Prosecution Insights
Last updated: April 19, 2026
Application No. 18/165,292

METHOD OF EXECUTING DESIGN FLOW WITH MACHINE LEARNING TECHNIQUES

Non-Final OA §102
Filed
Feb 06, 2023
Examiner
NGUYEN, NHA T
Art Unit
2851
Tech Center
2800 — Semiconductors & Electrical Systems
Assignee
Taiwan Semiconductor Manufacturing Company Ltd.
OA Round
1 (Non-Final)
87%
Grant Probability
Favorable
1-2
OA Rounds
2y 7m
To Grant
99%
With Interview

Examiner Intelligence

Grants 87% — above average
87%
Career Allow Rate
915 granted / 1052 resolved
+19.0% vs TC avg
Strong +19% interview lift
Without
With
+18.7%
Interview Lift
resolved cases with interview
Typical timeline
2y 7m
Avg Prosecution
22 currently pending
Career history
1074
Total Applications
across all art units

Statute-Specific Performance

§101
12.9%
-27.1% vs TC avg
§103
28.1%
-11.9% vs TC avg
§102
36.9%
-3.1% vs TC avg
§112
13.2%
-26.8% vs TC avg
Black line = Tech Center average estimate • Based on career data from 1052 resolved cases

Office Action

§102
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 . DETAILED ACTION 2. This Office Action responds to the Application filed on 2/6/2023 and IDS filed on 5/28/2024. Claims 1-20 are pending. Claim Rejections - 35 USC § 102 3. The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – (a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention. 4. Claim(s) 1-20 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Najibi et al. (U.S. Pub. No. 12,417,336 B1). As per claim 1, Najibi discloses: A method comprising: constructing a set of reference design contents associated with a set of reference design recipes (See Col 44 to Col 6; Line 35, i.e. learning from data previously collected from IC designer’s modification session…every permutton setting…software setting…design settings, See Col 7; Line 16 to Col 8 ; Line 58, i.e. different relevance setting … previous circuit design … high relevance , See Col 8; Line 59 to Col 10; Line 10, See Col 13; Line 1-25, i.e. previous circuit design…setting related to a simulation –[prior art include previous circuit design considered as the reference design and setting of the previous circuit design considered as the recipe]) determining a content similarity between a user design content and a reference design content taken from the set of reference design contents (See Col 7; Line 16-42, i.e. how similar a prior design session compared to the current design session, See Col 13; Lines 1-25, i.e. identify similarities between the current circuit design and the one or more previous circuit designs); and executing a design flow specified by a reference design recipe associated with the reference design content, as a result of the content similarity reaching a predetermined threshold (See Col 13; Lines 1-25, i.e. apply values obtained from the simulation data…setting related to a simulation, See Col 7; Line 16 to Col 8 ; Line 58, i.e. if there is high relevance 112, a very similar previous circuit design was found and the system can use the same permuton settings, See Col 8; Line 59 to Col 10; Line 10 –[prior art use settings from previous design for current design, considered as the design flow specified by the reference design recipe as cited above]). As per claim 2, Najibi discloses all of the features of claim 1 as discloses above wherein Najibi also discloses wherein each reference design content is associated with a reference design recipe in the set of reference design recipes (See Col 44 to Col 6; Line 35, i.e. learning from data previously collected from IC designer’s modification session…every permutton setting…software setting…design settings, See Col 7; Line 16 to Col 8 ; Line 58, i.e. different relevance setting … previous circuit design … high relevance , See Col 8; Line 59 to Col 10; Line 10, See Col 13; Line 1-25, i.e. previous circuit design…setting related to a simulation). As per claim 3, Najibi discloses all of the features of claim 1 as discloses above wherein Najibi also discloses wherein constructing the set of reference design contents comprises: constructing the reference design content from content parameters that include one or more design recipe parameters in the reference design recipe (See Col 44 to Col 6; Line 35, i.e. learning from data previously collected from IC designer’s modification session…every permutton setting…software setting…design settings, See Col 7; Line 16 to Col 8 ; Line 58, i.e. different relevance setting … previous circuit design … high relevance , See Col 8; Line 59 to Col 10; Line 10, See Col 13; Line 1-25, i.e. previous circuit design…setting related to a simulation). As per claim 4, Najibi discloses all of the features of claim 1 as discloses above wherein Najibi also discloses constructing the user design content from content parameters that include one or more design recipe parameters in a user design recipe (See Col 13; Lines 1-25, i.e. apply values obtained from the simulation data…setting related to a simulation, See Col 7; Line 16 to Col 8 ; Line 58, i.e. if there is high relevance 112, a very similar previous circuit design was found and the system can use the same permuton settings, See Col 8; Line 59 to Col 10; Line 10). As per claim 5, Najibi discloses all of the features of claim 1 as discloses above wherein Najibi also discloses wherein constructing the set of reference design contents comprises: constructing the reference design content from a reference design flow based on one or more content parameters which specify a technology targeted by the reference design flow (See Col 6; Line 1-35, i.e. library cell choices…IC size, IC aspect ratio, See Col 14; Lines 23-35, i.e. optimized for a target semiconductor manufacturing technology). As per claim 6, Najibi discloses all of the features of claim 1 as discloses above wherein Najibi also discloses wherein constructing the set of reference design contents comprises: constructing the user design content from a user design flow based on one or more content parameters which specify a technology targeted by the user design flow (See Col 6; Line 1-35, i.e. library cell choices…IC size, IC aspect ratio, See Col 14; Lines 23-35, i.e. optimized for a target semiconductor manufacturing technology). As per claim 7, Najibi discloses all of the features of claim 1 as discloses above wherein Najibi also discloses fetching the reference design content from a database (See Col 44 to Col 6; Line 35, i.e. learning from data previously collected from IC designer’s modification session…every permutton setting…software setting…design settings, See Col 7; Line 16 to Col 8 ; Line 58, i.e. different relevance setting … previous circuit design … high relevance , See Col 8; Line 59 to Col 10; Line 10, See Col 13; Line 1-25, i.e. previous circuit design…setting related to a simulation, See Col 1; Line 45-67, i.e. searching a database for data associated with previous design sessions). As per claim 8, Najibi discloses all of the features of claim 1 as discloses above wherein Najibi also discloses wherein executing the design flow comprises: optimizing the design flow while carrying out a machine learning session (See Col 13; Lines 1-25, i.e. apply values obtained from the simulation data…setting related to a simulation, See Col 7; Line 16 to Col 8 ; Line 58, i.e. if there is high relevance 112, a very similar previous circuit design was found and the system can use the same permuton settings, See Col 8; Line 59 to Col 10; Line 10, See Abstract, i.e. using machine learning to modify a current circuit design is provided). As per claim 9, Najibi discloses all of the features of claim 1 as discloses above wherein Najibi also discloses wherein executing the design flow comprises: executing the design flow based on a reference machine learning model associated with the reference design content (See Col 6; Lines 1-35, i.e. multiple machine learning strategies including incrementally searching entire search spaces…implemented learning strategies can be changed or adjusted based on how similar a prior search is with respect to a current design). As per claim 10, Najibi discloses all of the features of claim 9 as discloses above wherein Najibi also discloses fetching the reference design content and the reference machine learning model from a database (See Col 44 to Col 6; Line 35, i.e. learning from data previously collected from IC designer’s modification session…every permutton setting…software setting…design settings, See Col 7; Line 16 to Col 8 ; Line 58, i.e. different relevance setting … previous circuit design … high relevance , See Col 8; Line 59 to Col 10; Line 10, See Col 13; Line 1-25, i.e. previous circuit design…setting related to a simulation, See Col 1; Line 45-67, i.e. searching a database for data associated with previous design sessions). As per claim 11, Najibi discloses: A non-transitory machine-readable medium having instructions stored thereon, instructions being configured to cause a system having at least one processor to execute (See Figure 7, i.e. static memory and processing device): constructing a set of reference design contents associated with a set of reference design recipes (See Col 44 to Col 6; Line 35, i.e. learning from data previously collected from IC designer’s modification session…every permutton setting…software setting…design settings, See Col 7; Line 16 to Col 8 ; Line 58, i.e. different relevance setting … previous circuit design … high relevance , See Col 8; Line 59 to Col 10; Line 10, See Col 13; Line 1-25, i.e. previous circuit design…setting related to a simulation –[prior art include previous circuit design considered as the reference design and setting of the previous circuit design considered as the recipe]); determining a content similarity between a user design content and a reference design content taken from the set of reference design contents (See Col 7; Line 16-42, i.e. how similar a prior design session compared to the current design session, See Col 13; Lines 1-25, i.e. identify similarities between the current circuit design and the one or more previous circuit designs); and executing a design flow specified by a reference design recipe associated with the reference design content, as a result of the content similarity reaching a predetermined threshold (See Col 13; Lines 1-25, i.e. apply values obtained from the simulation data…setting related to a simulation, See Col 7; Line 16 to Col 8 ; Line 58, i.e. if there is high relevance 112, a very similar previous circuit design was found and the system can use the same permuton settings, See Col 8; Line 59 to Col 10; Line 10 –[prior art use settings from previous design for current design, considered as the design flow specified by the reference design recipe as cited above]). As per claim 12, Najibi discloses all of the features of claim 11 as discloses above wherein Najibi also discloses wherein each reference design content is associated with a reference design recipe in the set of reference design recipes (See Col 44 to Col 6; Line 35, i.e. learning from data previously collected from IC designer’s modification session…every permutton setting…software setting…design settings, See Col 7; Line 16 to Col 8 ; Line 58, i.e. different relevance setting … previous circuit design … high relevance , See Col 8; Line 59 to Col 10; Line 10, See Col 13; Line 1-25, i.e. previous circuit design…setting related to a simulation). As per claim 13, Najibi discloses all of the features of claim 11 as discloses above wherein Najibi also discloses wherein constructing the set of reference design contents comprises: constructing the reference design content from content parameters that include one or more design recipe parameters in the reference design recipe (See Col 44 to Col 6; Line 35, i.e. learning from data previously collected from IC designer’s modification session…every permutton setting…software setting…design settings, See Col 7; Line 16 to Col 8 ; Line 58, i.e. different relevance setting … previous circuit design … high relevance , See Col 8; Line 59 to Col 10; Line 10, See Col 13; Line 1-25, i.e. previous circuit design…setting related to a simulation). As per claim 14, Najibi discloses all of the features of claim 11 as discloses above wherein Najibi also discloses wherein the instructions is configured to cause the system further to execute: constructing the user design content from content parameters that include one or more design recipe parameters in a user design recipe (See Col 13; Lines 1-25, i.e. apply values obtained from the simulation data…setting related to a simulation, See Col 7; Line 16 to Col 8 ; Line 58, i.e. if there is high relevance 112, a very similar previous circuit design was found and the system can use the same permuton settings, See Col 8; Line 59 to Col 10; Line 10). As per claim 15, Najibi discloses all of the features of claim 11 as discloses above wherein Najibi also discloses wherein constructing the set of reference design contents comprises: constructing the reference design content from a reference design flow based on one or more content parameters which specify a technology targeted by the reference design flow (See Col 6; Line 1-35, i.e. library cell choices…IC size, IC aspect ratio, See Col 14; Lines 23-35, i.e. optimized for a target semiconductor manufacturing technology). As per claim 16, Najibi discloses all of the features of claim 11 as discloses above wherein Najibi also discloses wherein constructing the set of reference design contents comprises: constructing the user design content from a user design flow based on one or more content parameters which specify a technology targeted by the user design flow (See Col 6; Line 1-35, i.e. library cell choices…IC size, IC aspect ratio, See Col 14; Lines 23-35, i.e. optimized for a target semiconductor manufacturing technology). As per claim 17, Najibi discloses all of the features of claim 11 as discloses above wherein Najibi also discloses wherein the instructions is configured to cause the system further to execute: fetching the reference design content from a database (See Col 44 to Col 6; Line 35, i.e. learning from data previously collected from IC designer’s modification session…every permutton setting…software setting…design settings, See Col 7; Line 16 to Col 8 ; Line 58, i.e. different relevance setting … previous circuit design … high relevance , See Col 8; Line 59 to Col 10; Line 10, See Col 13; Line 1-25, i.e. previous circuit design…setting related to a simulation, See Col 1; Line 45-67, i.e. searching a database for data associated with previous design sessions). As per claim 18, Najibi discloses all of the features of claim 11 as discloses above wherein Najibi also discloses wherein executing the design flow comprises: optimizing the design flow while carrying out a machine learning session (See Col 13; Lines 1-25, i.e. apply values obtained from the simulation data…setting related to a simulation, See Col 7; Line 16 to Col 8 ; Line 58, i.e. if there is high relevance 112, a very similar previous circuit design was found and the system can use the same permuton settings, See Col 8; Line 59 to Col 10; Line 10, See Abstract, i.e. using machine learning to modify a current circuit design is provided). As per claim 19, Najibi discloses all of the features of claim 11 as discloses above wherein Najibi also discloses wherein executing the design flow comprises: executing the design flow based on a reference machine learning model associated with the reference design content (See Col 6; Lines 1-35, i.e. multiple machine learning strategies including incrementally searching entire search spaces…implemented learning strategies can be changed or adjusted based on how similar a prior search is with respect to a current design). As per claim 20, Najibi discloses: A system for manufacturing a semiconductor device, the system comprising: at least one processor; at least one non-transitory computer readable medium that stores computer executable code; and the at least one non-transitory computer readable medium, the computer executable code and the at least one processor being configured to cause the system (See Figure 7, i.e. static memory and processing device) to: construct a set of reference design contents associated with a set of reference design recipes (See Col 44 to Col 6; Line 35, i.e. learning from data previously collected from IC designer’s modification session…every permutton setting…software setting…design settings, See Col 7; Line 16 to Col 8 ; Line 58, i.e. different relevance setting … previous circuit design … high relevance , See Col 8; Line 59 to Col 10; Line 10, See Col 13; Line 1-25, i.e. previous circuit design…setting related to a simulation –[prior art include previous circuit design considered as the reference design and setting of the previous circuit design considered as the recipe]), determine a content similarity between a user design content and a reference design content taken from the set of reference design contents (See Col 7; Line 16-42, i.e. how similar a prior design session compared to the current design session, See Col 13; Lines 1-25, i.e. identify similarities between the current circuit design and the one or more previous circuit designs), and execute a design flow specified by a reference design recipe associated with the reference design content, as a result of the content similarity reaching a predetermined threshold (See Col 13; Lines 1-25, i.e. apply values obtained from the simulation data…setting related to a simulation, See Col 7; Line 16 to Col 8 ; Line 58, i.e. if there is high relevance 112, a very similar previous circuit design was found and the system can use the same permuton settings, See Col 8; Line 59 to Col 10; Line 10 –[prior art use settings from previous design for current design, considered as the design flow specified by the reference design recipe as cited above]). Conclusion 5. Any inquiry concerning this communication or earlier communications from the examiner should be directed to NHA T NGUYEN whose telephone number is (571)270-1405. The examiner can normally be reached M-F 8:00AM-5:00PM. 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, Jack Chiang can be reached at 571-272-7483. 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. /NHA T NGUYEN/Primary Examiner, Art Unit 2851
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Prosecution Timeline

Feb 06, 2023
Application Filed
Feb 19, 2026
Non-Final Rejection — §102 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

1-2
Expected OA Rounds
87%
Grant Probability
99%
With Interview (+18.7%)
2y 7m
Median Time to Grant
Low
PTA Risk
Based on 1052 resolved cases by this examiner. Grant probability derived from career allow rate.

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