DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . This office action is in response to communication filed 12/22/2025.
The instant application having application No. 18/519,688 filed on November 27, 2023, has no priority information.
Status of the Claims
Claims 1, 2, 6, 9-13, 16, and 19 are amended, claims 3 and 7-8 are canceled. Claims 21-23 are added. Accordingly, claims 1-2, 4-6, and 9-23 are currently pending in the application.
Response to Amendment
(A). Regarding spec objection: Applicant’s amendments to the spec appropriately addressed the objection, the objection is withdrawn.
(B). Regarding art rejection: In regards to pending claims, Applicant's amendments necessitated further search, and new grounds of rejections are presented in the following art rejection.
Examiner Notes
Examiner cites particular columns, paragraphs, figures and line numbers in the references as applied to the claims below for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested that, in preparing responses, the applicant fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the examiner.
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 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.
Claim Rejections - 35 USC § 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.
Claims 1-2, 4-5, 16-17 are rejected under 35 U.S.C. 103 as being unpatentable over WALTERS et al. (US 20200012583 A1, hereinafter “WALTERS”) in view of VASAVAN et al. (US 20220350733 A1, hereinafter “VASAVAN”).
With respect to claim 1 (Currently Amended), WALTERS discloses A system for dataset-based application testing (e.g. Fig. 1), the system comprising:
one or more memories; and
one or more processors, (e.g. Fig. 3. para [0034], “API management system 104 may include one or more computing systems configured to manage training of models for system 100 and route API calls, consistent with disclosed embodiments. …” wherein computing systems comprise memories and processors), configured to:
receive information identifying a[[n]] primary application for testing, wherein the primary application includes a dataset processing component that receives an input dataset and generates an actual output dataset (e.g. para [0107], “… The request may be a request to test one or more API nodes, consistent with disclosed embodiments. … For example, the instructions may specify a range of API call parameters and/or a list of API functions. The request may include one or more API identifiers, routing tables, routing models, and/or information identifying a routing model. The request may include a request to provide model output via a display (e.g., as depicted in interface 250 of FIG. 2B) and/or to store model output.” Wherein the API reads on an application for testing);
receive information identifying a secondary application that is a non-preferred, existing version of the primary application (e.g. para [0126], “At step 802, API management system 104 receives input, …. The information may include an API call, API response, a translated input or an output from translation model 502 and/or an API dataset …” para [0127], “At step 804, API management system 104 selects one or more node-testing models, ... The version of API may be associated with the call. For example, a first selected node-testing model may correspond to the first version of the API, and a second selected node-testing model may correspond to the second version of the API. These node-testing models may be, for example, node-testing model A 501a and/or node-testing model B 501b.” wherein node-testing model A 501a reads on a secondary application that is a non-preferred, existing version of the primary application);
identify, by the secondary application, an expected output dataset for the primary application(e.g. para [0129], “… For example, the expected output may include the model output from the node-testing model corresponding to a first version of an API (e.g., model output A, shown in FIG. 5). In some embodiments, the expected output may include system logs or analytic data. In some embodiments, the logs or analytic data may be unrelated to the input. …” wherein a first version of an API reads on the secondary application);
execute the primary application on the input dataset to generate the actual output dataset (e.g. para [0134], “… In some embodiments, at least one model output may be generated by a node-testing model corresponding to a second version of an API based on the translated input (e.g., as illustrated in model output B of FIG. 5). …”);
generate a data characterization comparing the actual output dataset and the expected output dataset with respect to a set of metrics (e.g. para [0135], “… This test criterion may include, for example, a percent match between a model output corresponding to a second version of an API generated at step 812 and an expected model output, or a percent match between a schema of the model output and an expected schema. …”);
determine that the data characterization passes the primary application and the input dataset for deployment (e.g. para [0135], “… In some embodiments, determining whether a model output satisfies a testing criterion may involve determining whether multiple model outputs satisfy a desired distribution related to expected model outputs.”); and
cause the primary application to be deployed to a deployment environment based on the data characterization passing the primary application and the input dataset for deployment (e.g. para [0138], “…; and/or transmitting the pre-updated and/or updated model to another component of system 100 (e.g. API system 102a, 102b, 102n and/or client device 112) and/or to a computing component outside system 100 (e.g., via interface 106). …” wherein transmitting the model to another component of system or to computing component outside system suggests deployment).
WALTERS does not appear to explicitly disclose
identify, by the primary application, the input dataset by accessing one or more data structures;
However this is taught in analogous art, VASAVAN (e.g. para [0018], “… the testing system 115 may identify the information stored in the data structure as the software product to be tested and/or as test input data associated with the software product.”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the invention of WALTERS with the invention of VASAVAN because it provides techniques for automatically generating and executing a test case plan for a software product, and conserving computing resources, networking resources, human resources, and/or the like associated with attempting to locate the technical description of the software product, attempting to gain the technical knowledge of the software product, generating incorrect software tests based on incorrect technical knowledge of the software product, reperforming the incorrect software tests, handling incorrect test results based on execution of the incorrect software tests, and/or the like. A person having ordinary skill in the art would have been motivated to make this combination, with a reasonable expectation of success, for the purpose of providing techniques for automatically generating and executing a test case plan for a software product, and conserving computing resources, networking resources, human resources, and/or the like associated with attempting to locate the technical description of the software product, attempting to gain the technical knowledge of the software product, generating incorrect software tests based on incorrect technical knowledge of the software product, reperforming the incorrect software tests, handling incorrect test results based on execution of the incorrect software tests, and/or the like as suggested by VASAVAN (see para [0010]).
With respect to claim 2 (Currently Amended), WALTERS discloses wherein the one or more processors, to generate the data characterization, are configured to:
generate the data characterization based on an equivalency or a logical relationship between the expected output dataset and the actual output dataset (e.g. para [0135], “… In some embodiments, determining whether a model output satisfies a testing criterion may involve determining whether multiple model outputs satisfy a desired distribution related to expected model outputs.” Wherein satisfying a desired distribution suggests equivalency).
With respect to claim 4, WALTERS discloses wherein the one or more processors, to generate the data characterization, are configured to:
generate the data characterization based on a range of values by which the expected output dataset differs from the actual output dataset. (e.g. para [0135], “… In another example, API management system 104 may see if a key or value of the model output is within a desirable range.. ...” Wherein a desirable range suggests the difference limit between the expected output and the actual output).
With respect to claim 5, WALTERS discloses wherein the one or more processors, to generate the data characterization, are configured to:
generate the data characterization based on a first statistical distribution of the expected output dataset relative to a second statistical distribution of the actual output dataset. (e.g. para [0135], “… For example, the test criterion may be based on a data profile or a statistic metric of API calls, … In some embodiments, determining whether a model output satisfies a testing criterion may involve determining whether multiple model outputs satisfy a desired distribution related to expected model outputs.”)
With respect to claim 16 (Currently Amended), it is directed to a non-transitory computer-readable medium to implement the method disclosed in claim 1, wherein the memory reads on a non-transitory computer-readable medium, and deploying the application based on the data characterization passing for deployment reads on selectively perform deployment, i.e. perform deployment when data characterization passes, please see the rejections directed to claim 1 above which also cover the limitations recited in claim 16.
With respect to claim 17, it recites same features as either claim 2, or 4, or 5, and is rejected for the same reason.
Claims 6 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over WALTERS in view of VASAVAN as applied to claims 1 and 16 respectively, in further view of NUSHI et al. (US 20200349395 A1, hereinafter “NUSHI”).
With respect to claim 6, WALTERS as modified by VASAVAN discloses The system of claim 1, but does not appear to explicitly disclose
wherein one of the input dataset is a plurality of datasets and the actual output dataset is another plurality of datasets;
the input dataset is a single dataset and the output dataset is another single dataset; or
the input dataset is a single dataset and the output dataset is a plurality of datasets..
However in analogous art, NUSHI discloses
wherein one of the input dataset is a plurality of datasets and the actual output dataset is another plurality of datasets (e.g. para [0086], “… For example, the act 610 may include receiving (e.g., from a machine learning system trained to generate an output for a given instance) a plurality of outputs for a test dataset, the test dataset comprising a plurality of test instances.. …”),
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the invention of NUSHI because it provides techniques for significantly reducing utilization of processing resources as well as accomplishing a higher degree of accuracy for the resulting machine learning system. A person having ordinary skill in the art would have been motivated to make this combination, with a reasonable expectation of success, for the purpose of providing techniques for significantly reducing utilization of processing resources as well as accomplishing a higher degree of accuracy for the resulting machine learning system as suggested by NUSHI (see para [0015]).
With respect to claim 18, a many-to-many basis corresponds to the office action regarding claim 6, and is rejected for the same reason as for claim 6.
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over WALTERS in view of VASAVAN and Wilson et al. (US 20240338309 A1, hereinafter “Wilson”).
With respect to claim 9, WALTERS discloses A method for dataset-based application testing (e.g. Fig. 3), comprising:
receiving, by a data test system, information identifying a[[n]] primary application for testing, wherein the primary application includes a dataset processing component that receives an input dataset and generates an actual output dataset (e.g. para [0107], “… The request may be a request to test one or more API nodes, consistent with disclosed embodiments. … For example, the instructions may specify a range of API call parameters and/or a list of API functions. The request may include one or more API identifiers, routing tables, routing models, and/or information identifying a routing model. The request may include a request to provide model output via a display (e.g., as depicted in interface 250 of FIG. 2B) and/or to store model output.” Wherein the API reads on an application for testing);
receiving, by the data test system, information identifying a secondary application that is a non-preferred, existing version of the primary application (e.g. para [0126], “At step 802, API management system 104 receives input, …. The information may include an API call, API response, a translated input or an output from translation model 502 and/or an API dataset …” para [0127], “At step 804, API management system 104 selects one or more node-testing models, ... The version of API may be associated with the call. For example, a first selected node-testing model may correspond to the first version of the API, and a second selected node-testing model may correspond to the second version of the API. These node-testing models may be, for example, node-testing model A 501a and/or node-testing model B 501b.” wherein node-testing model A 501a reads on a secondary application that is a non-preferred, existing version of the primary application);
identifying, by the data test system via the secondary application, an expected output dataset for the primary application(e.g. para [0129], “… For example, the expected output may include the model output from the node-testing model corresponding to a first version of an API (e.g., model output A, shown in FIG. 5). In some embodiments, the expected output may include system logs or analytic data. In some embodiments, the logs or analytic data may be unrelated to the input. …”);
executing, by the data test system, the primary application on the input dataset to generate the actual output dataset (e.g. para [0134], “… In some embodiments, at least one model output may be generated by a node-testing model corresponding to a second version of an API based on the input (e.g., as illustrated in model output A of FIG. 5).”);
generating, by the data test system, a data characterization comparing the actual output dataset and the expected output dataset with respect to a set of metrics (e.g. para [0135], “… This test criterion may include, for example, a percent match between a model output corresponding to a second version of an API generated at step 812 and an expected model output, or a percent match between a schema of the model output and an expected schema. …”);
determining, by the data test system, whether the data characterization passes the primary application and the input dataset for deployment (e.g. para [0135], “… In some embodiments, determining whether a model output satisfies a testing criterion may involve determining whether multiple model outputs satisfy a desired distribution related to expected model outputs.”);
WALTERS does not appear to explicitly disclose
identifying, by the data test system via the primary application, the input dataset by accessing one or more data structures;
transmitting, by the data test system, information indicating whether the data characterization passes the primary application and input dataset for deployment.
However, in analogous art, VASAVAN discloses
identifying, by the data test system via the primary application, the input dataset by accessing one or more data structures (e.g. para [0018], “… the testing system 115 may
identify the information stored in the data structure as the software product to be tested and/or as test input data associated with the software product.”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the invention of WALTERS with the invention of VASAVAN because it provides techniques for automatically generating and executing a test case plan for a software product, and conserving computing resources, networking resources, human resources, and/or the like associated with attempting to locate the technical description of the software product, attempting to gain the technical knowledge of the software product, generating incorrect software tests based on incorrect technical knowledge of the software product, reperforming the incorrect software tests, handling incorrect test results based on execution of the incorrect software tests, and/or the like. A person having ordinary skill in the art would have been motivated to make this combination, with a reasonable expectation of success, for the purpose of providing techniques for automatically generating and executing a test case plan for a software product, and conserving computing resources, networking resources, human resources, and/or the like associated with attempting to locate the technical description of the software product, attempting to gain the technical knowledge of the software product, generating incorrect software tests based on incorrect technical knowledge of the software product, reperforming the incorrect software tests, handling incorrect test results based on execution of the incorrect software tests, and/or the like as suggested by VASAVAN (see para [0010]).
WALTERS as modified by VASAVAN does not appear to explicitly disclose
transmitting, by the data test system, information indicating whether the data characterization passes the primary application and input dataset for deployment.
However, this is taught in analogous art, Wilson (e.g. para [0058], “When build validation module 112 determines that testing of the application artifacts in environment 128a is successful, build validation module 112 can transmit this indication to build deployment tool 112 to continue with the production deployment process. …”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the invention of Wilson because it provides techniques for systematic software application release preparation and deployment, including automation of data and dependency collection and validation analysis for each code release and provision of a user interface that can make software application release validation and deployment to multiple different testing and production computing environments simple to execute and review. A person having ordinary skill in the art would have been motivated to make this combination, with a reasonable expectation of success, for the purpose of providing techniques for systematic software application release preparation and deployment, including automation of data and dependency collection and validation analysis for each code release and provision of a user interface that can make software application release validation and deployment to multiple different testing and production computing environments simple to execute and review as suggested by Wilson (see para [0003-0004]).
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over WALTERS in view of VASAVAN and Wilson as applied to claim 9, in further view of Bussa et al. (US 20230011250 A1, hereinafter “Bussa”).
With respect to claim 10 (Currently Amended), WALTERS as modified by VASAVAN and Wilson discloses The method of claim 9, but does not appear to explicitly disclose wherein transmitting the information indicating whether the data characterization passes the primary application and the input dataset for deployment comprises:
transmitting an indication of an error associated with the primary application or the input dataset. However this is taught in analogous art, Bussa (e.g. para [0098], “In examples where the CI/CD testing computing platform 110 identified errors or anomalies in the compiled test results data, the CI/CD testing computing platform 110 may transmit one or more indications of identified errors or anomalies to the web service computing platform 120 and/or to the developer computing device 160 at step 215. …”),
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the invention of Bussa because it provides effective, efficient, scalable, and convenient technical solutions that address and overcome the technical problems associated with software testing. A person having ordinary skill in the art would have been motivated to make this combination, with a reasonable expectation of success, for the purpose of providing effective, efficient, scalable, and convenient technical solutions that address and overcome the technical problems associated with software testing as suggested by Bussa (see para [0002-0003]).
Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over WALTERS in view of VASAVAN, Wilson and Bussa as applied to claim 10, in further view of Uniyal et al. (US 20230113263 A1, hereinafter “Uniyal”).
With respect to claim 11 (Currently Amended), WALTERS as modified by VASAVAN, Wilson and Bussa discloses The method of claim 10, Wilson further discloses transmitting updated information indicating whether the primary application and the input dataset are to be deployed based on re-characterizing the primary application and the input dataset (e.g. para [0058] as cited above regarding claim 9. For motivation to combine, please refer to office action regarding claim 9 above). But does not appear to explicitly disclose further comprising:
receiving an update to the input dataset or the primary application;
re-characterizing the primary application and the input dataset based on receiving the update;
However, in analogous art, Uniyal discloses further comprising:
receiving an update to the input dataset or the primary application (e.g. para [0026], “… In some embodiments, the regression event is a received software update
associated with unified regression platform 100. …”);
re-characterizing the primary application and the input dataset based on receiving the update (e.g. para [0027], “To perform regression testing and ensure reports are generated correctly, regression run 112 may be configured to perform regression testing on reports associated with the run IDs defined at registration 104 as described above. …” para [0028], “In some embodiments, once regression run 112 regression tests all relevant run IDs, a compare event is raised, and comparison 114 compares relevant file attributes between the reference reports and the regenerated reports. …” wherein regression testing and comparison process read on re-characterizing);
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the invention of Uniyal because it provides techniques for an automated regression testing platform for automating regression testing on files to substantially reduce the manual labor cost to ensure accurate generation of the files. A person having ordinary skill in the art would have been motivated to make this combination, with a reasonable expectation of success, for the purpose of providing techniques for an automated regression testing platform for automating regression testing on files to substantially reduce the manual labor cost to ensure accurate generation of the files as suggested by Uniyal (see para [0003-0004]).
Claims 12 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over WALTERS in view of VASAVAN and Wilson as applied to claims 9 and 16 respectively, in further view of Dakov et al. (US 20250165381 A1, hereinafter “Dakov”).
With respect to claim 12 (Currently Amended), WALTERS as modified by VASAVAN and Wilson discloses The method of claim 9, but does not appear to explicitly disclose further comprising: storing a log of the information indicating whether the data characterization passes the primary application and the input dataset for deployment. However this is taught in analogous art, Dakov (e.g. para [0050], “… A record
associated with a successful correction of the software application error (leading to successful completion of the updated software deployment) can be generated and transmitted for storage in a software application error database.”),
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the invention of Dakov because it provides techniques for assisting with solving software application errors. A person having ordinary skill in the art would have been motivated to make this combination, with a reasonable expectation of success, for the purpose of providing techniques for assisting with solving software application errors as suggested by Dakov (see para [0002-0003]).
With respect to claim 19 (Currently Amended), it recites same features as either claim 12, and is rejected for the same reason.
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over WALTERS in view of VASAVAN, Wilson and Dakov as applied to claim 12, in further view of Moraes et al. (US 20240069908 A1, hereinafter “Moraes”).
With respect to claim 13 (Currently Amended), WALTERS as modified by VASAVAN, Wilson and Dakov discloses The method of claim 12, Dakov further discloses further comprising:
monitoring operation of the primary application after deployment of the primary application (e.g. para [0039], “… The error log can include one or more software application errors generated by an execution engine tracking the deployment of the software product throughout a computing system including multiple computing devices with fixed and/or variable components. …” For motivation to combine, please refer to office action regarding claim 12);
detecting an event associated with operation of the primary application (e.g. para [0039] as cited above. For motivation to combine, please refer to office action regarding claim 12);
performing an application management action based on a result of comparing the one or more outputs of the primary application with the log of the information (e.g. Fig. 3, step 310 or 312. For motivation to combine, please refer to office action regarding claim 12).
but does not appear to explicitly disclose comparing one or more outputs of the primary application with the log of the information; However this is taught in analogous art, Moraes (e.g. para [0092], “… In various cases, this can be facilitated by comparing the set of differences to a set of expected differences (e.g., 214) associated with the functional test or with the modified version of the computing application.” Wherein a set of expected differences (e.g., 214) reads on the log of the information. Para [0074] discloses that the set of expected differences (e.g., 214) is retrieved from a storage, “… In various aspects, the classification component 212 can electronically store, electronically maintain, electronically retrieve, or otherwise electronically access a set of expected stream differences 214. …”),
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the invention of Moraes because it provides techniques for catching non-visually-manifested differences between the current version and the new version. A person having ordinary skill in the art would have been motivated to make this combination, with a reasonable expectation of success, for the purpose of providing techniques for catching non-visually-manifested differences between the current version and the new version as suggested by Moraes (see para [0016]).
Claims 14 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over WALTERS in view of VASAVAN and Wilson as applied to claims 9 and 16 respectively, in further view of McLaren (US 20210279047 A1, hereinafter “McLaren”).
With respect to claim 14, WALTERS as modified by VASAVAN and Wilson discloses The method of claim 9, but does not appear to explicitly disclose wherein the input dataset includes synthetic or artificial data. However this is taught in analogous art, McLaren (e.g. para [0014], “Pre-deployment testing, such as unit, functional, integration, contract tests, and others, may be used to exercise microservice code paths using synthetic (i.e., not real production) input prior to deployment of the microservice under test within the production environment. ...”),
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the invention of McLaren because it provides techniques that preserve the advantages of in production testing, but without the potential adverse effects by isolating the production environment from the microservice under test. A person having ordinary skill in the art would have been motivated to make this combination, with a reasonable expectation of success, for the purpose of providing techniques that preserve the advantages of in production testing, but without the potential adverse effects by isolating the production environment from the microservice under test as suggested by McLaren (see para [0016]).
With respect to claim 20, it recites same features as either claim 14, and is rejected for the same reason.
Claim 15 is rejected under 35 U.S.C. 103 as being unpatentable over WALTERS in view of VASAVAN and Wilson as applied to claim 9, in further view of Singi et al. (US 20180260314 A1, hereinafter “Singi”).
With respect to claim 15, WALTERS as modified by VASAVAN and Wilson discloses The method of claim 9, WALTERS further discloses wherein generating the data characterization comprises:
generating the data characterization based on the set of test cases (e.g. para [0135] cited above regarding claim 9, “… This test criterion may include, for example, a percent match between a model output corresponding to a second version of an API generated at step 812 and an expected model output, or a percent match between a schema of the model output and an expected schema. …”). But does not appear to explicitly disclose further comprising:
generating the input dataset to include one or more outlier values associated with a set of test cases; However this is taught in analogous art, Singi (e.g. para [0014], “Pre-deployment testing, such as unit, functional, integration, contract tests, and others, may be used to exercise microservice code paths using synthetic (i.e., not real production) input prior to deployment of the microservice under test within the production environment. ...”),
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the invention of Singi because it provides testing techniques result in a better utilization of resources. A person having ordinary skill in the art would have been motivated to make this combination, with a reasonable expectation of success, for the purpose of providing testing techniques result in a better utilization of resources as suggested by Singi (see para [0021]).
Claim 21 is rejected under 35 U.S.C. 103 as being unpatentable over WALTERS in view of VASAVAN and Wilson as applied to claim 1, in further view of Allen et al. (US 20160132423 A1, hereinafter “Allen”).
With respect to claim 21 (New), WALTERS as modified by VASAVAN and Wilson discloses The system of claim 1, but does not appear to explicitly disclose wherein the secondary application is executed in a different type of execution environment and uses a different set of execution resources than the primary application.
However, this is taught in analogous art, Allen (e.g. para [0036], “… For example, it may be appreciated that multiple versions of the same general software product (e.g., the product-under-test) may be produced, which may be configured to execute in different computing
environments. An example of different environments under which the different version of the same general software product may be executed may include different operating
systems, and/or different versions of an operating system. …” wherein a different version of the same general software product reads on the secondary application, the different operating system reads on a different set of execution resources.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the invention of Allen because it provides testing techniques for inspecting any and all environments under which the product-under-test may be run, including different versions of operating systems, for any information indicative of requirements for the test case to execute properly. A person having ordinary skill in the art would have been motivated to make this combination, with a reasonable expectation of success, for the purpose of providing testing techniques for inspecting any and all environments under which the product-under-test may be run, including different versions of operating systems, for any information indicative of requirements for the test case to execute properly as suggested by Allen (see para [0036]).
Claims 22 and 23 are rejected under 35 U.S.C. 103 as being unpatentable over WALTERS in view of VASAVAN and Wilson as applied to claim 1, in further view of Gabrovski et al. (US 10896116 B1, hereinafter “Gabrovski”).
With respect to claim 22 (New), WALTERS as modified by VASAVAN and Wilson discloses The system of claim 1, but does not appear to explicitly disclose wherein the secondary application is a less efficient version of the primary application.
However, this is taught in analogous art, Gabrovski (e.g. col 8, lines 18-48, “The CPU and memory usage for various functions for the latest version of the software may then be compared by one of the one or more server computing device 110 to the respective distributions in order to detect performance regressions or anomalies….” Wherein to detect performance regression in terms of CPU and memory usage suggests that the latest version (reads on the primary application) is more efficient than the previous version which reads on the secondary application.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the invention of Gabrovski because it provides techniques for testing and validating software before such software is actually used to ensure safety. A person having ordinary skill in the art would have been motivated to make this combination, with a reasonable expectation of success, for the purpose of providing techniques for testing and validating software before such software is actually used to ensure safety as suggested by Gabrovski (see col 1, lines 6-38).
With respect to claim 23 (New), WALTERS as modified by VASAVAN and Wilson discloses The system of claim 1, but does not appear to explicitly disclose wherein the primary application has a higher level of resource efficiency than the secondary application.
However, this is taught in analogous art, Gabrovski (e.g. col 8, lines 18-48, “The CPU and memory usage for various functions for the latest version of the software may then be compared by one of the one or more server computing device 110 to the respective distributions in order to detect performance regressions or anomalies….” Wherein to detect performance regression in terms of CPU and memory usage suggests that the latest version (reads on the primary application) is more efficient or has a higher level of resource efficient than the previous version which reads on the secondary application.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the invention of Gabrovski because it provides techniques for testing and validating software before such software is actually used to ensure safety. A person having ordinary skill in the art would have been motivated to make this combination, with a reasonable expectation of success, for the purpose of providing techniques for testing and validating software before such software is actually used to ensure safety as suggested by Gabrovski (see col 1, lines 6-38).
Response to Arguments
Applicant's arguments with respect to art rejections filed 12/22/2025 have been fully considered and are moot upon new grounds of rejections made in the office action above.
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 Zengpu Wei whose telephone number is 571-270-1302. The examiner can normally be reached on Monday to Friday from 8:00AM to 5:00 PM.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Bradley Teets, can be reached on 571-272-3338. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ZENGPU WEI/
Examiner, Art Unit 2197
/BRADLEY A TEETS/Supervisory Patent Examiner, Art Unit 2197
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