Proceedings of the 3rd International Conference on Management Science and Software Engineering (ICMSSE 2023)

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An Improved Method for Test Case Prioritization in Continuous Integration based on Reinforcement Learning

Authors
Yanan Han1, *, Gang Chen1, Bin Han2
1School of Information Management and Engineering, Shanghai University of Finance and Economics, Yangpu District, No. 777 Guoding Road, Shanghai, 200433, China
2School of Materials Science and Engineering, China University of Petroleum (East China), No. 66 Changjiang West Road, Huangdao, Qingdao, Shandong, 266580, China
*Corresponding author. Email: hanyanan@163.sufe.edu.cn
Corresponding Author
Yanan Han
Available Online 9 October 2023.
DOI
10.2991/978-94-6463-262-0_99How to use a DOI?
Keywords
test case prioritization; continuous integration; reinforcement learning; additional rewards for new test cases
Abstract

The iterative update of software leads to frequent continuous integration, so the testing in the continuous integration environment should also be fast and accurate. Reinforcement learning is often used in the research of continuous integration testing because of its sequential strategy and good robustness. Some existing methods use reinforcement learning to solve test case prioritization problem, which provides a good idea, but the experimental defect detection rates are relatively low. Therefore, based on the existing reinforcement learning framework, this article proposes a reward mechanism to provide additional rewards for newly emerging test cases in each integration cycle. Through experiments on three industrial datasets, it has been proven that this mechanism improves the defect detection rate, the recall rate of failed test cases, and the efficiency of test feedback in the testing process.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 3rd International Conference on Management Science and Software Engineering (ICMSSE 2023)
Series
Atlantis Highlights in Engineering
Publication Date
9 October 2023
ISBN
978-94-6463-262-0
ISSN
2589-4943
DOI
10.2991/978-94-6463-262-0_99How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Yanan Han
AU  - Gang Chen
AU  - Bin Han
PY  - 2023
DA  - 2023/10/09
TI  - An Improved Method for Test Case Prioritization in Continuous Integration based on Reinforcement Learning
BT  - Proceedings of the 3rd International Conference on Management Science and Software Engineering (ICMSSE 2023)
PB  - Atlantis Press
SP  - 958
EP  - 972
SN  - 2589-4943
UR  - https://doi.org/10.2991/978-94-6463-262-0_99
DO  - 10.2991/978-94-6463-262-0_99
ID  - Han2023
ER  -