for arranging the plural physical elements so that a target value of a design is met PANDEY ([Column 6 |lines 52:62] “In 222, design constraint integration rules for the electronic circuit design are configured. In one embodiment, configuration of design constraint integration rules (providing information) may be accomplished at any stage before integration (to a design device for to the design device) in 226. This may involve the creation of rule instances (arranging the plural physical elements) that target each particular attribute to be ignored, reported, and/or promoted (target value of a design is met). 222 may be achieved by loading a default configuration file (output the electronic file), or this may be completely user-specific, or this may be a combination of both.”)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of PANDEY with DENG and MIURA as the references deal with relates to a design support system that verifies design and enables easy setting of a design constraint. PANDEY would modify DENG and MIURA wherein the executable instructions stored in the memory. The benefits of doing so performs compression to group similar constraints into single design constraint statement and reduces or minimizes the size of the generated design constraint. (PANDEY [Column 5 | lines 8-12 | pdf page 13 of 18]). Accordingly, claim 1 is rejected based on the combination of these references.
Claim 6
Claim 6 is rejected because the combination of DENG, MIURA, and PANDEY teach the claim 1 limitations.
DENG teaches extract from the verified design data, as a variable that defines the design constraint DENG ([Section 3.3. | User Interface of the Verification Design Environment] “The function of the device is to separate (extract) a pack of paper into individual pieces (design constraint). One possible physical structure is shown in Fig. 3.”) See also DENG ([Section 4.2 Approaches for VDG Development |pdf page 8 of 11] “Furthermore, a constraint graph (CG) (a variable that defines the design constraint) can be developed from the reduced VDG (variable dependency graph) by connecting each constraint node with its related variables (variables that define a design constraint). The combined graph is called VDG-CG graph. Fig. 8 shows the VDG-CG graph for the paper separation device design produced by our design verification environment (verified design data). The left-most column of nodes (design constraint) is input variables (variables that define a design constraint) for deriving output variables (variables that define a design constraint), that is, the input variables (variables that define a design constraint) used as part of the VDG (verified design data). The right-most column of nodes (design constraint) is input variables (variables that define a design constraint) not used in the VDG (verified design data), but required by the CG (constraint graph).”)
DENG does not explicitly teach a variable that does not satisfy a first design constraint set at a design phase, and set a second design constraint that is more relaxed than the first design constraint by analyzing, using the statistical processing or the machine learning, the frequency distribution of the variable extracted by the variable extractor.
However, MIURA teaches a variable that does not satisfy a first design constraint set at a design phase, and set a second design constraint that is more relaxed than the first design constraint MIURA ([Embodiment 2 | pdf page 8 of 11] “ A second embodiment (second design) of the present invention will be described. FIG. 26 is a block diagram showing the configuration of the distribution system design support apparatus 1d of this embodiment. Referring to the figure, the distribution system design support apparatus 1d (variable) does not include (does not satisfy) the system distribution load information 113 (a first design constraint set at a design phase), the probability density function calculation unit 22, and the integral value calculation unit 23. The device number output unit 25 includes the device performance information 117 and the device it differs (sets a second design constraint) from the distribution system design support apparatus 1 of the first embodiment in that the number of devices is calculated based on the load occurrence probability information 211 (that is more relaxed than the first design constraint).
MIURA also teaches by analyzing, using the statistical processing or the machine learning, the frequency distribution of the variable extracted by the variable extractor MIURA ([Description | pdf page 7 of 11] “FIG. 17 is a flowchart showing the allocation probability calculation process. Referring to the figure, the allocation probability calculation unit 15 reads (analyzes and extracts) all “content loads" (variable) of each content from the content load information 131 (step S21), and a frequency distribution in which each content is divided (frequency distribution of the variable extracted) into a plurality of classes based on these values. (Histogram) (statistical processing) is created (step S23), and the allocation probability (statistical processing) is calculated (extracted by the variable extractor) for each class using equation (1) (step S25). After step S35, the allocation probability calculation unit 15 ends the allocation probability calculation process.”)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of MIURA with DENG as the references deal with relates to a design support system that verifies design and enables easy setting of a design constraint. MIURA would modify DENG by analyzing, using the statistical processing or the machine learning, the frequency distribution of the variable extracted by the variable extractor. The benefits of doing so aim to provide a technique that facilitates the design of an appropriate distribution system. (MIURA [Description | pdf page 3 of 11]). Accordingly, claim 6 is rejected based on the combination of these references.
The combination of DENG and MIURA does not explicitly teach the executable instructions stored in the memory.
However, PANDEY teaches the executable instructions stored in the memory PANDEY ([Column 10 | Lines 47-60] “The computer system 800 also includes a main memory 806. Such as a random access memory (RAM) or other dynamic storage device, coupled to the bus 802 for storing information and instructions to be executed by the processor 804. The main memory 806 also may be used for storing temporary variables or other inter mediate information during execution of instructions to be executed by the processor 804. The computer system 800 further includes a read only memory (ROM) 808 or other static storage device coupled to the bus 802 for storing static information and instructions for the processor 804. A data storage device 810. Such as a magnetic disk or optical disk, is provided and coupled to the bus 802 for storing information and instructions.”)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of PANDEY with DENG and MIURA as the references deal with relates to a design support system that verifies design and enables easy setting of a design constraint. PANDEY would modify DENG and MIURA wherein the executable instructions stored in the memory. The benefits of doing so performs compression to group similar constraints into single design constraint statement and reduces or minimizes the size of the generated design constraint. (PANDEY [Column 5 | lines 8-12 | pdf page 13 of 18]). Accordingly, claim 6 is rejected based on the combination of these references.
Claim 7
Claim 7 is rejected because the combination of DENG, MIURA, and PANDEY teach the claim 6 limitations.
DENG does not explicitly teach a design reference storage to store the first design constraint defining that the value of the variable is equal to or greater than a first design constraint value or equal to or less than the first design constraint value or the variable extractor extracts from the verified design data the variable having a value less than or greater than the first design constraint value.
However, MIURA teaches a design reference storage to store the first design constraint defining that the value of the variable is equal to or greater than a first design constraint value or equal to or less than the first design constraint value MIURA ([Description |pdf page 4 of 11] “The "storage capacity" is a storage capacity of a storage device (a design reference storage) that can store assigned content (first design constraint) in the device (a design reference storage).”) See also MIURA ([Description | pdf page 5 of 11] “ Specifically, the content number calculation unit 17 reads "average data size” and "total number of contents" (first design constraint) from the content statistical information 115, and reads “storage capacity" of each device from the device performance information 117. The content number calculation unit 17 acquires the "device number" of each device provided in the distribution system, which has been changed by the device number output unit 25, and acquires the content number based on these values. If the number of devices has not been changed by the device number output unit 25 (first design constraint), the content number calculation unit 17 sets a predetermined initial value (for example, one) as the number of devices. And the content number calculation part 17 calculates the value of the content number which satisfy I fills the following (2) Formula and (3) Formula for every device for every device. (Average data size) x (number of contents allocated to the device) ≤ (storage capacity) (defining that the value of the variable is equal to or less than a first design constraint value) (2) ∑ (number of contents allocated to the device) = (total number of contents) (3) In the above equation (3), the left side is a total value of the number of contents allocated to each device.”) See also MIURA ([Description | pdf page 8 of 11] “The distribution system design support device 1 determines (a first design constraint value) whether or not the integral value Pa of the occurrence probability that the random variable x of this function is equal to or greater than the threshold value M (defining that the value of the variable is equal to or greater than) is within a predetermined range. By obtaining an appropriate number of devices so that the fluctuating integral value satisfies the condition according to the variation, the optimum number of devices can be determined, and the design of the distribution system is facilitated.”)
MIURA also teaches extract from the verified design data the variable having a value less than or greater than the first design constraint value MIURA ([Description | pdf pages 8-9 of 11] “The device number output unit 25 calculates (extract) “cumulative value" (variable having a value), which is a value for evaluating the distribution performance (from the verified design data) of the device, for each device by the following equation (7). (Cumulative value of device= ∑ (device load occurrence probability corresponding to device load greater than (greater than the first design constraint) distribution capability) (first design constraint) (7) In the equation (7), the left side is a total value of "device occurrence probabilities” corresponding to "device loads" equal to or higher than the "distribution capability" of the device.”)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of MIURA with DENG as the references deal with relates to a design support system that verifies design and enables easy setting of a design constraint. MIURA would modify DENG wherein extract from the verified design data the variable having a value less than or greater than the first design constraint value. The benefits of doing so aim to provide a technique that facilitates the design of an appropriate distribution system. (MIURA [Description | pdf page 3 of 11]).
The combination of DENG and MIURA does not explicitly teach the executable instructions stored in the memory.
However, PANDEY teaches the executable instructions stored in the memory PANDEY ([Column 10 | Lines 47-60] “The computer system 800 also includes a main memory 806. Such as a random access memory (RAM) or other dynamic storage device, coupled to the bus 802 for storing information and instructions to be executed by the processor 804. The main memory 806 also may be used for storing temporary variables or other inter mediate information during execution of instructions to be executed by the processor 804. The computer system 800 further includes a read only memory (ROM) 808 or other static storage device coupled to the bus 802 for storing static information and instructions for the processor 804. A data storage device 810. Such as a magnetic disk or optical disk, is provided and coupled to the bus 802 for storing information and instructions.”)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of PANDEY with DENG and MIURA as the references deal with relates to a design support system that verifies design and enables easy setting of a design constraint. PANDEY would modify DENG and MIURA wherein the executable instructions stored in the memory. The benefits of doing so performs compression to group similar constraints into single design constraint statement and reduces or minimizes the size of the generated design constraint. (PANDEY [Column 5 | lines 8-12 | pdf page 13 of 18]). Accordingly, claim 7 is rejected based on the combination of these references.
Claim 8
Claim 8 is rejected because the combination of DENG, MIURA, and PANDEY teach the claim 1 limitations.
The combination of DENG and MIURA does not explicitly teach determine a share of a plurality of components in an area of a device to be designed and adjust a design constraint value in accordance with the share of the plurality of components and the executable instructions stored in the memory.
However, PANDEY teaches determine a share of a plurality of components in an area of a device to be designed and adjust a design constraint value in accordance with the share of the plurality of components PANDEY ([Background | Column 1 | Lines 19-33] “Typically, a design flow at various levels of design abstraction involves specifying design constraints (design constraint values) while different synthesis tools (design constraint value adjuster) optimize the design around these constraints (determine a share of a plurality of components in an area of a device to be designed). In case of timing constraints, after synthesis, a static timing analysis (a design constraint value adjuster) is used to verify whether a design is meeting the timing budget (determine a share of a plurality of components in an area of a device to be designed). If this is not the case, the static timing analysis produces a critical path report (adjust a design constraint value in accordance with the share of the plurality of components). Typically, static timing analysis ignores (adjusts) the logic function of the gates in the design. Therefore, certain critical paths may turn out to be not sensitizable. The designer may analyze (find) all the critical paths (design constraint values in accordance with the share of the plurality of components) to determine whether a critical path is a false path or a multi cycle path. Since false paths may not be sensitized, they should not be considered in static timing analysis. For multi cycle paths, the timing budget may be extended (adjusted) to multiple clock cycles. Therefore, if such paths are found, the design constraints are modified (adjusted) accordingly.”)
PANDEY also teaches the executable instructions stored in the memory PANDEY ([Column 10 | Lines 47-60] “The computer system 800 also includes a main memory 806. Such as a random access memory (RAM) or other dynamic storage device, coupled to the bus 802 for storing information and instructions to be executed by the processor 804. The main memory 806 also may be used for storing temporary variables or other inter mediate information during execution of instructions to be executed by the processor 804. The computer system 800 further includes a read only memory (ROM) 808 or other static storage device coupled to the bus 802 for storing static information and instructions for the processor 804. A data storage device 810. Such as a magnetic disk or optical disk, is provided and coupled to the bus 802 for storing information and instructions.”)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of PANDEY with DENG and MIURA as the references deal with relates to a design support system that verifies design and enables easy setting of a design constraint. PANDEY would modify DENG and MIURA wherein the executable instructions stored in the memory. The benefits of doing so performs compression to group similar constraints into single design constraint statement and reduces or minimizes the size of the generated design constraint. (PANDEY [Column 5 | lines 8-12 | pdf page 13 of 18]). Accordingly, claim 8 is rejected based on the combination of these references.
Claim 9
Claim 9 is rejected because the combination of DENG, MIURA, and PANDEY teach the claim 1 limitations.
The combination of DENG and MIURA does not explicitly teach determine a share of a plurality of components in an area of a device to be designed, for each of a plurality of areas and adjust a design constraint value for each of the plurality of areas in accordance with a share of the plurality of components for each of the plurality of areas and the executable instructions stored in the memory.
However, PANDEY teaches determine a share of a plurality of components in an area of a device to be designed, for each of a plurality of areas and adjust a design constraint value for each of the plurality of areas in accordance with a share of the plurality of components for each of the plurality of areas PANDEY ([ Column 7 | Lines 31-48] “FIG.2B is a block diagram of one embodiment of a method 260 for integrating rules in a new design constraint file. In one aspect, the following is a description of 226 of method 200 taken during each activation of the integration mechanism after configuration and all the input data has been provided. 260 begins in 270 (design constraint value adjuster), wherein for each type of constraint specified by the user, such as clocks, external delays, timing exceptions, etc., 270 finds the constraints (find a share of a plurality of components in an area of a device to be designed) of that type in all the Sub-designs or Sub-blocks to be integrated. In 272, each constraint is submitted to an integration rule relevant to the current constraint type. In 274, the integration rule applies (adjusts) all existing rule instances to all existing constraints (a design constraint value for each of the plurality of areas). In 276, each instance, when applied to a constraint (design constraint), checks whether the configured condition is satisfied (in accordance with a share of the plurality of components for each of the plurality of areas) and, in 278, performs the configured action or actions, such as a request to promote, a request not to promote and/or a request to produce a message.”) See also PANDEY ([Figure 2B].)
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PANDEY Figure 2B Reference
PANDEY also teaches the executable instructions stored in the memory PANDEY ([Column 10 | Lines 47-60] “The computer system 800 also includes a main memory 806. Such as a random access memory (RAM) or other dynamic storage device, coupled to the bus 802 for storing information and instructions to be executed by the processor 804. The main memory 806 also may be used for storing temporary variables or other inter mediate information during execution of instructions to be executed by the processor 804. The computer system 800 further includes a read only memory (ROM) 808 or other static storage device coupled to the bus 802 for storing static information and instructions for the processor 804. A data storage device 810. Such as a magnetic disk or optical disk, is provided and coupled to the bus 802 for storing information and instructions.”)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of PANDEY with DENG and MIURA as the references deal with relates to a design support system that verifies design and enables easy setting of a design constraint. PANDEY would modify DENG and MIURA wherein the executable instructions stored in the memory. The benefits of doing so performs compression to group similar constraints into single design constraint statement and reduces or minimizes the size of the generated design constraint. (PANDEY [Column 5 | lines 8-12 | pdf page 13 of 18]). Accordingly, claim 9 is rejected based on the combination of these references.
Claim 10
Claim 10 is rejected because it has similar limitations to claim 1 and is such rejected using the same reasoning found in claim 1.
The combination of DENG and MIURA does not explicitly teach adjust the design constraint value to be higher for a higher share of the plurality of components and the executable instructions stored in the memory .
However PANDEY teaches adjust the design constraint value to be higher for a higher share of the plurality of components PANDEY ([ Column 7 | Lines 31-48] “FIG.2B is a block diagram of one embodiment of a method 260 for integrating rules in a new design constraint file. In one aspect, the following is a description of 226 of method 200 taken during each activation of the integration mechanism after configuration and all the input data has been provided. 260 begins in 270 (design constraint), wherein for each type of constraint specified by the user, such as clocks, external delays, timing exceptions, etc., 270 finds the constraints (plurality of components) of that type in all (design constraint value to be higher for a higher share of the plurality of components) the Sub-designs or Sub-blocks to be integrated. In 272, each constraint is submitted to an integration rule relevant to the current constraint type. In 274, the integration rule applies (adjusts) all existing rule instances to all existing constraints (a design constraint). In 276, each instance, when applied to a constraint (design constraint), checks whether the configured condition is satisfied (plurality of components) and, in 278, performs the configured action or actions, such as a request to promote, a request not to promote and/or a request to produce a message.”) See also PANDEY ([Figure 2B].)
PANDEY also teaches the executable instructions stored in the memory PANDEY ([Column 10 | Lines 47-60] “The computer system 800 also includes a main memory 806. Such as a random access memory (RAM) or other dynamic storage device, coupled to the bus 802 for storing information and instructions to be executed by the processor 804. The main memory 806 also may be used for storing temporary variables or other inter mediate information during execution of instructions to be executed by the processor 804. The computer system 800 further includes a read only memory (ROM) 808 or other static storage device coupled to the bus 802 for storing static information and instructions for the processor 804. A data storage device 810. Such as a magnetic disk or optical disk, is provided and coupled to the bus 802 for storing information and instructions.”)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of PANDEY with DENG and MIURA as the references deal with relates to a design support system that verifies design and enables easy setting of a design constraint. PANDEY would modify DENG and MIURA wherein the executable instructions stored in the memory. The benefits of doing so performs compression to group similar constraints into single design constraint statement and reduces or minimizes the size of the generated design constraint. (PANDEY [Column 5 | lines 8-12 | pdf page 13 of 18]). Accordingly, claim 10 is rejected based on the combination of these references.
Claim 15
Claim 15 is rejected because the combination of DENG, MIURA, and PANDEY teach the claim 1 limitations.
The combination of DENG and MIURA does not explicitly teach verify whether or not a variable included in new design data satisfies the design constraint set by the setter and the executable instructions stored in the memory.
However, PANDEY teaches verify whether or not a variable included in new design data satisfies the design constraint set by the setter PANDEY ([Column 7 | Lines 14-22 | pdf page 14 of 18] “In 240, the partial full-chip design constraint is replaced with the newly written design constraint (new design data), and 200 terminates (variable design constraint either satisfies or does not satisfy the new design data set by the setter). In one embodiment (design verifier), 220 thru 240 of 200 may be repeated 250 for each type of constraint, such as clock timing, input/ output delays, timing exceptions (variable), etc. These may be repeated for the same type of constraints when the results of the diagnosis or evaluation of 230 are not satisfactory and/or acceptable (satisfies or does not satisfy the design constraint) to a user. Following 240, 220 thru 240 may be applied to each type of constraint.”)
PANDEY also teaches the executable instructions stored in the memory PANDEY ([Column 10 | Lines 47-60] “The computer system 800 also includes a main memory 806. Such as a random access memory (RAM) or other dynamic storage device, coupled to the bus 802 for storing information and instructions to be executed by the processor 804. The main memory 806 also may be used for storing temporary variables or other inter mediate information during execution of instructions to be executed by the processor 804. The computer system 800 further includes a read only memory (ROM) 808 or other static storage device coupled to the bus 802 for storing static information and instructions for the processor 804. A data storage device 810. Such as a magnetic disk or optical disk, is provided and coupled to the bus 802 for storing information and instructions.”)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of PANDEY with DENG and MIURA as the references deal with relates to a design support system that verifies design and enables easy setting of a design constraint. PANDEY would modify DENG and MIURA wherein executable instructions stored in the memory. The benefits of doing so performs compression to group similar constraints into single design constraint statement and reduces or minimizes the size of the generated design constraint. (PANDEY [Column 5 | lines 8-12 | pdf page 13 of 18]). Accordingly, claim 15 is rejected based on the combination of these references.
Claim 16
Claim 16 is rejected because it has similar limitations to claim 1 and is such rejected using the same reasoning found in claim 1.
The combination of DENG and MIURA does not explicitly teach receive choice of the design constraint to be applied to the new design data from a plurality of design constraints.
However PANDEY teaches receive choice of the design constraint to be applied to the new design data from a plurality of design constraints PANDEY ([ Column 11 | Lines 45-61] “Various forms of computer-readable media may be involved in carrying one or more sequences of one or more instructions to the processor 804 for execution. For example, the instructions (a plurality of design constraints) may initially be carried on a magnetic disk of a remote computer. The remote computer may load the instructions into its dynamic memory and send the instructions over a telephone line using a modem. A modem local to the computer system (receiver) 800 may receive the data on the telephone line and use an infrared transmitter to convert the data to an infrared signal (to receive choice of the design constraint to be applied to the new design data). An infrared detector coupled to the bus 802 may receive the data carried in the infrared signal and place the data on the bus 802. The bus 802 carries the data to the main memory 806, from which the processor 804 retrieves and executes the instructions. The instructions received by the main memory 806 may optionally be stored on the storage device 810 either before or after execution by the processor 804.”)
PANDEY also teaches verify whether or not a variable included in new design data satisfies the design constraint PANDEY ([Column 7 | Lines 44-49] “In 276, each instance, when applied to a constraint (design constraint), checks whether the configured condition is satisfied (verify whether or not a variable included in new design data satisfies) and, in 278, performs the configured action or actions, such as a request to promote, a request not to promote and/or a request to produce a message.”)
PANDEY also teaches verify whether or not the variable included in the new design data satisfies the received design constraint PANDEY ([Column 7 | Lines 44-49] “In 276, each instance, when applied to a constraint (design constraint), checks whether the configured condition (received design constraint) is satisfied (verify whether or not a variable included in new design data satisfies) and, in 278, performs the configured action or actions, such as a request to promote, a request not to promote and/or a request to produce a message.”)
PANDEY also teaches generate an electronic file including the new design data when the variable satisfies the received design constraint PANDEY ([Column 10 | Lines 47-54] “Integration of block level constraints into a full-chip constraint set (variable satisfies the received design constraint) is a delicate task, because the constraints taken from a block, and in particular the timing exceptions, may take on an unexpected meaning at the top-level. It is of particular importance to avoid manipulating constraints purely at the textual level. In one aspect of the invention, the meaning of the constraints is propagated to top-level entities (set for each of the plurality of groups), and then written out as new commands (generate an electronic file including the new design data) that may (variable satisfies the received design constraint) or may not resemble the original ones.”)
PANDEY also teaches output the electronic file to a design device for providing information to the design device for arranging the plural physical elements so that a target value of a design is met PANDEY ([Column 6 |lines 52:62] “In 222, design constraint integration rules for the electronic circuit design are configured. In one embodiment, configuration of design constraint integration rules (providing information) may be accomplished at any stage before integration (to a design device for to the design device) in 226. This may involve the creation of rule instances (arranging the plural physical elements) that target each particular attribute to be ignored, reported, and/or promoted (target value of a design is met). 222 may be achieved by loading a default configuration file (output the electronic file), or this may be completely user-specific, or this may be a combination of both.”)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of PANDEY with DENG and MIURA as the references deal with relates to a design support system that verifies design and enables easy setting of a design constraint. PANDEY would modify DENG and MIURA wherein outputing the electronic file to a design device for providing information to the design device for arranging the plural physical elements so that a target value of a design is met. The benefits of doing so performs compression to group similar constraints into single design constraint statement and reduces or minimizes the size of the generated design constraint. (PANDEY [Column 5 | lines 8-12 | pdf page 13 of 18]). Accordingly, claim 16 is rejected based on the combination of these references.
Claim 19
Claim 19 is rejected because it is method embodiment of claim 1 with similar limitations to claim 1, and is such rejected using the same reasoning found in claim 1.
Claim 20
Claim 20 is rejected because it is the non-transitory computer-readable recording medium embodiment of claim 1 with similar limitations to claim 1, and is such rejected using the same reasoning found in claim 1.
Claim(s) 2-5, 11 and 12 are rejected under are rejected under 35 U.S.C. 103 as being unpatentable over DENG, in view of MIURA, in view of PANDEY, and in further view of LANGENHUISEN (WO 2008012536 A1), herein LANGENHUISEN.
Claim 2
Claim 2 is rejected because DENG teaches extract from the verified design data a variable that defines a design constraint of plural physical elements of a device in the design data DENG ([Section 3.3. | User Interface of the Verification Design Environment] “The implemented design verification environment is described in this section. The process starts with a designer entering a causal behavioral process (CBP). We shall use a CBP from a paper separation device design as an example. The function of the device (device) is to separate a pack of paper into individual pieces (design constraint) . One possible physical structure is shown in Fig. 3.”) See also DENG ([Section 4.2 Approaches for VDG Development |pdf page 8 of 11] “Furthermore, a constraint graph (CG) (design constraint) can be developed from the reduced VDG (variable dependency graph) (design data) by connecting each constraint node (a design constraint) with its related variables (variables that define a design constraint). The combined graph is called VDG-CG graph. Fig. 8 shows the VDG-CG graph for the paper separation device (device) design produced (extract from the verified design data) by our design verification environment (verified design data). The left-most column of nodes (plural physical elements) is input variables (design data) for deriving output variables (variables that define a design constraint), that is, the input variables (variables that define a design constraint) used as part of the VDG (verified design data). The right-most column of nodes (plural physical elements) is input variables (variables that define a design constraint) not used in the VDG (verified design data), but required by the CG (constraint graph).”)
DENG does not explicitly teach determine an existence probability of the extracted variable.
However, MIURA teaches determine an existence probability of the extracted variable MIURA ([Abstract] “A device probability density function acquiring means acquires the probability (determine an existence probability) at which an event that a distribution load (of the extracted variable) resulting from one request out of all the requests is put on one arbitrary device occurs as an occurrence probability. The device probability density function acquiring means (an existence probability acquirer) determines numerical values (finds an existence probability) equivalent to the system distribution loads (of the extracted variable) as the number of trials and acquires the probability density function (finds an existence probability) of a binomial distribution (extracted variable) with the occurrence probability as the occurrence probability in each of the trials as a device probability density function.”)
MIURA teaches determine cumulative existence probability of the determined existence probability MIURA ([Description | pdf page 8 of 11] “The device number output unit 25 calculates “cumulative value" (determine cumulative existence probability), which is a value for evaluating the distribution performance (determined existence probability) of the device, for each device by the following equation (7).
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of MIURA with DENG as the references deal with relates to a design support system that verifies design and enables easy setting of a design constraint. MIURA would modify DENG wherein determine cumulative existence probability of the determined existence probability. The benefits of doing so aim to provide a technique that facilitates the design of an appropriate distribution system. (MIURA [Description | pdf page 3 of 11]).
The combination of DENG and MIURA does not explicitly teach memory storing executable instructions, receive verified design data for a device to be manufactured, generate an electronic file including the design constraint value of the design constraint, and output the electronic file to a design device for providing information to the design device for arranging the plural physical elements so that a target value of a design target is met.
PANDEY also teaches memory storing executable instructions PANDEY ([Column 10 | Lines 47-54] “The computer system 800 also includes a main memory 806. Such as a random access memory (RAM) or other dynamic storage device, coupled to the bus 802 for storing information and instructions (memory storing executable instructions) to be executed by the processor 804. The main memory 806 also may be used for storing temporary variables or other inter mediate information during execution of instructions to be executed by the processor 804.”)
PANDEY also teaches receive verified design data for a device to be manufactured PANDEY ([Column 5 | Lines 49-53] “FIG. 1 shows one embodiment of a high-level process flow 100 of an automatic constraint generation process (verified design data). As shown, inputs 110, 112, 114 to process 100 are received (receive verified design data) from an RTL or a gate-level design (for a device to be manufactured), existing design constraint specifications (if any), and/or timing reports (if they exist).”)
PANDEY also teaches generate an electronic file including the design constraint value of the design constraint; PANDEY ([Column 10 | Lines 47-54] “Integration of block level constraints into a full-chip constraint set is a delicate task, because the constraints taken from a block, and in particular the timing exceptions, may take on an unexpected meaning at the top-level. It is of particular importance to avoid manipulating constraints (design constraint value) purely at the textual level. In one aspect of the invention, the meaning of the constraints is propagated to top-level entities, and then written out as new commands (generate an electronic file including the design constraint value of the design constraint) that may or may not resemble the original ones.”)
PANDEY also teaches output the electronic file to a design device for providing information to the design device for arranging the plural physical elements so that a target value of a design target is met PANDEY ([Column 6 |lines 52:62] “In 222, design constraint integration rules for the electronic circuit design are configured. In one embodiment, configuration of design constraint integration rules (providing information) may be accomplished at any stage before integration (to a design device for to the design device) in 226. This may involve the creation of rule instances (arranging the plural physical elements) that target each particular attribute to be ignored, reported, and/or promoted (target value of a design is met). 222 may be achieved by loading a default configuration file (output the electronic file), or this may be completely user-specific, or this may be a combination of both.”)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of PANDEY with DENG and MIURA as the references deal with relates to a design support system that verifies design and enables easy setting of a design constraint. PANDEY would modify DENG and MIURA wherein output the electronic file to a design device for providing information to the design device for arranging the plural physical elements so that a target value of a design target is met. The benefits of doing so performs compression to group similar constraints into single design constraint statement and reduces or minimizes the size of the generated design constraint. (PANDEY [Column 5 | lines 8-12 | pdf page 13 of 18]).
The combination of DENG, MIURA, and PANDEY does not teach identify a value of the variable that is a value when the cumulative existence probability matches a preset reference value and set the identified value to a design constraint value of the design constraint
However, LANGENHUISEN identify a value of the variable that is a value when the cumulative existence probability matches a preset reference value and set the identified value to a design constraint value of the design constraint LANGENHUISEN ([Description | pdf page 14 of 29] “As is the case for the identifying means, the grouping means (setter) 4 may comprise several different means for finding (identifying) similarities between process sequences. One example would be to use known "pattern matching" algorithms (cumulative existence probability matches). For example, the system of the present invention could try and express similar process steps using similar symbols (letters, numbers, etc) and use so called "regular expressions" (preset reference value) to find sequences of process steps. To do so, the system would build several regular expressions (set the identified value to a design constraint value of the design constraint) from the first flow under inspection and try to find other flows that match these expressions. This step can be repeated for each flow under inspection. Another method would be to use approaches from symbolic Artificial Intelligence using classificators. This method is used, for example, in text recognition software.
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of LANGENHUISEN with DENG, MIURA, and PANDEY as the references deal with relates to a design support system that verifies design and enables easy setting of a design constraint. LANGENHUISEN would modify DENG, MIURA, and PANDEY wherein identify a value of the variable that is a value when the cumulative existence probability matches a preset reference value and set the identified value to a design constraint value of the design constraint. The benefits of doing reduces the number of failed experiments in semiconductor development processes without relying on or being adversely affected by the experience, expertise and ability of process engineers. (LANGENHUISEN [pdf page 2 of 29]). Accordingly, claim 2 is rejected based on the combination of these references.
Claim 3
Claim 3 is rejected because the combination of DENG, MIURA, PANDEY, and LANGENHUISEN teaches the limitations of claim 2.
DENG teaches extract a plurality of variables that define the design constraint DENG ([Section 4.2. | Approaches for VDG Development] “Remove also the links between these nodes and their respective design variable nodes (extract a plurality of variables). If this produces isolated design variable nodes then these design variable nodes should be removed as well (design constraint). For example, removal of node B2P1 requires removal of nodes B3FV1, B3FV3 (plurality of variables)… Examine all attribute expressions in set TP. If an attribute expression only relates to functional output variables then it should be regarded as a constraint on these variables (design constraints). These attribute expressions need not be processed in the development of VDG and are removed (variable extractor extracts plurality of variables) from the set TP.”) See also DENG ([Figure 8].)
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DENG Figure 8 Reference
DENG does not explicitly teach determine the existence probability of each variable of the extracted plurality of variables.
However, MIURA determine the existence probability of each variable of the extracted plurality of variables MIURA ([Abstract] “A device probability density function acquiring means (an existence probability acquirer) acquires the probability (determine an existence probability) at which an event that a distribution load (of each variable extracted) resulting from one request out of all the requests is put on one arbitrary device occurs as an occurrence probability. The device probability density function acquiring means (an existence probability acquirer) determines numerical values (determine an existence probability) equivalent to the system distribution loads (of the extracted variable) as the number of trials and acquires the probability density function (determine an existence probability) of a binomial distribution (extracted variable) with the occurrence probability as the occurrence probability in each of the trials as a device probability density function.”)
MIURA also teaches determine a cumulative existence probability of the existence probability of each of the plurality of variables MIURA ([Description | pdf page 8 of 11] “The device number output unit (cumulative existence probability acquirer) 25 calculates “cumulative value" (determine cumulative existence probability), which is a value for evaluating the distribution performance (of the found existence probability) of the device, for each device by the following equation (7).
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of MIURA with DENG as the references deal with relates to a design support system that verifies design and enables easy setting of a design constraint. MIURA would modify DENG determine a cumulative existence probability of the existence probability of each of the plurality of variables. The benefits of doing so aim to provide a technique that facilitates the design of an appropriate distribution system. (MIURA [Description | pdf page 3 of 11]).
PANDEY also teaches memory storing executable instructions PANDEY ([Column 10 | Lines 47-54] “The computer system 800 also includes a main memory 806. Such as a random access memory (RAM) or other dynamic storage device, coupled to the bus 802 for storing information and instructions (memory storing executable instructions) to be executed by the processor 804. The main memory 806 also may be used for storing temporary variables or other inter mediate information during execution of instructions to be executed by the processor 804.”)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of PANDEY with DENG and MIURA as the references deal with relates to a design support system that verifies design and enables easy setting of a design constraint. PANDEY would modify DENG and MIURA wherein the executable instructions stored in the memory. The benefits of doing so performs compression to group similar constraints into single design constraint statement and reduces or minimizes the size of the generated design constraint. (PANDEY [Column 5 | lines 8-12 | pdf page 13 of 18]).
The combination of DENG, MIURA, and PANDEY does not teach a setter to identify a value of the variable that is a value when the cumulative existence probability matches a preset reference value and set the identified value to a design constraint value of the design constraint
However, LANGENHUISEN teaches set, to the design constraint value of the design constraint, each value of the plurality of variables when the cumulative existence probability matches the preset reference value LANGENHUISEN ([Description | pdf page 14 of 29] “As is the case for the identifying (set) means, the grouping means (when the cumulative existence probability) 4 may comprise several different means for finding (identifying) similarities between process sequences. One example would be to use known "pattern matching" algorithms (matching preset reference value). For example, the system of the present invention could try and express similar process steps using similar symbols (letters, numbers, etc) and use so called "regular expressions" (design constraint value of the design constraint) to find sequences of process steps. To do so, the system would build several regular expressions (each value of the plurality of variables) from the first flow under inspection and try to find other flows that match these expressions (matches the preset reference value). This step can be repeated for each flow under inspection. Another method would be to use approaches from symbolic Artificial Intelligence using classificators.
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of LANGENHUISEN with DENG, MIURA, and PANDEY as the references deal with relates to a design support system that verifies design and enables easy setting of a design constraint. LANGENHUISEN would modify DENG, MIURA, and PANDEY wherein using set, to the design constraint value of the design constraint, each value of the plurality of variables when the cumulative existence probability matches the preset reference value. The benefits of doing reduces the number of failed experiments in semiconductor development processes without relying on or being adversely affected by the experience, expertise and ability of process engineers. (LANGENHUISEN [pdf page 2 of 29]). Accordingly, claim 3 is rejected based on the combination of these references.
Claim 4
Claim 4 is rejected because the combination of DENG, MIURA, PANDEY, and LANGENHUISEN teaches the limitations of claim 2.
DENG does not teach determine a cumulative existence probability of the new existence probabilities.
However, MIURA teaches determine a cumulative existence probability of the new existence probabilities MIURA ([Description | pdf page 9 of 11] “The device number output unit (cumulative existence probability acquirer) 25 determines whether or not the cumulative value (determine a cumulative existence probability) obtained by the above equation (7) is within a predetermined range for each device (step S7). If it is within the predetermined range (step S7: YES), the device number output unit 25 determines that the number of devices is a necessary minimum value, and outputs the number of devices (new existence probabilities) (step SB). If not within the predetermined range (step S7: NO), the device number output unit 25 increases or decreases the number of devices (new existence probabilities) (step S9).”)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of MIURA with DENG as the references deal with relates to a design support system that verifies design and enables easy setting of a design constraint. MIURA would modify DENG wherein determine a cumulative existence probability of the new existence probabilities. The benefits of doing so aim to provide a technique that facilitates the design of an appropriate distribution system. (MIURA [Description | pdf page 3 of 11]).
The combination of DENG and MIURA does not explicitly teach determine from the found existence probability, one or more new existence probabilities based on an attribute.
However, PANDEY teaches determine from the found existence probability, one or more new existence probabilities based on an attribute PANDEY ([Column 7 | Lines 26-38] “Each time new constraints are created, some embodiments of methods and systems of the invention perform hierarchical consistency checks (the existence probability acquirer finds from the found existence probability), which allow the user to identify any problems before proceeding to a next phase. The user is involved in the process, but manual work is shifted from tedious manipulation of design constraint commands to the (more productive) analysis of results and refinement of the integration configuration. In a resulting design constraint file, newly written commands (one or more new existence probabilities) are accompanied by a clear annotation of the source commands of the attributes (based on an attribute) they convey. In addition, there is an annotation of the name of the rule instance that caused each constraint to be promoted.”)
PANDEY also teaches memory storing executable instructions PANDEY ([Column 10 | Lines 47-54] “The computer system 800 also includes a main memory 806. Such as a random access memory (RAM) or other dynamic storage device, coupled to the bus 802 for storing information and instructions (memory storing executable instructions) to be executed by the processor 804. The main memory 806 also may be used for storing temporary variables or other inter mediate information during execution of instructions to be executed by the processor 804.”)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of PANDEY with DENG and MIURA as the references deal with relates to a design support system that verifies design and enables easy setting of a design constraint. PANDEY would modify DENG and MIURA wherein the executable instructions stored in the memory. The benefits of doing so performs compression to group similar constraints into single design constraint statement and reduces or minimizes the size of the generated design constraint. (PANDEY [Column 5 | lines 8-12 | pdf page 13 of 18]). Accordingly, claim 4 is rejected based on the combination of these references.
Claim 5
Claim 5 is rejected because the combination of DENG, MIURA, PANDEY, and LANGENHUISEN teaches the limitations of claim 2.
DENG does not teach determine, when the determined existence probability has a plurality of extreme values, a plurality of new existence probabilities to separate the plurality of extreme values.
However, MIURA teaches determine, when the determined existence probability has a plurality of extreme values, a plurality of new existence probabilities to separate the plurality of extreme values MIURA ([Description | pdf page 7 of 11] “Returning to FIG. 1, the integral value calculation unit 23 reads (the existence probability acquirer finds) “system distribution load" from the system distribution load information 113, reads "distribution capability” of each device from the content statistical information 115, and reads each device's "distribution capability" from the probability density function information 221. The "device probability density function F (x)' is read, and the integrated value Pa of each device is calculated using the following equation (a plurality of new existence probabilities to separate the plurality of extreme values) (5). In the above equation (5), "N" is "system distribution load". "M" is "delivery capability". 'Max ((x-M), O)" (when the determined existence probability has a plurality of extreme values) is a function that selects the larger value of “x-M" and “0”. The integral value may be calculated using the following equation (6) instead of the above equation (5).
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MIURA also teaches determine a cumulative existence probability of the new existence probabilities MIURA ([Description | pdf page 9 of 11] “The device number output unit (cumulative existence probability acquirer) 25 determines whether or not the cumulative value (determine a cumulative existence probability) obtained by the above equation (7) is within a predetermined range for each device (step S7). If it is within the predetermined range (step S7: YES), the device number output unit 25 determines that the number of devices is a necessary minimum value, and outputs the number of devices (new existence probabilities) (step SB). If not within the predetermined range (step S7: NO), the device number output unit 25 increases or decreases the number of devices (new existence probabilities) (step S9).”)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of MIURA with DENG as the references deal with relates to a design support system that verifies design and enables easy setting of a design constraint. MIURA would modify DENG by using ethe existence probability acquirer finds, when the found existence probability has a plurality of extreme values, a plurality of new existence probabilities to separate the plurality of extreme values. The benefits of doing so aim to provide a technique that facilitates the design of an appropriate distribution system. (MIURA [Description | pdf page 3 of 11]).
PANDEY also teaches memory storing executable instructions PANDEY ([Column 10 | Lines 47-54] “The computer system 800 also includes a main memory 806. Such as a random access memory (RAM) or other dynamic storage device, coupled to the bus 802 for storing information and instructions (memory storing executable instructions) to be executed by the processor 804. The main memory 806 also may be used for storing temporary variables or other inter mediate information during execution of instructions to be executed by the processor 804.”)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of PANDEY with DENG and MIURA as the references deal with relates to a design support system that verifies design and enables easy setting of a design constraint. PANDEY would modify DENG and MIURA wherein the executable instructions stored in the memory. The benefits of doing so performs compression to group similar constraints into single design constraint statement and reduces or minimizes the size of the generated design constraint. (PANDEY [Column 5 | lines 8-12 | pdf page 13 of 18]).
The combination of DENG, MIURA, and PANDEY do not explicitly teach identify a value of the variable that is a value when each of the cumulative existence probabilities matches the preset reference value and sets the identified value to the design constraint value of the design constraint.
However, LANGENHUISEN teaches identify a value of the variable that is a value when each of the cumulative existence probability matches the preset reference value LANGENHUISEN ([Description | pdf page 14 of 29] “As is the case for the identifying means (identify a value of the variable), the grouping means (cumulative existence probability) 4 may comprise several different means for finding (identifying) similarities between process sequences. One example would be to use known "pattern matching" algorithms (matching preset reference value). For example, the system of the present invention could try and express similar process steps using similar symbols (letters, numbers, etc) and use so called "regular expressions" (design constraint value of the design constraint) to find sequences of process steps. To do so, the system would build several regular expressions (each of values of the plurality of variables that are values) from the first flow under inspection and try to find other flows that match these expressions (matches the preset reference value). This step can be repeated for each flow under inspection. Another method would be to use approaches from symbolic Artificial Intelligence using classificators.
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of LANGENHUISEN with DENG, MIURA, and PANDEY as the references deal with relates to a design support system that verifies design and enables easy setting of a design constraint. LANGENHUISEN would modify DENG, MIURA, and PANDEY wherein using identify a value of the variable that is a value when each of the cumulative existence probability matches the preset reference value. The benefits of doing reduces the number of failed experiments in semiconductor development processes without relying on or being adversely affected by the experience, expertise and ability of process engineers. (LANGENHUISEN [pdf page 2 of 29]). Accordingly, claim 5 is rejected based on the combination of these references.
Claim 11
Claim 11 is rejected because the combination of DENG, MIURA, PANDEY, and LANGENHUISEN teaches the limitations of claim 2.
DENG does not explicitly teach classify the variable extracted from the verified design data into a plurality of groups.
However, MIURA teaches classify the variable extracted from the verified design data into a plurality of groups MIURA ([Description | pdf page 5 of 11] “Returning to FIG. 1, the device load calculation unit 19 reads the "class value” (classify the variable) of each class (plurality of groups) from the content load distribution information 151, reads the "number of contents (classified variable) selected (extracted) by each device from the content number information 171 " (from the verified design data), and based on these values to calculate (extract) "device load" (classified variable). The "device load" (classified variable) is a distribution load applied to a device by distributing (extracting) the content (classified variable) stored in the device. Even if the number of contents (classified variable) stored in each device is determined, the device load varies depending on the combination of the content loads (classified variables) of the stored contents. For example, if the stored content includes content with a high content load (variable), the device load becomes a high value. A high content load means high popularity (a classified group). Here, when the content load is represented by a class value (classify the variable), all possible device load values (variable) are extracted.”)
MIURA also teaches set, for each of the plurality groups, the design constraint by analyzing a frequency distribution of the classified variable for each of the plurality of groups MIURA ([Description | pdf page 5 of 11] “Specifically, the allocation probability calculation unit 15 classifies content (a frequency distribution of the classified variable) into a plurality of classes (each of the plurality of groups) based on the value of "content load", and calculates the number of contents (frequency) belonging to each class. In other words, a frequency distribution (histogram) (frequency distribution of the classified variable) using the content as a sample is created. Then, the allocation probability calculation unit 15 calculates the probability (allocation probability) that content belonging to each class is allocated to the device for each class value using the following equation (1). (Class Allocation Probability)= (Class Frequency)/ (Total Content) (1).”)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of MIURA with DENG as the references deal with relates to a design support system that verifies design and enables easy setting of a design constraint. MIURA would modify DENG wherein set, for each of the plurality groups, the design constraint by analyzing a frequency distribution of the classified variable for each of the plurality of groups. The benefits of doing so aim to provide a technique that facilitates the design of an appropriate distribution system. (MIURA [Description | pdf page 3 of 11]).
The combination of DENG and MIURA does not explicitly teach memory storing executable instructions or set, for each of the plurality of groups, the design constraint based on a frequency distribution of the classified variable for each of the plurality of groups.
The combination of DENG and MIURA does not explicitly memory storing executable instructions or set, for each of the plurality of groups, the design constraint based on a frequency distribution of the classified variable for each of the plurality of groups.
However, PANDEY teaches memory storing executable instructions PANDEY ([Column 10 | Lines 47-54] “The computer system 800 also includes a main memory 806. Such as a random access memory (RAM) or other dynamic storage device, coupled to the bus 802 for storing information and instructions (memory storing executable instructions) to be executed by the processor 804. The main memory 806 also may be used for storing temporary variables or other inter mediate information during execution of instructions to be executed by the processor 804.”)
PANDEY also teaches set, for each of the plurality of groups, the design constraint based on a frequency distribution of the classified variable for each of the plurality of groups PANDEY ([Column 4 | Lines 38-40] “some embodiments of methodology of the invention select a set of candidates (set for each of the plurality of groups) by structural analysis of the design (design constraint).”) See also PANDEY ([Column 5 | Lines 49-57] “FIG. 1 shows one embodiment of a high-level process flow 100 of an automatic constraint generation process. As shown, inputs 110, 112, 114 to process 100 are received from an RTL or a gate-level design, existing design constraint specifications (design constraint) (if any), and/or timing reports (if they exist). Given the RTL or gate level design, the design constraint process 100 collects information about path statistics, such as a number of paths (based on a frequency distribution) in the design, a path distribution by delays (classified variable), a number of logic levels (classified variable), etc., and outputs an design constraint file 130.”)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of PANDEY with DENG and MIURA as the references deal with relates to a design support system that verifies design and enables easy setting of a design constraint. PANDEY would modify DENG and MIURA wherein the set, for each of the plurality of groups, the design constraint based on a frequency distribution of the classified variable for each of the plurality of groups. The benefits of doing so performs compression to group similar constraints into single design constraint statement and reduces or minimizes the size of the generated design constraint. (PANDEY [Column 5 | lines 8-12 | pdf page 13 of 18]). Accordingly, claim 11 is rejected based on the combination of these references.
Claim 12
Claim 12 is rejected because the combination of DENG, MIURA, and PANDEY teach the claim 1 limitations.
The combination of DENG and MIURA does not explicitly teach memory storing executable instructions.
However, PANDEY teaches memory storing executable instructions PANDEY ([Column 10 | Lines 47-54] “The computer system 800 also includes a main memory 806. Such as a random access memory (RAM) or other dynamic storage device, coupled to the bus 802 for storing information and instructions (memory storing executable instructions) to be executed by the processor 804. The main memory 806 also may be used for storing temporary variables or other inter mediate information during execution of instructions to be executed by the processor 804.”)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of PANDEY with DENG and MIURA as the references deal with relates to a design support system that verifies design and enables easy setting of a design constraint. PANDEY would modify DENG and MIURA wherein the executable instructions stored in the memory. The benefits of doing so performs compression to group similar constraints into single design constraint statement and reduces or minimizes the size of the generated design constraint. (PANDEY [Column 5 | lines 8-12 | pdf page 13 of 18]).
The combination of DENG, MIURA, and PANDEY does not explicitly teach classify the extracted variable from the verified design data into the plurality of groups using a clustering method.
However, LANGENHUISEN teaches classify the extracted variable from the verified design data into the plurality of groups using a clustering method LANGENHUISEN ([pdf page 7 of 29] “In reference to Figure 3, this method of data mining (classify) comprises a first step of clustering process steps (using a clustering method). One form of clustering (clustering method) sees each process step (extracted variable) being represented as a point in n dimensional space (variable extracted from the verified design data), n being the number of variables in the largest process step found in the data (variables extracted from the verified design data). As shown in Figure 2, each process step (extracted variable) contains a plurality of parameters (plurality of groups). In this method of clustering (clustering method), each parameter (variable) will be assigned (classified) a dimension in a multidimensional Euclidian space (variables extracted from the verified design data).”)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of LANGENHUISEN with DENG, MIURA, and PANDEY as the references deal with relates to a design support system that verifies design and enables easy setting of a design constraint. LANGENHUISEN would modify DENG, MIURA, and PANDEY wherein classify the extracted variable from the verified design data into the plurality of groups using a clustering method. The benefits of doing reduces the number of failed experiments in semiconductor development processes without relying on or being adversely affected by the experience, expertise and ability of process engineers. (LANGENHUISEN [pdf page 2 of 29]). Accordingly, claim 12 is rejected based on the combination of these references.
Claim(s) 13, 14, 17, and 18 are rejected under are rejected under 35 U.S.C. 103 as being unpatentable over DENG, in view of MIURA, in view of PANDEY, in view of LANGENHUISEN, and in further view of INAN (US 20180289313 A1), herein INAN.
Claim 13
Claim 13 is rejected because the combination of DENG, MIURA, and PANDEY teach the claim 12 limitations.
DENG does not explicitly teach wherein the setter sets the design constraint by analyzing, using unsupervised machine learning, the frequency distribution of the variable extracted by the variable extractor.
However, MIURA teaches the frequency distribution of the variable extracted by the variable extractor MIURA ([Description | pdf page 7 of 11] “FIG. 17 is a flowchart showing the allocation probability calculation process. Referring to the figure, the allocation probability calculation unit 15 reads all “content loads" of each content from the content load information 131 (step S21), and a frequency distribution in which each content is divided into a plurality of classes based on these values. (Histogram) is created (step S23), and the allocation probability is calculated for each class using equation (1) (step S25). After step S35, the allocation probability calculation unit 15 ends the allocation probability calculation process.”)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of MIURA with DENG as the references deal with relates to a design support system that verifies design and enables easy setting of a design constraint. MIURA would modify DENG wherein the frequency distribution of the variable extracted by the variable extractor . The benefits of doing so aim to provide a technique that facilitates the design of an appropriate distribution system. (MIURA [Description | pdf page 3 of 11]).
The combination of DENG and MIURA does not explicitly teach memory storing executable instructions or wherein the setter sets the design constraint by analyzing.
However, PANDEY teaches memory storing executable instructions PANDEY ([Column 10 | Lines 47-54] “The computer system 800 also includes a main memory 806. Such as a random access memory (RAM) or other dynamic storage device, coupled to the bus 802 for storing information and instructions (memory storing executable instructions) to be executed by the processor 804. The main memory 806 also may be used for storing temporary variables or other inter mediate information during execution of instructions to be executed by the processor 804.”)
PANDEY also teaches set the design constraint by analyzing PANDEY ([Column 4 | Lines 38-40] “some embodiments (setter) of methodology of the invention select a set of candidates (sets the design constraint) by structural analysis of the design (analyzing a design constraint).”)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of PANDEY with DENG and MIURA as the references deal with relates to a design support system that verifies design and enables easy setting of a design constraint. PANDEY would modify DENG and MIURA wherein set the design constraint by analyzing. The benefits of doing so performs compression to group similar constraints into single design constraint statement and reduces or minimizes the size of the generated design constraint. (PANDEY [Column 5 | lines 8-12 | pdf page 13 of 18]).
The combination of DENG, MIURA, PANDEY, and LANGENHUISEN does not explicitly teach using unsupervised machine learning.
However, INAN teaches using unsupervised machine learning INAN ([0340] “The data analytics efforts will then have two focuses: (1) using unsupervised machine learning (i.e., graph mining) to facilitate clustering of the measured data to determine which signals, and features of signals, provide the best capability in detecting fatigue and "wear-and-tear" (cumulative throughout the season, incorporating metrics such as the number of pitches throughout the season) for the joints.”)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of INAN with DENG, MIURA, PANDEY, and LANGENHUISEN as the references deal with relates to a design support system that verifies design and enables easy setting of a design constraint. INAN would modify DENG, MIURA, PANDEY, and LANGENHUISEN wherein using unsupervised machine learning. The benefits of doing enables high resolution, quantitative assessment of both the structural and hemodynamic characteristics of the knee joint longitudinally for the first time, paving the way to better understanding joint recovery physiology, and designing closed-loop personalized therapies to accelerate the recovery process. (INAN [pdf page 2 of 29]). Accordingly, claim 13 is rejected based on the combination of these references.
Claim 14
Claim 14 is rejected because the combination of DENG, MIURA, PANDEY, LANGENHUISEN, and INAN teach the claim 13 limitations.
DENG does not explicitly teach teaches a frequency distribution of variable extracted from the design data.
However, MIURA teaches a frequency distribution of variable extracted from the design data MIURA ([Description | pdf page 7 of 11] “FIG. 17 is a flowchart showing the allocation probability calculation process. Referring to the figure, the allocation probability calculation unit 15 reads all “content loads" (variable) of each content from the content load information (extracted from the design data) 131 (step S21), and a frequency distribution (frequency distribution) in which each content is divided into a plurality of classes based on these values. (Histogram) is created (step S23), and the allocation probability is calculated for each class using equation (1) (step S25). After step S35, the allocation probability calculation unit 15 ends the allocation probability calculation process.”)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of MIURA with DENG as the references deal with relates to a design support system that verifies design and enables easy setting of a design constraint. MIURA would modify DENG wherein a frequency distribution of variable extracted from the design data. The benefits of doing so aim to provide a technique that facilitates the design of an appropriate distribution system. (MIURA [Description | pdf page 3 of 11]).
The combination of DENG and MIURA does not explicitly teach memory storing executable instructions.
However, PANDEY teaches memory storing executable instructions PANDEY ([Column 10 | Lines 47-54] “The computer system 800 also includes a main memory 806. Such as a random access memory (RAM) or other dynamic storage device, coupled to the bus 802 for storing information and instructions (memory storing executable instructions) to be executed by the processor 804. The main memory 806 also may be used for storing temporary variables or other inter mediate information during execution of instructions to be executed by the processor 804.”)
However, PANDEY teaches set the design constraint by analyzing PANDEY ([Column 4 | Lines 38-40] “some embodimentsof methodology of the invention select a set of candidates (sets the design constraint) by structural analysis of the design (analyzing a design constraint).”)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of PANDEY with DENG and MIURA as the references deal with relates to a design support system that verifies design and enables easy setting of a design constraint. PANDEY would modify DENG and MIURA wherein set the design constraint by analyzing. The benefits of doing so performs compression to group similar constraints into single design constraint statement and reduces or minimizes the size of the generated design constraint. (PANDEY [Column 5 | lines 8-12 | pdf page 13 of 18]).
The combination of DENG, MIURA, and PANDEY does not explicitly teach extract the variable from each of design data determined as a pass through verification and design data determined as a fail through the verification.
However, LANGENHUISEN teaches extract the variable from each of design data determined as a pass through verification and design data determined as a fail through the verification LANGENHUISEN ([pdf page 17 of 29] “Yet another example would include using inspection and Artificial Intelligence methods to evaluate the parameters of failed and successful sequences (design data determined as pass or fail through the verification) that are similar and compare these parameters. If the failed sequences always have a certain behaviour (e.g. always exceed 500 degrees Celsius), a rule regarding this parameter 30 may be created (extract the variable) (e.g. temperature must not exceed 500 degrees Celsius).”)
LANGENHUISEN also teaches a frequency distribution of variable extracted from the design data determined as the pass and a frequency distribution of variable extracted from the design data determined as the fail LANGENSHUISEN ([pdf page 17 of 29] “Yet another example would include using Inspection and Artificial Intelligence methods to evaluate the parameters of failed and successful sequences (frequency distribution of variable extracted from the design data) that are similar and compare these parameters. If the failed sequences (determined as a fail) always have a certain behaviour (e.g. always exceed 500 degrees Celsius), a rule (determined as a pass) regarding this parameter 30 may be created (e.g. temperature must not exceed 500 degrees Celsius).”)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of LANGENHUISEN with DENG, MIURA, and PANDEY as the references deal with relates to a design support system that verifies design and enables easy setting of a design constraint. LANGENHUISEN would modify DENG, MIURA, and PANDEY wherein a frequency distribution of variable extracted from the design data determined as the pass and a frequency distribution of variable extracted from the design data determined as the fail. The benefits of doing reduces the number of failed experiments in semiconductor development processes without relying on or being adversely affected by the experience, expertise and ability of process engineers. (LANGENHUISEN [pdf page 2 of 29]).
The combination of DENG, MIURA, PANDEY, and LANGENHUISEN does not explicitly teach using the unsupervised machine learning.
However, INAN teaches using the unsupervised machine learning INAN ([0340] “The data analytics efforts will then have two focuses: (1) using unsupervised machine learning (i.e., graph mining) to facilitate clustering of the measured data to determine which signals, and features of signals, provide the best capability in detecting fatigue and "wear-and-tear" (cumulative throughout the season, incorporating metrics such as the number of pitches throughout the season) for the joints.”)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of INAN with DENG, MIURA, PANDEY, and LANGENHUISEN as the references deal with relates to a design support system that verifies design and enables easy setting of a design constraint. INAN would modify DENG, MIURA, PANDEY, and LANGENHUISEN wherein using the unsupervised machine learning. The benefits of doing enables high resolution, quantitative assessment of both the structural and hemodynamic characteristics of the knee joint longitudinally for the first time, paving the way to better understanding joint recovery physiology, and designing closed-loop personalized therapies to accelerate the recovery process. (INAN [pdf page 2 of 29]). Accordingly, claim 14 is rejected based on the combination of these references.
Claim 17
Claim 17 is rejected because the combination of DENG, MIURA, and PANDEY teach the claim 15 limitations.
The combination of DENG and MIURA does not explicitly teach memory storing executable instructions.
However, PANDEY teaches memory storing executable instructions PANDEY ([Column 10 | Lines 47-54] “The computer system 800 also includes a main memory 806. Such as a random access memory (RAM) or other dynamic storage device, coupled to the bus 802 for storing information and instructions (memory storing executable instructions) to be executed by the processor 804. The main memory 806 also may be used for storing temporary variables or other inter mediate information during execution of instructions to be executed by the processor 804.”)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of PANDEY with DENG and MIURA as the references deal with relates to a design support system that verifies design and enables easy setting of a design constraint. PANDEY would modify DENG and MIURA wherein memory storing executable instructions. The benefits of doing so performs compression to group similar constraints into single design constraint statement and reduces or minimizes the size of the generated design constraint. (PANDEY [Column 5 | lines 8-12 | pdf page 13 of 18]).
The combination of DENG, MIURA, PANDEY, and LANGENHUISEN does not explicitly teach update the design constraint based on a verification result of whether or not the variable verified by the design verifier and included in the new design data satisfies the design constraint.
However, INAN teaches teach update the design constraint based on a verification result of whether or not the variable verified by the design verifier and included in the new design data satisfies the design constraint INAN ([0247] “The is fed to a peak detection algorithm signal to detect heart beats. Peaks in the waveform are searched window-by-window (design constraint). When a peak is found within the given window, the window size is updated (update) using previous heartbeat intervals (based on a verification result of whether or not the variable verified by the design verifier). The window is then moved to its next location. To make sure the heartbeats are detected precisely, the window is relocated such that the peak is around the mid-point (new design data in satisfies the design constraint) of the given window.”)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of INAN with DENG, MIURA, and PANDEY as the references deal with relates to a design support system that verifies design and enables easy setting of a design constraint. INAN would modify DENG, MIURA, and PANDEY wherein update the design constraint based on a verification result of whether or not the variable verified by the design verifier and included in the new design data satisfies the design constraint. The benefits of doing enables high resolution, quantitative assessment of both the structural and hemodynamic characteristics of the knee joint longitudinally for the first time, paving the way to better understanding joint recovery physiology, and designing closed-loop personalized therapies to accelerate the recovery process. (INAN [pdf page 2 of 29]). Accordingly, claim 17 is rejected based on the combination of these references.
Claim 18
Claim 18 is rejected because the combination of DENG, MIURA, PANDEY, LANGENHUISEN, and INAN teach the claim 17 limitations.
The combination of DENG and MIURA does not explicitly teach memory storing executable instructions.
However, PANDEY teaches memory storing executable instructions PANDEY ([Column 10 | Lines 47-54] “The computer system 800 also includes a main memory 806. Such as a random access memory (RAM) or other dynamic storage device, coupled to the bus 802 for storing information and instructions (memory storing executable instructions) to be executed by the processor 804. The main memory 806 also may be used for storing temporary variables or other inter mediate information during execution of instructions to be executed by the processor 804.”)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of PANDEY with DENG and MIURA as the references deal with relates to a design support system that verifies design and enables easy setting of a design constraint. PANDEY would modify DENG and MIURA wherein memory storing executable instructions. The benefits of doing so performs compression to group similar constraints into single design constraint statement and reduces or minimizes the size of the generated design constraint. (PANDEY [Column 5 | lines 8-12 | pdf page 13 of 18]).
The combination of DENG, MIURA, PANDEY does not explicitly teach receive modification to the verification result from a user, and update the design constraint based on the verification result to which the modification is added.
However, LANGENHUISEN teaches teach receive modification to the verification result from a user, and update the design constraint based on the verification result to which the modification is added LANGENHUISEN ([pdf page 6 of 29] “The receiving means 2 (receive) may be one of several known receiving means such as a data-communications network connection, or the like. The receiving means 2 may also comprise formatting means for formatting (modifications) the process step data (verification result from a user) into a specific format (updates the design constraint based on the verification result) in order for it to be more easily processed (to which the modification is added) by the identifying means 3. The identifying means 3 for identifying similarities between the process steps may accomplish the identification of similar process steps in a plurality of different ways.
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of LANGENHUISEN with DENG, MIURA, and PANDEY as the references deal with relates to a design support system that verifies design and enables easy setting of a design constraint. LANGENHUISEN would modify DENG, MIURA, and PANDEY wherein receive modification to the verification result from a user, and update the design constraint based on the verification result to which the modification is added. The benefits of doing reduces the number of failed experiments in semiconductor development processes without relying on or being adversely affected by the experience, expertise and ability of process engineers. (LANGENHUISEN [pdf page 2 of 29]). Accordingly, claim 18 is rejected based on the combination of these references.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/M.K.V./Examiner, Art Unit 2186
/RENEE D CHAVEZ/Supervisory Patent Examiner, Art Unit 2186