DETAILED ACTION
This office action is responsive to amendment filed on July 6, 2026 in this application Sethia et al., U.S. Patent Application No. 18/630,434 (Filed April 9, 2024) (“Sethia”). Claims 1 – 20 were pending. Claims 1, 8, and 15 are amended. Claims 1 – 20 are pending.
Applicants' arguments have been carefully and respectfully considered and found not persuasive. Accordingly, this action has been made FINAL.
Response to Arguments
1. With respect to Applicant’s argument on pgs. 8 – 12 of the Applicant’s Remarks (“Remarks”) that there is no motivation to combine Warfield and Kommineni, examiner respectfully disagrees. See infra § Claim Rejections - 35 USC §103, § Claim 1.
Applicant argues the combination would change the principle of operation of Warfield, render it inoperable, and that “there is no hint in either Warfiled or Kommineni” that their methods could be combined.
As an initial matter, it is noted that the section directed to motivation to combine found on pages 8 – 10 of the Remarks appears to have several internal inconsistencies including a citation to a quote which appears to be presented as from In re Ratti, 270 F.2d 810,813, 123 USPQ 349, 352 (CCPA 1959). Ratti is cited in MPEP 2143.01(VI) and is a decision on changes to the method of operation of “an oil seal comprising a bore engaging portion.” However, in the Remarks at pg. 10 the following alleged quote from Ratti appears:
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The parenthetical appears to contain a quote from Ratti, however the italicized text Warfield which appears in the quote does not come from Ratti. Rather Ratti states: “This suggested combination of references would require a substantial reconstruction and redesign of the elements shown in Chinnery et al. as well as a change in the basic principles under which the Chinnery et al. construction was designed to operate.” It is unclear how Applicant intends to support their argument of a change to the principle of operation of Warfield based on this alleged parenthetical citation to Ratti.
In light of the argument topics listed by Applicant in their Remarks directed to the art combination, it is noted that Kommineni is being relied upon for a teaching of using a secondary fitness criteria such as selecting a minimum number of test cases and that this aspect of Kommineni, rather than every disclosure in Kommineni, would neither change the operation of Warfield nor render it inoperable if used in combination with the methods of Warfield. In addition, and in contrast to the assertions presented in the Remarks, both Warfield and Kommineni teach that it is desirable to try and obtain a minimized number of test cases. See Kommineni at ¶ 0002 and Warfield at col. 10 ll. 39 - 44.
Therefore, there is a motivation to combine Warfield and Kommineni.
2. With respect to Applicant’s argument on pgs. 12 – 14 of the Remarks stating that Warfield fails to teach a fitness score for each test case and instead allegedly teaches a fitness score for each test script, examiner respectfully disagrees. See infra § Claim Rejections - 35 USC §103, § Claim 1.
Applicant argues that “[a]t no point does Warfield describe…a fitness score for an individual test case.” However, Warfield does describe that each test script may consist of one test case. Id. at col. 3 ll. 66. Thus, the fitness scores assigned to each test script are fitness scores for each test case within the test script. Therefore, Warfield teaches a fitness score for each test case.
Please note that the second quote below from Warfiled that appears in the Remarks on pg. 13 and which has a citation of “Id., col. 8, lines 45 – 50” appears to instead be found in Warfield at col. 9 lines 60 – 62.
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3. With respect to Applicant’s argument on pgs. 14 – 15 of the Remarks stating that the prior art references fail to teach the newly added limitations, examiner respectfully disagrees. See infra § Claim Rejections - 35 USC §103, § Claim 1. Warfield teaches building test cases to perform requirements testing in order to test the required application functionality embodied in state machines. Warfield at col. 5 ll. 41 – 57 (state machines defining application functionality testing requirements); see also Kommineni at ¶¶ 0016 & 0017 (test cases satisfy requirement specification). Therefore, the current prior art teaches the newly added limitations.
Claim Rejections 35 U.S.C. §103
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 of this title, 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.
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.
Claims 1, 3 – 8, 10 – 15, and 17 - 20 are rejected under 35 U.S.C. 103 as being unpatentable over Warfield, United States Patent No. 5,754,760 (Patented May 19, 1998, filed May 30, 1996) (“Warfield”) in view of Kommineni et al., United States Patent Application Publication No. 2015/0261657 (Published September 17, 2015, filed February 12, 2015) (“Kommineni”).
Claims 1, 8, and 15
With respect to claims 1, 8, and 15, Warfield teaches the invention as claimed including a system, comprising:
a memory configured to store a total population of test cases, a selected population of test cases, a first set of fitness criteria, and a second set of fitness criteria, wherein the selected population of test cases is configured to test a functionality of one or more of a first instance of a software application or a second instance of the software application, and wherein the selected population of test cases comprises a subset of the total population of test cases; and one or more processors operably coupled to the memory and configured to: access the selected population of test cases and the first set of fitness criteria; determine, based on the selected population of test cases and the first set of fitness criteria, a fitness score for each test case of the selected population of test cases, wherein the first set of fitness criteria comprises a requirement coverage and a functionality of one or more of the first instance of the software application or the second instance of the software application to be tested; iteratively execute a natural computing algorithm to identify one or more best possible test cases based at least in part on the fitness score for each test case of the selected population of test cases;… and execute, based at least in part on the output, the identified one or more best possible test cases to test the functionality of the one or more of the first instance of the software application or the second instance of the software application. {Test cases for a software application are provided to a genetic algorithm which iteratively (repeatedly) creates new generations of tests cases to perform requirements testing to test application functionality embodied in state machines by selecting a subset of each previous generation based on a plurality of different types of fitness score data stored for each test, uses crossover points between prior tests and/or mutates values for the prior tests to generate the next generation of tests until a generation of test cases produces the “best” test cases based on the fitness criteria at which point the application may be tested using such scripts that were generated by the genetic algorithm. Warfield at Abstract; id. at col. 3 ll. 44 – 66, id. at col. 4 ll. 5 – 35; id. at col. 5 ll. 15 – 18; id. at col. 8 ll. 13 – 62; id. at col.10 ll. 16 – 38; id. at Claim 32 & fig. 1 (program storage device of computer 10 includes memory 12 and mass storage 19 for generating and storing the plurality of test scripts and fitness scores); id. at col. 5 ll. 41 – 57 (state machines defining requirements).}
However, Warfield doesn’t explicitly teach the limitation:
in response to determining that the identified one or more best possible test cases satisfies the second set of fitness criteria, generate an output comprising the identified one or more best possible test cases; {Kommineni does teach this limitation. Kommineni teaches that using a genetic algorithm to select the best test cases for requirements testing an application, as taught in Warfield, may include selecting test cases for a software application that satisfy requirement fitness criteria such as by using a genetic algorithm to select a specified minimum number of test cases that are required to achieve a specified level of branch coverage at which point the genetic algorithm is stopped and the application is tested using the selected test cases. Kommineni at Abstract; id. at ¶¶ 0027, 0047, 0048, and 0085; id. at fig. 2; id. at ¶¶ 0016 & 0017 (test cases satisfy requirement specification).
Warfield and Kommineni are analogous art because they are from the “same field of endeavor” and are both from the same “problem-solving area.” Specifically, they are both from the field of software testing, and both are trying to solve the problem of how to use a genetic algorithm to select test cases.
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine using a genetic algorithm to select the best test cases for testing an application, as taught in Warfield, with using a genetic algorithm to select the best test cases based on selection criteria, as taught in Kommineni. Kommineni teaches that it is desirable to try and obtain a minimized number of test cases. Kommineni at ¶ 0002. Therefore, one having ordinary skill in the art would have been motivated to combine using a genetic algorithm to select the best test cases for testing an application, as taught in Warfield, with using a genetic algorithm to select the best test cases based on selection criteria, as taught in Kommineni, for the purpose of using criteria to select the best test cases with a method that requires selecting the best test cases.}
Claims 3, 10, and 17
With respect to claims 3, 10, and 17, Warfield and Kommineni teach the invention as claimed including:
wherein the one or more processors are further configured to: prior to determining the fitness score for each test case of the selected population of test cases: initialize the selected population of test cases; and assign each test case of the selected population of test cases to one of a plurality of test suites based at least in part on a functionality to be tested.
{Initial test cases for a software application are provided to a genetic algorithm which iteratively (repeatedly) creates new generations of tests cases by selecting a subset of each previous generation based on a plurality of different types of fitness score data stored for each test, uses crossover points between prior tests and/or mutates values for the prior tests to generate the next generation of tests until a generation of test cases produces the “best” test cases based on the fitness criteria at which point the application may be tested using such scripts that were generated by the genetic algorithm. Warfield at Abstract; id. at col. 3 ll. 44 – 66, id. at col. 4 ll. 5 – 35; id. at col. 5 ll. 15 – 18; id. at col. 8 ll. 13 – 62; id. at col.10 ll. 16 – 38; id. at Claim 32 & fig. 1 (program storage device of computer 10 includes memory 12 and mass storage 19 for generating and storing the plurality of test scripts and fitness scores).}
Claims 4, 11, and 18
With respect to claims 4, 11, and 18, Warfield and Kommineni teach the invention as claimed including:
wherein the natural computing algorithm comprises a genetic algorithm (GA). {Initial test cases for a software application are provided to a genetic algorithm which iteratively (repeatedly) creates new generations of tests cases by selecting a subset of each previous generation based on a plurality of different types of fitness score data stored for each test, uses crossover points between prior tests and/or mutates values for the prior tests to generate the next generation of tests until a generation of test cases produces the “best” test cases based on the fitness criteria at which point the application may be tested using such scripts that were generated by the genetic algorithm. Warfield at Abstract; id. at col. 3 ll. 44 – 66, id. at col. 4 ll. 5 – 35; id. at col. 5 ll. 15 – 18; id. at col. 8 ll. 13 – 62; id. at col.10 ll. 16 – 38; id. at Claim 32 & fig. 1 (program storage device of computer 10 includes memory 12 and mass storage 19 for generating and storing the plurality of test scripts and fitness scores).}
Claims 5, 12, and 19
With respect to claims 5, 12, and 19, Warfield and Kommineni teach the invention as claimed including:
wherein the one or more processors are further configured to execute the genetic algorithm (GA) by: selecting a set of test cases from the selected population of test cases, wherein the selected set of test cases comprises test cases having a highest fitness score; generating, based at least in part on the selected set of test cases, at least one new test case by 1) identifying a crossover point between at least one pair of test cases of the selected set of test cases and 2) alternating one or more values of a sequence of values representative of each test case of the at least one pair of test cases, the one or more values of the sequence of values being alternated until the identified crossover point between the at least one pair of test cases is reached; performing a mutation of the at least one new test case by altering one or more values of a sequence of values representative of the at least one new test case; and generating a new population of test cases, wherein the new population of test cases comprises the at least one new test case. {Initial test cases for a software application are provided to a genetic algorithm which iteratively (repeatedly) creates new generations of tests cases by selecting a subset of each previous generation based on a plurality of different types of fitness score data stored for each test, uses crossover points between prior tests and/or mutates values for the prior tests to generate the next generation of tests until a generation of test cases produces the “best” test cases based on the fitness criteria at which point the application may be tested using such scripts that were generated by the genetic algorithm. Warfield at Abstract; id. at col. 3 ll. 44 – 66, id. at col. 4 ll. 5 – 35; id. at col. 5 ll. 15 – 18; id. at col. 8 ll. 13 – 62; id. at col.10 ll. 16 – 38; id. at Claim 32 & fig. 1 (program storage device of computer 10 includes memory 12 and mass storage 19 for generating and storing the plurality of test scripts and fitness scores).}
Claims 6, 13, and 20
With respect to claims 6, 13, and 20, Warfield and Kommineni teach the invention as claimed including:
wherein the one or more processors are further configured to determine whether the identified one or more best possible test cases satisfies the second set of fitness criteria based at least in part on whether the identified one or more best possible test cases satisfies one or more of a credibility criterion, a feasibility criterion, a requirements coverage criterion, or a requirements traceability criterion. {Test cases for satisfying a requirement coverage are selected for a software application to satisfy fitness criteria such as by using a genetic algorithm to select a specified secondary criterion such as a minimum number of test cases that are required to achieve a specified level of branch coverage at which point the genetic algorithm is stopped and the application is tested using the selected test cases. Kommineni at Abstract; id. at ¶¶ 0027, 0047, 0048, and 0085; id. at fig. 2.}
Claims 7 and 14
With respect to claims 7 and 14, Warfield and Kommineni teach the invention as claimed including:
wherein the one or more processors are further configured to: prior to accessing the selected population of test cases and the first set of fitness criteria, generate the selected population of test cases based on the total population of test cases. {Initial test cases for a software application are generated from a total potential population and are provided to a genetic algorithm which iteratively (repeatedly) creates new generations of tests cases by selecting a subset of each previous generation based on a plurality of different types of fitness score data stored for each test, uses crossover points between prior tests and/or mutates values for the prior tests to generate the next generation of tests until a generation of test cases produces the “best” test cases based on the fitness criteria at which point the application may be tested using such scripts that were generated by the genetic algorithm. Warfield at Abstract; id. at col. 3 ll. 44 – 66, id. at col. 4 ll. 5 – 35; id. at col. 5 ll. 15 – 18; id. at col. 8 ll. 13 – 62; id. at col.10 ll. 16 – 38; id. at Claim 32 & fig. 1 (program storage device of computer 10 includes memory 12 and mass storage 19 for generating and storing the plurality of test scripts and fitness scores); id. at col. 7 ll. 43 – 45 & 60 – 62, id. at col. 8 ll. 8 – 12, and id. at col. 10 ll. 6 – 13 (initial test case generation and selection).}
Claims 2, 9, and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Warfield and Kommineni in view of Mitchell et al., United States Patent Application Publication No. 2019/0171552 (Published June 6, 2019, filed December 1, 2017) (“Mitchell”).
Claims 2, 9, and 16
With respect to claims 2, 9, and 16, Warfield and Kommineni teach the invention as claimed, however, Warfield and Kommineni doesn’t explicitly teach the limitation:
wherein the first instance of the software application comprises an instance of the software application during development time, and wherein the second instance of the software application comprises an instance of the software application during runtime. {Mitchell does teach this limitation. Mitchell teaches that using a genetic algorithm to select the best test cases for testing an application, as taught in Warfield and Kommineni, may include performing the testing during both development and production stages. Mitchell at Abstract; id. at ¶¶ 0003, 0009, 0021 – 0025 (development and production testing); id. at ¶¶ 0007, 0026, 0027 (genetic algorithm).
Warfield, Kommineni, and Mitchell are analogous art because they are from the “same field of endeavor” and are both from the same “problem-solving area.” Specifically, they are both from the field of software testing, and both are trying to solve the problem of using a genetic algorithm to select test cases.
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine using a genetic algorithm to select the best test cases for testing an application, as taught in Warfield and Kommineni, with performing the testing during both development and production stages, as taught in Mitchell. Kommineni teaches that it is desirable to try and obtain a minimized number of test cases. Kommineni at ¶ 0002. Therefore, one having ordinary skill in the art would have been motivated to combine using a genetic algorithm to select the best test cases for testing an application, as taught in Warfield and Kommineni, with performing the testing during both development and production stages, as taught in Mitchell, for the purpose of using the genetic algorithm to select the best test cases for testing at multiple different testing stages.}
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 extension fee 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 THEODORE E HEBERT whose telephone number is (571)270-1409. The examiner can normally be reached on Monday to Friday 9:00 a.m. to 6:00 p.m..
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//T.H./ September 22, 2026
Examiner, Art Unit 2199
/LEWIS A BULLOCK JR/Supervisory Patent Examiner, Art Unit 2199
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