Optum, Inc.

Atul B Subhash

Pawan Sharma

Kumar Shailendra

Veera Raghavendra Chikka

Swaroop S Shekar

Vaishnavi K B

Sukant Arora

Vamsi M Bhandaru

Various embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for performing digital image processing operations. For example, as described herein, various embodiments of the present invention relate to performing digital image processing operations using at least one of using bounding box precision models to generate an optimal object differentiation kernel, using an optimal object differentiation kernel to generate/detect optimal bounding boxes of an image set, and using an image classification machine learning model to generate bounding box classifications for the optimal bounding boxes of an image set.

Digital image processing techniques using bounding box precision models

Various embodiments are directed to performing automated software testing configuration management operations. In one embodiment, a method is provided. The method includes generating a graph data structure including nodes representing test steps across test cases of a software testing data object for a software application platform and including segments each connecting two nodes and representing test cases having the two represented test steps. The method further includes receiving a query describing a testing change and generating extracted features from the query. The method further includes generating test outcome requirements and graph portions of the graph data structure relevant to the testing change using supervised machine learning models and the extracted features. The method further includes generating, in response to the query, an updated graph data structure and a change report indicating the relevant test outcome requirements and performing prediction-based actions using the updated graph data structure and the change report.

Machine learning techniques for automated software testing configuration management

Methods, apparatuses, systems, computing devices, computing entities, and/or the like are provided. An example method may include receiving a requirement request data object, generating at least one of a predicted complexity attribute or a predicted work track attribute corresponding to the requirement request data object, generating at least one predicted defect description attribute or at least one predicted test case description attribute corresponding to the requirement request data object, and transmitting a prediction data object that includes at least one of the predicted complexity attribute, the predicted work track attribute, the at least one predicted defect description attribute, or the at least one predicted test case description attribute. In some examples, the client device is configured to perform one or more software testing operations corresponding to the software testing task based at least in part on the prediction data object.

Method, apparatus and computer program product for predictive configuration management of a software testing system

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Bengaluru, India

Atul B Subhash