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 office action is in response to the amendment filed on 7/14/2026. Claims 1, 3-5,7- 10, 12 and 13 are pending. Claims 2,6 and 11 are cancelled.
Response to Arguments
Applicant's arguments filed 07/14/2026 with respect to 35 U.S.C. 112(b) have been fully considered and are persuasive. The amended claims overcome the rejections by clarifying the commit data and change data references, and therefore the rejections under 35 U.S.C. 112(b) have been withdrawn.
Applicant's arguments filed 07/17/2026 with respect to 35 U.S.C. 103 have been fully considered and are persuasive. The applicant’s amended claims are recited such that the combination of references originally outlined may not clearly render the claims obvious, and therefore the rejections under 35 U.S.C. 103 have been withdrawn.
Applicant's arguments filed 07/17/2026 with respect to 35 U.S.C. 101 have been fully considered but they are not persuasive. Applicant argued ” when the labeled data is embedded reflecting the hierarchical structure of the source code, it can reduce code inspection efforts (see [84] of the present application). In other words, when the data is embedded, the hierarchical structure of the source code is incorporated therein, and therefore, the number of calculations or processing of the code inspection can be reduced. Accordingly, this technical feature can lead to lowering CPU overhead and reducing memory consumption. Further, this feature can enable the defect inspection to run faster or to scale to larger codebase that were previously too computationally expensive to process. These technical features improving the functioning of the computer demonstrate that claim 1 is directed to patent eligible subject matter.” And “ the claimed method combines the learned commit data and the learned code change data into one during the evaluation step, and thus, the classification can be performed by classification learning using the combined data. According to the present application, the concatenation of the learned commit data and the learned code change data significantly reduces the code inspection efforts (see [85] of the present application). In other words, by combining the learned commit data and the learned code change data into one, the number of learning of classification during the classification learning step can be reduced because it can be performed by the classification learning using the combined data, rather than using both of the commit data and the code change data. The combination of the two different types of data (the learned commit data and the learned code change data) can effectively reduce the number of learnings for classification, and thus, the CPU resource can be saved and the memory consumption can be reduced.”
Examiner respectfully disagrees. The claims as amended recite mental processes including learning , determination and embedding steps that can reasonably be carried out in the human mind.
The claims do not include additional elements that integrate into practical application or are sufficient to amount to significantly more than the judicial exception. The above elements recited by the applicant are well known and common development steps that are not specifically directed to the improvement of the computing device but rather the practice of the abstract idea. See 35 U.S.C. 101 rejections below for a detailed analysis
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, 3-5, 7-10, and 12-13 are rejected under 35 U.S.C. 101 because the claimed invention recites a judicial exception, is directed to that judicial exception, an abstract idea, it has not been integrated into practical application and the claims further do not recite significantly more than the judicial exception. Examiner has evaluated the claims under the framework provided in the 2019 Patent Eligibility Guidance published in the Federal Register 01/07/2019 and has provided such analysis below.
Claims 1, 3-5, 7-10, and 12-13 are rejected under 35 U.S.C. 101 because the claimed invention recites a judicial exception, is directed to that judicial exception, an abstract idea, it has not been integrated into practical application and the claims further do not recite significantly more than the judicial exception. Examiner has evaluated the claims under the framework provided in the 2019 Patent Eligibility Guidance published in the Federal Register 01/07/2019 and has provided such analysis below.
Regarding claim 1, the limitations,
“a data labeling step of labeling data with a possibility of generating a defect by using an identification algorithm for the collected data;”
“a learning step of learning context and meaning of the data embedded in the embedding step based on deep learning;”
“an evaluation step of evaluating a learning result based on the context and meaning of the data learned in the learning step”
“wherein, in the data labeling step, the collected data includes commit data and code change data, such that the commit data and the code change data are learned during the learning step,”
“wherein the evaluation step includes: a step of generating learning data represented by combining the learned commit data and the learned code change data into one;”
“a classification learning step of learning of classification by using the learning data;”
as drafted, are functions that, under their broadest reasonable interpretation, recite the abstract idea of a mental process. These limitations encompass a human mind carrying out these functions through observation, evaluation judgment and /or opinion, or even with the aid of pen and paper. For example , the “labeling” limitation can be performed by a user looking at data and marking the data based on determinations, such as a predefined list of steps that the user makes in their determination. The “learning“ limitation can be carried out by a user looking at data and making judgements based on the contents of the data. Similarly the “evaluation” limitation can be carried out by a user recording information on a sheet of paper based on their learning/determinations. Thus, these limitations recite and fall within the “Mental Processes” grouping of abstract ideas under Prong 1.
The limitation, “an embedding step of receiving the labeled data and embedding the labeled data;”, “wherein, in the embedding step, the embedding is performed by considering context and semantics, a hierarchical structure and semantic information of a source code, and a relationship between a commit message and a code change [] based on the commit data and the code change data,” and “a classification learning evaluation step of evaluating the learning of the classification by using a loss function.“ As drafted is a function that under its broadest reasonable interpretation, recites the abstract idea of a mathematical concept . The limitation includes organizing information and manipulating information through mathematical correlations. For example, a user can look at data and form an interpretation of the data by following a predefined set of transformational embedding instructions, recording their embedding on a sheet of paper. Thus, the limitation recites and falls within the “Mathematical Concept” grouping of abstract ideas under Prong 1.
Under Prong 2, the judicial exception is not integrated into a practical application. The additional elements, “a data collection step of collecting data on software;”, do nothing more than add insignificant extra solution activity to the judicial exception of merely gathering and outputting data. Accordingly, the additional elements do not integrate the recited judicial exception into a practical application and the claim is therefore directed to the judicial exception. See MPEP 2106.05 (g).
Claim 1 recites further additional element “using a pre-trained embedding model”. These additional elements are recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using generic computer, and/or generic computer components. See MPEP 2106.05(f). Therefore, the additional elements recited in claim 1 does not integrate the judicial exception into a practical application under prong 2, nor amount to significantly more under step 2B.
Regarding claim 3, the limitations, “wherein in the data labeling step, the identification algorithm is configured for automatically identifying defect-causing change data”, recites additional mental processes under Prong 1. This limitation encompasses a human mind carrying out these functions through observation, evaluation judgment and /or opinion, or even with the aid of pen and paper. For example, the above limitations can be carried out by a user in a similar method to those outlined in the above rejection of claim 1.
Regarding claim 4, the limitations,
“a step of searching for a keyword of the defect-causing change data and identifying a commit corresponding to the keyword;”
“ a step of identifying changed code lines of a previous version and a modified version in the commit corresponding to the keyword;”
“a step of generating a change by performing at least one of modification and deletion of a code line in a previous modification for a last commit of commits corresponding to the identified code lines; and”
as drafted, are functions that, under their broadest reasonable interpretation, recite the abstract idea of a mental process. These limitations encompass a human mind carrying out these functions through observation, evaluation judgment and /or opinion, or even with the aid of pen and paper. For example, the above limitations can be carried out by a user in a similar method to those outlined in the above rejection of claim 1. Thus, these limitations recite and fall within the “Mental Processes” grouping of abstract ideas under Prong 1.
The additional elements, “a step of labeling the commit data subject to the change as defective, and the commit data not subject to the change as defect-free.”, are analyzed under Prong 2 as mere data gathering and outputting which does not integrate the judicial exception into a practical application, nor amount to significantly more under Step 2B for similar reasons as those provided in the rejection of claim 1.
Regarding claim 5, the limitations, “wherein the identification algorithm includes an SZZ algorithm.”, are analyzed under Prong 2 as field of use and technical environment as limiting the abstract idea to a particular algorithm does not apply any meaningful limits on the claim, does not integrate the judicial exception into a practical application, nor amount to significantly more under Step 2B . See MPEP 21.06.05(h).
Regarding claim 7, the limitations, “wherein the embedding model includes a UniXCoder model.” , are analyzed under Prong 2 as field of use and technical environment as limiting the abstract idea to a particular model does not apply any meaningful limits on the claim, does not integrate the judicial exception into a practical application, nor amount to significantly more under Step 2B . See MPEP 21.06.05(h).
Regarding claim 8, the limitations, “a preprocessing step of preprocessing for tokenization on the commit data and the code change data before the embedding step.”, can be classified as insignificant extra-solution activity in the form of pre-solution activity by manipulating the data prior to the practicing of the abstract idea. The additional element amounts to no more that insignificant extra-solution activity in the form of pre-solution activity as tokenizing the data prior to embedding does not add a meaningful limitation to abstract idea nor does the limitation alone or in combination with the abstract idea amount to significantly more than the identified judicial exception. Accordingly, the claim is not patent eligible under 35 USC 101.
Regarding claim 9, the limitations, “wherein in the learning step, the context and meaning of the embedded data are learned based on the deep learning … capable of learning a relationship between previous data and subsequent data for the embedded data.”, recites additional mental processes under Prong 1. This limitation encompasses a human mind carrying out these functions through observation, evaluation judgment and /or opinion, or even with the aid of pen and paper. For example, the above limitations can be carried out by a user in a similar method to those outlined in the above rejection of claim 1. The additional elements, “by using a two-way learning model” , are analyzed under Prong 2 as field of use and technical environment as limiting the abstract idea to a particular model does not apply any meaningful limits on the claim, does not integrate the judicial exception into a practical application, nor amount to significantly more under Step 2B . See MPEP 21.06.05(h).
Regarding claim 10, the limitations, “wherein the two-way learning model includes a Bi-LSTM model.” , are analyzed under Prong 2 as field of use and technical environment as limiting the abstract idea to a particular model does not apply any meaningful limits on the claim, does not integrate the judicial exception into a practical application, nor amount to significantly more under Step 2B . See MPEP 21.06.05(h).
Regarding claim 12, the limitations, “ further comprising: a step of outputting final data based on the evaluation step.” , are analyzed under Prong 2 as mere data gathering and outputting which does not integrate the judicial exception into a practical application, nor amount to significantly more under Step 2B for similar reasons as those provided in the rejection of claim 1.
Regarding claim 13, the limitations, “wherein the software includes an edge computing application.”, are analyzed under Prong 2 as field of use and technical environment as limiting the abstract idea to a particular application type does not apply any meaningful limits on the claim, does not integrate the judicial exception into a practical application, nor amount to significantly more under Step 2B . See MPEP 21.06.05(h).
Allowable Subject Matter
Claims 1, 3-5, 7-10, and 12-13 would be allowable if rewritten or amended to overcome the rejection(s) under 35 U.S.C. 101 as directing to an abstract idea rejection, set forth in this Office action.
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.Any inquiry concerning this communication or earlier communications from the examiner should be directed to LAWRENCE O'CONNOR EMANUEL whose telephone number is (571)272-8975. The examiner can normally be reached M-F 7:30 - 5:00 pm ( Alternate Fridays off).
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/L.S.O./Examiner, Art Unit 2193
/Chat C Do/Supervisory Patent Examiner, Art Unit 2193
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