Deep Q-network reinforcement learning for testing case selection and prioritization

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United States of America Patent

PATENT NO 11249887
APP PUB NO 20210064515A1
SERIAL NO

16998224

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Systems and methods for automated software test design and implementation. The system and method being able to establish an initial pool of test cases for testing computer code; apply the initial pool of test cases to the computer code in a testing environment to generate test results; preprocess the test results into a predetermined format; extract metadata from the test results; generate a training sequence; calculate a reward value for the pool of test cases; input the training sequence and reward value into a reinforcement learning agent; utilizing the value output from the reinforcement learning agent to produce a ranking list; prioritizing the initial pool of test cases and one or more new test cases based on the ranking list; and applying the prioritized initial pool of test cases and one or more new test cases to the computer code in a testing environment to generate test results.

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Patent Owner(s)

  • NEC CORPORATION

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Inventor(s)

Inventor Name Address # of filed Patents Total Citations
Bian, Yuchen Santa Clara, US 3 6
Chen, Haifeng West Windsor, US 303 1456
Xu, Jianwu Titusville, US 38 256

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