Patent Issued for Intelligent software agent to facilitate software development and operations (USPTO 11693650): Hartford Fire Insurance Company

2023 JUL 25 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- A patent by the inventors Mittal, Sachin (Cumming, GA, US), Thomas, Renoi (Thornwood, NY, US), Venugopal, Satish (Chennai, IN), Yaramchitti, Sandeep Kumar (Manchester, CT, US), filed on September 20, 2022, was published online on July 4, 2023, according to news reporting originating from Alexandria, Virginia, by NewsRx correspondents.

Patent number 11693650 is assigned to Hartford Fire Insurance Company (Hartford, Connecticut, United States).

The following quote was obtained by the news editors from the background information supplied by the inventors: “An enterprise may develop and deploy software applications. For example, a business might write software applications (and periodic upgrades to those applications) to handle internal workflows, interactions with customers, etc. As part of the software development process, the enterprise may implement quality assurance processes to reduce the likelihood of errors and improve the stability of the software application. For example, the enterprise might manually review software error logs to monitor the quality of software development. Recently, enterprises have begun to combine software development practices and information technology operations to shorten the system development lifecycle while still delivering features, fixes, and updates in accordance with business objectives. This trend, which includes Continuous Integration (“CI”) and Continuous Deployment (“CD”) processes which introduce a fast pace of software builds and automated test executions. Manually implementing quality assurance in such an environment can be a time consuming and error-prone task (e.g., a team of experts may face a huge job of reviewing software logs to determine the root causes of an error).

“It would be desirable to provide systems and methods to automatically and efficiently implement quality assurance in a software development environment.”

In addition to the background information obtained for this patent, NewsRx journalists also obtained the inventors’ summary information for this patent: “According to some embodiments, a system may facilitate software development and operations for an enterprise. A communication input port may receive information associated with a software continuous integration/deployment pipeline of the enterprise. An intelligent software agent platform, coupled to the communication input port, may listen for a trigger indication from the software continuous integration/deployment pipeline. Responsive to the trigger indication, the intelligent software agent platform may apply system configuration and rule layer information to extract software log data and apply a machine learning model to the extracted software log data to generate a pipeline health check analysis report. The pipeline health check analysis report may include, for example, an automatically generated prediction associated with future operation of the software continuous integration/deployment pipeline. The intelligent software agent platform may then facilitate transmission of the pipeline health check analysis report via a communication output port and a distributed communication network.

“Some embodiments comprise: means for listening, by intelligent software agent platform, to information from a communication input port associated with a software continuous integration/deployment pipeline of an enterprise, wherein the intelligent agent is listening for a trigger indication from the software continuous integration/deployment pipeline; responsive to the trigger indication, means for applying system configuration and rule layer information to extract software log data; means for applying a machine learning model to the extracted software log data to generate a pipeline health check analysis report, wherein the pipeline health check analysis report includes an automatically generated prediction associated with future operation of the software continuous integration/deployment pipeline; and means for transmitting, via a communication output port coupled to the intelligent software agent platform, the pipeline health check analysis report via a distributed communication network.

“In some embodiments, a communication device associated with an intelligent software agent platform exchanges information with remote devices in connection with an interactive graphical user interface. The information may be exchanged, for example, via public and/or proprietary communication networks.

“A technical effect of some embodiments of the invention is an improved and computerized way to automatically and efficiently implement quality assurance in a software development environment. With these and other advantages and features that will become hereinafter apparent, a more complete understanding of the nature of the invention can be obtained by referring to the following detailed description and to the drawings appended hereto.”

The claims supplied by the inventors are:

“1. A system to facilitate software development and operations for an enterprise, comprising: (a) a communication input port to receive information associated with a software continuous integration and/or deployment pipeline of the enterprise; (b) an intelligent software agent platform, coupled to the communication input port, including a computer processor and a memory storing instructions to cause the computer processor to: (i) listen for a trigger indication from the software continuous integration and/or deployment pipeline, (ii) responsive to the trigger indication, apply system configuration information and rule layer information to extract software log data, and (iii) apply a machine learning model to the extracted software log data to generate a pipeline health check analysis report, wherein the pipeline health check analysis report includes an automatically generated prediction associated with future operation of the software continuous integration and/or deployment pipeline; and © a communication output port coupled to the intelligent software agent platform to facilitate transmission of the pipeline health check analysis report via a distributed communication network; wherein the pipeline health check analysis report includes: a prediction of a level of stability of the software continuous integration and/or deployment pipeline; a percentage of software builds that have successively passed through the software continuous integration and/or deployment pipeline during a time period; a prediction of a future type of failure of the software continuous integration and/or deployment pipeline; and a number of test jobs associated with an application program; and wherein the pipeline health check analysis report comprises an email message transmitted to at least one of: (i) a subject matter expert, (ii) a software development engineer in test, (iii) a software manager, (iv) a quality control member, (v) a quality assurance member, or (vi) any other stakeholder.

“2. The system of claim 1, wherein the machine learning model is associated with a knowledge map of the software continuous integration and/or deployment pipeline that classifies errors in the software log data.

“3. The system of claim 1, wherein the software continuous integration and/or deployment pipeline includes at least one of: (i) code and build components, (ii) static code analysis, (iii) deployment, (iv) build completion, (iv) a test trigger, (v) a performance measurement component, and (vi) any other type of pipeline component.

“4. The system of claim 1, wherein the system configuration information includes at least one of: (i) a pipeline configuration, (ii) a user configuration, and (iii) a log properties configuration.

“5. The system of claim 4, wherein the system configuration information includes at least one of: (i) stakeholder email addresses, (ii) line of business identifiers, (iii) jobs to be monitored, (iv) a monitoring range, (v) a pipeline stability threshold, (vi) a test case failure threshold, (vii) quality control login and configuration details, (viii) an automatic trigger time, (ix) an error classification, (x) application and value stream mapping, and (xi) multi-environment configuration information.

“6. The system of claim 1, wherein the generation of the pipeline health check analysis report is performed by a view generator including at least one of: (i) a build level generator, (ii) a line of business level generator, and (iii) an enterprise level generator.

“7. The system of claim 1, wherein the pipeline health check analysis report is transmitted to an automation framework and includes at least one of a self-healing analysis and a recommended corrective action.

“8. The system of claim 1, wherein the predicted future type of failure or the predicted level of stability are based on one or more current applications that are being modified.

“9. The system of claim 1, wherein the pipeline health check analysis report is used to automatically transmit a remote access Application Programming Interface (API) console output to the software continuous integration and/or deployment pipeline.

“10. The system of claim 1, wherein the pipeline health check analysis report includes information about multiple software continuous integration and/or deployment pipelines.

“11. The system of claim 1, wherein the pipeline health check analysis report includes at least one recommended action.

“12. The system of claim 1, wherein the level of stability of the software continuous integration and/or deployment pipeline represents a threshold value that at least one of triggers an alert and adjusts a display of data.

“13. The system of claim 1, wherein the machine learning model is associated with at least one of: (i) artificial intelligence, (ii) supervised learning, (iii) semi-supervised learning, (iv) weakly supervised learning, (v) unsupervised learning, (vi) reinforcement learning, (vii) feature learning, (viii) sparse dictionary learning, (ix) anomaly detection, (x) decision trees, (xi) association rules, (xii) an artificial neural network, (xiii) a support vector machine, (xiv) a Bayesian network, and (xv) a genetic algorithm.

“14. A computerized method to facilitate software development and operations for an enterprise, comprising: listening, by an intelligent software agent platform, to information from a communication input port associated with a software continuous integration and/or deployment pipeline of the enterprise, wherein the intelligent software agent platform is listening for a trigger indication from the software continuous integration and/or deployment pipeline; responsive to the trigger indication, applying system configuration information and rule layer information to extract software log data; applying a machine learning model to the extracted software log data to generate a pipeline health check analysis report, wherein the pipeline health check analysis report includes an automatically generated prediction associated with future operation of the software continuous integration and/or deployment pipeline; and transmitting, via a communication output port coupled to the intelligent software agent platform, the pipeline health check analysis report via a distributed communication network; wherein the pipeline health check analysis report includes: a prediction of a level of stability of the software continuous integration and/or deployment pipeline; a percentage of software builds that have successively passed through the software continuous integration and/or deployment pipeline during a time period; a prediction of future type of failure of the software continuous integration and/or deployment pipeline; and a number of test jobs associated with an application program; and wherein the pipeline health check analysis report comprises an email message transmitted to at least one of: (i) a subject matter expert, (ii) a software development engineer in test, (iii) a software manager, (iv) a quality control member, (v) a quality assurance member, or (vi) any other stakeholder.

“15. The method of claim 14, wherein the software continuous integration and/or deployment pipeline includes at least one of: (i) code and build components, (ii) static code analysis, (iii) deployment, (iv) build completion, (iv) a test trigger, (v) a performance measurement component, and (vi) any of pipeline component.

“16. The method of claim 14, wherein the system configuration information includes at least one of: (i) a pipeline configuration, (ii) a user configuration, and (iii) a log properties configuration.

“17. The method of claim 14, wherein the generation of the pipeline health check analysis report is performed by a view generator including at least one of: (i) a build level generator, (ii) a line of business level generator, and (iii) an enterprise level generator.

“18. A non-transitory, computer-readable medium storing instructions, that, when executed by a processor, cause the processor to perform a method to facilitate software development and operations for an enterprise, the method comprising: listening, by an intelligent software agent platform, to information from a communication input port associated with a software continuous integration and/or deployment pipeline of the enterprise, wherein the intelligent software agent platform is listening for a trigger indication from the software continuous integration and/or deployment pipeline; responsive to the trigger indication, applying system configuration information and rule layer information to extract software log data; applying a machine learning model to the extracted software log data to generate a pipeline health check analysis report, wherein the pipeline health check analysis report includes an automatically generated prediction associated with future operation of the software continuous integration and/or deployment pipeline; and transmitting, via a communication output port coupled to the intelligent software agent platform, the pipeline health check analysis report via a distributed communication network; wherein the pipeline health check analysis report includes: a prediction of a level of stability of the software continuous integration and/or deployment pipeline; a percentage of software builds that have successively passed through the software continuous integration and/or deployment pipeline during a time period; a prediction of a future type of failure of the software continuous integration and/or deployment pipeline; and a number of test jobs associated with an application program; and wherein the pipeline health check analysis report comprises an email message transmitted to at least one of: (i) a subject matter expert, (ii) a software development engineer in test, (iii) a software manager, (iv) a quality control member, (v) a quality assurance member, or (vi) any other stakeholder.”

There are additional claims. Please visit full patent to read further.

URL and more information on this patent, see: Mittal, Sachin. Intelligent software agent to facilitate software development and operations. U.S. Patent Number 11693650, filed September 20, 2022, and published online on July 4, 2023. Patent URL (for desktop use only): https://ppubs.uspto.gov/pubwebapp/external.html?q=(11693650)&db=USPAT&type=ids

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