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 Amendment
This action is in response to the amendment and remarks filed 9-10-2025. In the amendment, claims 1, 5, 7, 11, 12, 17, 21, 22, and 25 were amended, claims 26-28 were canceled, and claims 29-31 were added. Thus, claims 1-25 and 29-31 are pending.
The objections of the specification and claims 1-25, set forth in the Office Action issued 6-10-2025 (hereinafter “the previous Office Action”), have been withdrawn.
Claim Interpretation
Examiner is interpreting the use of “ones of the pairs” throughout claims 1, 5, 7, 11-12, 17, 21-22, and 25 as referring to a singular pair derived from the multiple “pairs of programs”.
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 7 and 17 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.
Regarding Claims 7 and 17:
Claims 7 and 17 recite “respective ones of pairs of programs”. Claims 1 and 11 also recite “respective ones of pairs of programs”. It is unclear if the respective ones of pairs of programs from claims 7 and 17 refer to the respective ones of pairs of programs from claim 1 and 11 (respectively), or claims 7 and 17 refer to different respective ones of pairs of programs entirely. Examiner is interpreting claims 7 and 17 to be referring to claim 1 and 11. Therefore, Applicant is advised to amend “respective ones of pairs of programs” to “the respective ones of pairs of programs”.
Claim Rejections - 35 USC § 101
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claims 1-25 and 29-31 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim 1
Step 1: The claim recites [a]n apparatus; therefore, it is directed to the statutory category of machine.
Step 2A Prong 1: The claim recites, inter alia:
[S]ample pairs of programs, the pairs of programs including first programs and second programs, the first programs including natural language descriptions:
This limitation could encompass a human mentally sampling the pairs of programs and writing them with a pen and paper.
[C]alculate program similarity scores corresponding to the pairs of programs: This limitation could encompass a human could mentally performing the calculations to determine how similar the programs are and provide a score with a pen and paper.
Step 2A Prong 2: This judicial exception is not granted into a practical application. The additional elements of the claim are:
An apparatus comprising: at least one memory; instructions; and processor circuitry to execute the instructions to: This limitation recites mere instruction to apply exception using a generic computer. MPEP § 2106.05(f).
[T]rain a machine learning model to generate an output similarity score based on a comparison between the pairs of the programs and an external program, the machine learning model trained based on entries corresponding to respective ones of the pairs of programs, at least one of the entries including: a corresponding one of the natural language descriptions with a paired one of the second programs, and a corresponding one of the program similarity scores. Stating that the method of training a model based on entries corresponding to one of the pairs of programs is mere instruction to apply the exception using a generic computer. MPEP § 2106.05(f).
Step 2B: [A]t least one memory; instructions; and processor circuitry to execute the instructions to: This limitation recites mere instruction to apply exception using a generic computer. MPEP § 2106.05(f). Apple, Inc. v. Ameranth, Inc., 842 F.3d 1229, 1243-44, 120 USPQ2d 1844, 1855-57 (Fed. Cir.2016).
[T]rain a machine learning model to generate an output similarity score based on a comparison between the pairs of the programs and an external program, the machine learning model trained based on entries corresponding to respective ones of the pairs of programs, at least one of the entries including: a corresponding one of the natural language descriptions with a paired one of the second programs, and a corresponding one of the program similarity scores. Stating that the method of training a model based on entries corresponding to one of the pairs of programs is mere instruction to apply the exception using a generic computer. MPEP § 2106.05(f). Apple, Inc. v. Ameranth, Inc., 842 F.3d 1229, 1243-44, 120 USPQ2d 1844, 1855-57 (Fed. Cir. 2016).
The claim does not contain significantly more than the judicial exception.
Claim 2
Step 1: A machine, as above.
Step 2A Prong 1: The claim recites the same mental process as in claim 1.
Step 2A Prong 2: This judicial exception is not granted into a practical application. The additional elements of the claim are:
[W]herein the entries further include a corresponding one of the first programs paired with the one of the second programs: This limitation recites insignificant extra-solution activity of mere data gathering. MPEP § 2106.05(g)
Step 2B: [W]herein the entries further include a corresponding one of the first programs paired with the one of the second programs: This limitation recites insignificant extra-solution activity of mere data gathering. The entries limitation is well-understood, routine, and conventional (“WURC”) because it is directed to receiving or transmitting data over a network. MPEP § 2106.05(d)(II); OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 U.S.P.Q.2d 1090, 1093 (Fed Cir. 2015) (sending messages over a network).
The claim does not contain significantly more than the judicial exception.
Claim 3
Step 1: A machine, as above.
Step 2A Prong 1: The claim recites the same mental process as in claim 1.
Step 2A Prong 2: This judicial exception is not granted into a practical application. The additional elements of the claim are:
[W]herein the processor circuitry is to execute the instructions to generate the second programs with a genetic algorithm. Stating that the method is performed by a processor circuitry is mere instruction to apply the exception using a generic computer. MPEP § 2106.05(f).
Step 2B: [W]herein the processor circuitry is to execute the instructions to generate the second programs with a genetic algorithm. Stating that the method is performed by a processor circuitry is mere instruction to apply the exception using a generic computer. MPEP § 2106.05(f). Apple, Inc. v. Ameranth, Inc., 842 F.3d 1229, 1243-44, 120 USPQ2d 1844, 1855-57 (Fed. Cir. 2016).
The claim does not contain significantly more than the judicial exception.
Claim 4
Step 1: A machine, as above.
Step 2A Prong 1: The claim recites the same mental process as in claim 1.
Step 2A Prong 2: This judicial exception is not granted into a practical application. The additional elements of the claim are:
[W]herein the processor circuitry is to execute the instructions to train the model further based on at least one of an input or an output associated with the input. Stating that the method is performed by a processor circuitry is mere instruction to apply the exception using a generic computer. MPEP § 2106.05(f).
Step 2B: [W]herein the processor circuitry is to execute the instructions to train the model further based on at least one of an input or an output associated with the input. Stating that the method is performed by a processor circuitry is mere instruction to apply the exception using a generic computer. MPEP § 2106.05(f). Apple, Inc. v. Ameranth, Inc., 842 F.3d 1229, 1243-44, 120 USPQ2d 1844, 1855-57 (Fed. Cir. 2016).
The claim does not contain significantly more than the judicial exception.
Claim 5
Step 1: A machine, as above.
Step 2A Prong 1: The claim recites the same mental process as in claim 4.
Step 2A Prong 2: This judicial exception is not granted into a practical application. The additional elements of the claim are:
[W]herein respective ones of the entries further include the input and the output, the output generated by providing the input to one of at least one of the first or second programs. This limitation recites insignificant extra-solution activity of mere data gathering and output. MPEP § 2106.05(g).
Step 2B: [W]herein respective ones of the entries further include the input and the output, the output generated by providing the input to one of at least one of the first or second programs. This limitation recites insignificant extra-solution activity of mere data gathering and output. MPEP § 2106.05(g). Upon reevaluation, the providing the input to one of at least one of the first or second programs limitation is well-understood, routine, and conventional (“WURC”) because it is directed to receiving or transmitting data over a network. MPEP § 2106.05(d)(II); OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 U.S.P.Q.2d 1090, 1093 (Fed Cir. 2015) (sending messages over a network).
The claim does not contain significantly more than the judicial exception.
Claim 6
Step 1: A machine, as above.
Step 2A Prong 1: The claim recites the same mental process as in claim 1.
Step 2A Prong 2: This judicial exception is not granted into a practical application. The additional elements of the claim are:
[W]herein the processor circuitry is to execute the instructions to filter the pairs of programs: Stating that the method is performed by a processor circuitry is mere instruction to apply the exception using a generic computer. MPEP § 2106.05(f).
Step 2B: [W]herein the processor circuitry is to execute the instructions to filter the pairs of programs: Stating that the method is performed by a processor circuitry is mere instruction to apply the exception using a generic computer. MPEP § 2106.05(f). Apple, Inc. v. Ameranth, Inc., 842 F.3d 1229, 1243-44, 120 USPQ2d 1844, 1855-57 (Fed. Cir. 2016).
The claim does not contain significantly more than the judicial exception.
Claim 7
Step 1: A machine, as above.
Step 2A Prong 1: The claim recites inter alia:
[T]o filter the pairs of programs by removing respective ones of the pairs of programs that have predominant scores: This limitation could encompass a human mentally performing filtering one of the pairs of programs by removing one of the pairs of programs that have a predominant scores and writing them down with a pen and paper.
Step 2A Prong 2: This judicial exception is not granted into a practical application. The additional elements of the claim are:
[W]herein the processor circuitry is to execute the instructions: Stating that the method is performed by a processor circuitry is mere instruction to apply the exception using a generic computer. MPEP § 2106.05(f).
Step 2B: [W]herein the processor circuitry is to execute the instructions: Stating that the method is performed by a processor circuitry is mere instruction to apply the exception using a generic computer. MPEP § 2106.05(f). Apple, Inc. v. Ameranth, Inc., 842 F.3d 1229, 1243-44, 120 USPQ2d 1844, 1855-57 (Fed. Cir. 2016).
The claim does not contain significantly more than the judicial exception.
Claim 8
Step 1: A machine, as above.
Step 2A Prong 1: The claim recites inter alia:
[T]o calculate the program similarity scores via a code semantics similarity algorithm. A human can mentally calculate the similarity scores and write them with a pen and paper.
Step 2A Prong 2: This judicial exception is not granted into a practical application. The additional elements of the claim are:
[W]herein the processor circuitry is to execute the instructions: Stating that the method is performed by a processor circuitry is mere instruction to apply the exception using a generic computer. MPEP § 2106.05(f)
Step 2B: [W]herein the processor circuitry is to execute the instructions to calculate the program similarity scores via a code semantics similarity algorithm. Stating that the method is performed by a processor circuitry is mere instruction to apply the exception using a generic computer. MPEP § 2106.05(f). Apple, Inc. v. Ameranth, Inc., 842 F.3d 1229, 1243-44, 120 USPQ2d 1844, 1855-57 (Fed. Cir. 2016).
The claim does not contain significantly more than the judicial exception.
Claim 9
Step 1: A machine, as above.
Step 2A Prong 1: The claim recites the same mental process as in claim 1.
Step 2A Prong 2: This judicial exception is not granted into a practical application. The additional elements of the claim are:
[W]herein the processor circuitry is to execute the instructions to train the model with a long-short-term memory (LSTM) neural network. Stating that the processor circuitry is to execute the instructions to train the model with a long-short-term memory (LSTM) neural network merely indicates field of use or technological environment in which the judicial exception is performed. MPEP § 2106.05(h).
Step 2B: [W]herein the processor circuitry is to execute the instructions to train the model with a long-short-term memory (LSTM) neural network. Stating that the processor circuitry is to execute the instructions to train the model with a long-short-term memory (LSTM) neural network merely indicates field of use or technological environment in which the judicial exception is performed. MPEP § 2106.05(h). FairWarning v. Iatric Sys., 839 F.3d 1089, 1094-95, 120 USPQ2d 1293, 1295 (Fed. Cir. 2016).
The claim does not contain significantly more than the judicial exception.
Claim 10
Step 1: A machine, as above.
Step 2A Prong 1: The claim recites the same mental process as in claim 9.
Step 2A Prong 2: This judicial exception is not granted into a practical application. The additional elements of the claim are:
[W]herein the LSTM neural network is a bi-directional LSTM training network. Stating that the LSTM neural network is a bi-directional LSTM training network merely indicates field of use or technological environment in which the judicial exception is performed. MPEP § 2106.05(h).
Step 2B: [W]herein the LSTM neural network is a bi-directional LSTM training network. Stating that the LSTM neural network is a bi-directional LSTM training network merely indicates field of use or technological environment in which the judicial exception is performed. MPEP § 2106.05(h). FairWarning v. Iatric Sys., 839 F.3d 1089, 1094-95, 120 USPQ2d 1293, 1295 (Fed. Cir. 2016).
The claim does not contain significantly more than the judicial exception.
Claims 11-20
Step 1: Claims 11-20 are directed to a non-transitory computer readable medium, corresponding to apparatus claims 1-10.
Step 2A Prong 1: The claim recites the same abstract ideas as in claims 1-10. Specifically 11:1, 12:2, 13:3, 14:4, 15:5, 16:6, 17:7, 18:8, 19:9, and 20:10.
Step 2A Prong 2: There are no additional elements in this claim that integrate the judicial exception into a practical application. The analysis of claims 11-20 at this step mirror that of claims 1-10, with the exception of the following limitation from claim 11:
A non-transitory computer readable medium comprising instructions, which when executed, cause at least one processor to: This limitation recites mere instruction to apply exception using a generic computer. MPEP § 2106.05(f).
Step 2B: There are no additional elements in this claim that amount to significantly more than the judicial exception. The analysis of claims 11-20 at this step mirror that of claims 1-10, with the exception of the following limitation from claim 11:
A non-transitory computer readable medium comprising instructions, which when executed, cause at least one processor to: This limitation recites mere instruction to apply exception using a generic computer. MPEP § 2106.05(f). Apple, Inc. v. Ameranth, Inc., 842 F.3d 1229, 1243-44, 120 USPQ2d 1844, 1855-57 (Fed. Cir.2016).
Claims 21-25
Step 1: Claims 21-25 are directed to a method, corresponding to apparatus claims 1-5.
Step 2A Prong 1: The claim recites the same abstract ideas as in claims 1-5. Specifically 21:1, 22:2, 23:3, 24:4, and 25:5.
Step 2A Prong 2: There are no additional elements in this claim that integrate the judicial exception into a practical application. The analysis of claims 21-25 at this step mirror that of claims 1-5.
Step 2B: There are no additional elements in this claim that amount to significantly more than the judicial exception. The analysis of claims 21-25 at this step mirror that of claims 1-5.
Claim Rejections - 35 USC § 103
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claims 1-3, 8, 11-13, 18, and 21-23 are rejected under 35 U.S.C. 103 as being unpatentable over Kurabayashi et al. (US 20230089227), hereinafter Kura, in view of Whitelock et al. (US 20080126074), hereinafter White, further in view of Bahrami et al. (US 20220236964), hereinafter Bahrami, and further in view of Yoshimura (US 20180189492), hereinafter Yoshi.
Regarding Claim 1:
Kura discloses:
An apparatus comprising: at least one memory; instructions; and processor circuitry to execute the instructions to
Kura, Claim 6, “A computer-readable non-transitory recording medium storing computer-executable program instructions that when executed by a processor cause a computer to execute a method comprising:”
sample pairs of programs, the pairs of programs including first programs and second programs, the first programs including natural language descriptions
Kura, [0023], “The program generation device 10 also includes a search data set 16. As described later, the search data set 16 is a set of search data pieces that are each expressed as a pair of a program (a source code of the program) [second program] and a specification of the program written in natural language [first program].”
the machine learning model trained based on entries corresponding to respective ones of the pairs of programs, at least one of the entries including: a corresponding one of the natural language descriptions with a paired one of the second programs
Kura, [0026], “In the similar code search processing, a specification that is written in natural language for the program to be generated (hereinafter referred to as the "target program") [second program] and specifications written in natural language [first program] for programs included in respective search data pieces of the search data set 16 are input [entry] to the trained machine learning model, which has been trained in step Sl0, to find a source code (hereinafter referred to as a "similar code") of a program that has a specification similar to the specification of the target program from the search data set 16.”
Kura does not explicitly disclose:
calculate program similarity scores corresponding to the pairs of programs
train a machine learning model to generate an output similarity score based on a comparison between the pairs of programs and an external program
a corresponding one of the program similarity scores
However, in the same field, analogous art White teaches:
calculate program similarity scores corresponding to the pairs of programs
White, [0022], “The thesaurus information is a code. The codes are such that any pair of codes [programs] can be compared to provide a numerical measure of the similarity of said codes.”
[0029] “For two items in correspondence, the cross-product of the thesaurus codes associated with the two items is submitted to the similarity computation. The similarity value of the most similar pair or pairs is passed back to the comparer (S7) for use in the global computation of similarity.”
a corresponding one of the program similarity scores
White, [0022], “The thesaurus information is a code. The codes are such that any pair of codes can be compared to provide a numerical measure of the similarity of said codes.”
[0029] “For two items in correspondence, the cross-product of the thesaurus codes associated with the two items is submitted to the similarity computation. The similarity value of the most similar pair or pairs is passed back to the comparer (S7) for use in the global computation of similarity.”
Kura, White, and the instant application are analogous art because they are all directed to determining similarity.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to combine Kura with the calculation of program similarity scores corresponding to the pairs of programs from White. Doing so would improve the matching of texts. (White, [0006]).
Kura in view of White does not explicitly disclose:
train a machine learning model to generate an output similarity score based on a comparison between the pairs of programs and an external program
However, in the same field, analogous art Bahrami teaches:
train a machine learning model to generate an output similarity score based on a comparison between the pairs of programs…
Bahrami, [0059], “At block 540, a similarity score between the search vector and the description-code vector may be determined.”
[0055], “the machine learning model 130 may perform one or more of the operations associated with the method 500.”
[0031], “the description-code vectors included in the augmented programming language corpus may be considered positively classified examples for training the machine learning model such that the machine learning model is trained to consider the code description paired to the section of source code in a positively classified description-code vector to be a valid relation.”
In paragraph 59, Bahrami discloses obtaining a similarity score [generate an output similarity score] by performing a comparison using a description-code vector as one of the comparison elements [comparison between the pairs of programs]. Paragraph 55 further specifies that method 500, discussed in paragraph 59, is performed using an machine learning model. The model is trained on these code description pairs as disclosed in paragraph 31 [train a machine learning model].
Kura, White, Bahrami, and the instant application are analogous art because they are all directed to determining similarity.
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify Kura and White with Bahrami in order to improve the content, relevance, and/or accuracy of the machine learning model. “Additionally or alternatively, the applicability of the given code comment to the particular section of source code may provide further insight for the machine learning system in determining the applicability of the particular sections of source code to queries. For example, by properly associating particular comments with particular sections of source code, those sections of source code may be better classified and/or identified by the machine learning system” (Bahrami, [0016]).
In the same field, analogous art Yoshi teaches:
…a machine learning model to generate an output similarity score based on a comparison between the…[program] and an external program
Yoshi, [0030], “The determining unit 30 determines the similarity between the original program 11A and the target program 11B based on the result of comparison between the code of the original program 11A and the code of the target program 11B and the result of comparison between information acquired at the time of execution of the original program 11A and information acquired at the time of execution of the target program 11B.”
[0050]-[0051], “Subsequently, the determining unit 30 determines the similarity (score)…(S6). In the determination of the similarity in S6, the degree of similarity between an N-gram model based on…may be obtained as the score.”
In paragraph 30, Yoshi using a determining unit [machine learning model] to determine the similarity [generate an output similarity score] based on a comparison between the code of an original program [program] and the code of a target program [external program]. Paragraphs 50-51 further specifies that the determining unit, which determines the similarity score, is a model.
Kura, White, Bahrami, Yoshi, and the instant application are analogous art because they are all directed to determining similarity.
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify Kura, White, and Bahrami with Yoshi in order to more quickly and easily identify similar programs when there are many programs. “In an aspect, it is an object to provide a similarity judgment program, a similarity judgment method, and an information processing apparatus, capable of easily detecting a lot of various subspecies of malware” (Yoshimura, [0017]).
Regarding Claim 2:
As discussed above, Kura in view of White, further in view of Bahrami, and further in view of Yoshi teach [the] apparatus as defined in claim 1, and Kura further discloses:
wherein the entries further include a corresponding one of the first programs paired with the one of the second programs
Kura, [0026], “In the similar code search processing, a specification that is written in natural language for the program to be generated (hereinafter referred to as the "target program") [second program] and specifications written in natural language [first program] for programs included in respective search data pieces of the search data set 16 are input [entry] to the trained machine learning model, which has been trained in step Sl0, to find a source code (hereinafter referred to as a "similar code") of a program that has a specification similar to the specification of the target program from the search data set 16.”
Regarding Claim 3:
As discussed above, Kura in view of White, further in view of Bahrami, and further in view of Yoshi teach [the] apparatus as defined in claim 1, and Kura further discloses:
wherein the processor circuitry is to execute the instructions
Kura, Claim 6, “A computer-readable non-transitory recording medium storing computer-executable program instructions that when executed by a processor cause a computer to execute a method comprising:”
generate the second programs with a genetic algorithm
Kura, [0053], “For example, a genetic algorithm may be used to partially change the synthesized code. That is, a genetic operation may be performed [executed] N times on the synthesized code of the previous generation to generate N synthesized codes of the next generation. Here, N represents the number of individuals (source codes) of a single generation of the genetic algorithm.”
Regarding Claim 8:
As discussed above, Kura in view of White, further in view of Bahrami, and further in view of Yoshi teach [the] apparatus as defined in claim 1, and Kura further discloses:
wherein the processor circuitry is to execute the instructions
Kura, Claim 6, “A computer-readable non-transitory recording medium storing computer-executable program instructions that when executed by a processor cause a computer to execute a method comprising:”
White further discloses:
to calculate the program similarity scores via a code semantics similarity algorithm
White, [0022], “The thesaurus information is a code. The codes are such that any pair of codes can be compared to provide a numerical measure of the similarity of said codes.”
[0029] “For two items in correspondence, the cross-product of the thesaurus codes associated with the two items is submitted to the similarity computation. The similarity value of the most similar pair or pairs is passed back to the comparer (S7) for use in the global computation of similarity.”
[0049] “In practise, the most likely candidates may first be pre-fetched using techniques common in the literature of information retrieval [Information Retrieval, Van Rijsbergen, Butterworths, 1979], possibly using n-gram techniques and semantic proximity. The score may also be computed by including information from the unmatched_parts described hereinafter. The similarity computation may make use of dynamic programming procedures common in the approximate string matching [semantic similarity] and bioinformatics fields.”
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to combine Kura with program similarity scores calculated with a code semantic similarity algorithm from White. Doing so would allow for the programs to be paired based on the similarity calculation. (White, [0029]).
Regarding Claim 11:
Claim 11 is a non-transitory computer readable medium claim corresponding to apparatus claim 1 and is rejected for at least the same reasons as given in the rejection of claim 1.
Regarding Claim 12:
Claim 12 is a non-transitory computer readable medium claim corresponding to apparatus claim 2 and is rejected for at least the same reasons as given in the rejection of claim 2.
Regarding Claim 13:
Claim 13 is a non-transitory computer readable medium claim corresponding to apparatus claim 3 and is rejected for at least the same reasons as given in the rejection of claim 3.
Regarding Claim 18:
Claim 18 is a non-transitory computer readable medium claim corresponding to apparatus claim 8 and is rejected for at least the same reasons as given in the rejection of claim 8.
Regarding Claim 21:
Claim 21 is a method claim corresponding to apparatus claim 1 and is rejected for at least the same reasons as given in the rejection of claim 1.
Regarding Claim 22:
Claim 22 is a method claim corresponding to apparatus claim 2 and is rejected for at least the same reasons as given in the rejection of claim 2.
Regarding Claim 23:
Claim 23 is a method claim corresponding to apparatus claim 3 and is rejected for at least the same reasons as given in the rejection of claim 3.
Response to Arguments
Applicant's arguments filed 9-10-2024 (“Remarks”) have been fully considered but they are not persuasive.
35 U.S.C. § 101:
Remarks, pg. 8. Applicant argues with respect to claim 1 that the claim is not directed to an abstract idea and does not recite any mental processes that can be practically performed in the human mind. Applicant further argues this by citing paragraphs [0017], [0018], [0022], [0030], [0033], and [0039] of the instant specification. Examiner respectfully disagrees. Claim 1 as drafted, as a whole, is directed to calculating a similarity score by using a machine learning model to make a comparison between data. Thus, this is directed to the abstract idea of determining similarity by comparing data and assigning a score (e.g. human observation, evaluation). Furthermore, claim 1 does not recite the steps listed by Applicant such as: synthesizing software programs [0017], synthesis of programs [0018], encoding programs and natural language text [0022], thousands to millions of pairs of programs [0039]. For these reasons, claim 1 remains rejected under 35 U.S.C. § 101.
Remarks, pg. 9. Applicant argues with respect to claim 1 that the training of a machine learning model includes using a processor to access computer memory and as such, cannot be practically performed by the human mind. In particular, Applicant analogizes instant claim 1 to claim 2 of Example 37 of the USPTO Subject Matter Eligibility Examples. Examiner respectfully disagrees with Applicant’s analysis. Firstly, the machine learning model recited in instant claim 1 is recited at a high level of generality. The model is trained using data and generates an output similarity score. As discussed above, the similarity score is practically performable within the human. The high level recitation of the machine learning training is therefore analyzed as a mere instruction to apply the abstract idea. For these reasons, instant claim 1 is not analogous to claim 2 of Example 37, and remains rejected under 35 U.S.C. § 101.
Remarks pg. 9-10. Applicant argues with respect to claim 1 that the claim improves machine learning-based generation of software programs. Examiner respectfully disagrees. Claim 1 does not recite any sort of generating software programs or synthesizing of software programs. Claim 1, as drafted, compares programs using a machine learning model and outputs a similarity score. For these reasons, claim 1 does not recite an improvement to machine-learning based generation of software programs, and remains rejected under 35 U.S.C. § 101.
Remarks, pg. 10-11. Applicant argues with respect to claim 1 that the claim amounts to significantly more than the abstract idea by presenting a technical improvement in the field of machine learning model-based evaluation and synthesis of software programs. As discussed above with respect to pg. 9-10, the claim does recite any synthesis of software programs or generation of programs that more closely match specifications associated with the natural language text. The claim, as drafted, compares programs using a machine learning model and outputs a similarity score. For these reasons, the claim does not amount to significantly more than the abstract idea, and remains rejected under 35 U.S.C. § 101.
35 U.S.C. § 103:
Remarks, pg. 12-14. Applicant’s arguments with respect to claims 1, 9, and 21 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KAMRAN AFSHAR whose telephone number is 571-272-7796. The examiner can normally be reached Monday-Thursday: 9:00AM-4:00PM ET.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, DAVID WILEY can be reached at (571) 272-4150.
The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/KAMRAN AFSHAR/Supervisory Patent Examiner, Art Unit 2125