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AssigneeInternational Business Machines Corporation
InventorsAlexander Sobran, Yogesh Rane, Bo Zhang, Guilherme Ferreira
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Approaches presented herein enable domain knowledge-based software defect prediction. More specifically, a cost function configured to train a machine learning model to predict a defect in a software version is obtained. A domain knowledge penalty metric is then determined for a software development team associated with the software version. A linear combination of the determined domain knowledge penalty metric is then applied to the obtained cost function to create a domain knowledge-modified cost function. Using this domain knowledge-modified cost function, the machine learning model is then trained based on a minimization of the domain knowledge-modified cost function. Once trained, the machine learning model is used to report a set of predicted values based on the domain knowledge-modified cost function trained machine learning model.
A method for domain knowledge-based software defect prediction, the method comprising:
A computer system for domain knowledge-based software defect prediction, the computer system comprising:
A computer program product for domain knowledge-based software defect prediction, the computer program product comprising a computer readable hardware storage device, and program instructions stored on the computer readable hardware storage device, to:
Dependencies are inferred from the claim text.