Invention Grant
- Patent Title: Machine learning based ranking of test cases for software development
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Application No.: US15710127Application Date: 2017-09-20
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Publication No.: US10474562B2Publication Date: 2019-11-12
- Inventor: J. Justin Donaldson , Benjamin Busjaeger , Siddharth Rajaram , Berk Coker , Hormoz Tarevern
- Applicant: salesforce.com, inc.
- Applicant Address: US CA San Francisco
- Assignee: salesforce.com
- Current Assignee: salesforce.com
- Current Assignee Address: US CA San Francisco
- Agency: Fenwick & West LLP
- Main IPC: G06F11/36
- IPC: G06F11/36 ; G06N3/08 ; G06F8/71 ; G06F16/13

Abstract:
An online system ranks test cases run in connection with check-in of sets of software files in a software repository. The online system ranks the test cases higher if they are more likely to fail as a result of defects in the set of files being checked in. Accordingly, the online system informs software developers of potential defects in the files being checked in early without having to run the complete suite of test cases. The online system determines a vector representation of the files and test cases based on a neural network. The online system determines an aggregate vector representation of the set of files. The online system determines a measure of similarity between the test cases and the aggregate vector representation of the set of files. The online system ranks the test cases based on the measures of similarity of the test cases.
Public/Granted literature
- US20190087311A1 MACHINE LEARNING BASED RANKING OF TEST CASES FOR SOFTWARE DEVELOPMENT Public/Granted day:2019-03-21
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