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
This final office action is a response to the applicant amendment and remarks filed August 14th, 2026.
Claims 1-20 are pending.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 103as being unpatentable over Alpert et al. US 2017/0161407 A1 (“Alpert”) in view of Oh et al. US 2023/0177377 A1 (“Oh”).
As to claim 1, Alpert discloses a method for predicting failure in a circuit design caused by noise impact, the method comprising:
receiving, for a net representing the circuit design and including at least one of a source or a sink gate, data for a specified feature set (Alpert Paragraphs 54-55 – e.g., analysis of nets according to various criteria);
predicting, by using a machine learning model, a failure related to noise impact including induced switching of the net based on the data for the specified feature set and using noise tolerance information, wherein the data for the specified feature set is input to the machine learning model (Alpert Paragraphs 54-55 – e.g., timing and/or delay analysis, including taking noise into account, in view of Oh, see below); and
upon receiving the prediction, modifying the net using the predicted failure information (Alpert Paragraphs 58-59 – e.g., identifying timing violations and optimizing or modifying the design).
Alpert teaches many of the elements of claim 1, including timing and delay analysis while accounting for noise. Alpert does not explicitly disclose the use of a machine learning model. However, the missing element is well known in the art because while teaching error mitigation in a circuit, Oh discloses using a neural network learning model in order to mitigate errors (Of Paragraphs 58 or 65 or Claim 6). It would have been obvious to one having ordinary skill in the art at the time the invention was made to use machine learning models for circuit analysis because doing so would allow the designer to more easily evaluate the design and prevent possible errors. The examiner notes that evaluating a circuit design with a machine learning model necessarily involves inputting data associated with the design as an input into the machine learning model.
As to claim 2, Alpert and Oh disclose the method of claim 1. Alpert further discloses after modifying the net using the predicted failure information, re-predicting a failure related to noise impact including induced switching of the net based on updated data for the specified feature set and using noise tolerance information; upon receiving the updated prediction, modifying the net using the updated predicted failure information (Alpert Figure 5 or Paragraphs 58-59 – e.g., iteration of optimization and retiming/analysis).
As to claim 3, Alpert and Oh disclose the method of claim 1. Alpert further discloses wherein modifying the net using the predicted failure information comprises: inserting a buffer (Alpert Paragraphs 58-60 – e.g., “buffer optimization”).
As to claim 4, Alpert and Oh disclose the method of claim 1. Alpert further discloses wherein the noise tolerance information comprises sink gate noise tolerance information (Alpert Paragraphs 54-58 – e.g., necessary in analysis of timing violations).
As to claim 5, Alpert and Oh disclose the method of claim 1. Alpert further discloses wherein the prediction is a pass/fail prediction (Alpert Paragraphs 54-58 – e.g., analysis of timing violations).
As to claim 6, Alpert and Oh disclose the method of claim 1. Alpert further discloses wherein the prediction is an amount of noise slack (Alpert Paragraphs 58-60 – e.g., analysis and optimization of “slack improvement of the affected endpoint”).
Claims 7-18 recite elements similar to claims 1-6, and are rejected for the same reasons.
As to claim 19, Alpert and Oh disclose the method of claim 13. Alpert further discloses wherein the computer readable medium comprises a storage medium (Alpert Figures 1-2 or Paragraphs 82-83).
As to claim 20, Alpert and Oh disclose the method of claim 13. Alpert further discloses wherein the specified feature set comprises wire length and sink gate noise tolerance information. Alpert mentions that both noise tolerance (Alpert Paragraphs 54-58 – e.g., noise tolerance information necessary in analysis of timing violations) and wirelength (Alpert Paragraphs 18, 44-47, or 80) are considerations in determining timing violations. It would have been obvious to one having ordinary skill in the art at the time the invention was made to take those factors into account while predicting failures.
Response to Amendment and Arguments
Applicant’s amendment and remarks filed 8/14/26 have been considered. After consideration of the amendment and arguments, the examiner has found that the prior art Alpert alone does not disclose the elements of the amended claims. However, after additional search and consideration new rejections with the additional prior art Oh have been made above. A new rejection of new claim 20 has also been added.
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.
/BRYCE M AISAKA/ Primary Examiner, Art Unit 2851
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