Fmr Corp.

Aravind Arumugham

Sancho Chittillappily Sebastine

Krishnaraj Sooji

Natalia Potochniak

Cameron Keith

Maureen Olejarz

Shubham Dhanuka

Amit Mawkin

Peter Davies

Xinxing Zeng

Dilip Kumar Raghupatruni

Robert Rosum

Venkatesh Yerramsetty

Narasimha Mannepalli

Ashok Rajashekarappa

Systems and methods for implementing impact-centric source code testing based on historical execution analysis. The method includes receiving a source code file including modified classes and unmodified classes. The method also includes storing class names corresponding to the modified classes in a database. The method further includes determining impacted classes in the source code file based on the class names corresponding to the modified classes. The method also includes, for each of the impacted classes in the source code file, identifying at least one test. The method further includes, for each of the impacted classes in the source code file, initiating the at least one test for the impacted class. The method also includes generating a data log including results generated by the at least one test for each of the impacted classes.

Systems and methods for impact-centric source code testing based on historical execution analysis

Methods and apparatuses for automated software container rehydration and deployment include a server that updates a container image for a software application by modifying layers of the container image and deploying the updated container image as a first container in a passive production environment. For a plurality of traffic volumes, the server: a) increases application traffic directed to the first container to a first traffic volume, b) monitors service level indicators associated with performance of the first container, c) increases the application traffic directed to the first container to a higher traffic volume upon determining that the service level indicators are within a performance threshold, and d) repeats steps b) and c) until the application traffic is increased to a highest traffic volume and the service level indicators are within the performance threshold. The server deploys the updated container image as a second container in an active production environment.

Automated software container rehydration and deployment

Methods and apparatuses are described for assessing and auditing release readiness for a software application. A server receives identification of a software application to be deployed to a production computing environment. The server determines technical attributes of the identified software application from application lifecycle management tools. The server selects one or more release readiness assessment criteria corresponding to the identified software application. The server applies the technical attributes of the identified software application to the release readiness assessment criteria to generate a release readiness score for the software application. The server deploys the identified software application to the production computing environment when the release readiness score is at or above a predetermined threshold. The server prevents deployment of the identified software application to the production computing environment when the release readiness score is below the predetermined threshold.

Assessing and auditing release readiness for a software application

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Chennai, India

Aravind Arumugham