Test Set Optimization in Continuous Integration: A Systematic Literature Review
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National Natural Science Foundation of China (61432001, 61602450)

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    Abstract:

    Currently, many software applications are rapidly developed and deployed. Rapid iterations are used to implement new requirements while keeping high quality. Continuous integration (CI) is an important activity to make it work. CI tests the code automatically before it will be integrated into the master branch to ensure its quality. The big challenge is how to select an appropriate test case set for continuous integration. Running all test cases will consume a large amount of resource and get feedback in a long cycle, but selecting an improper test case subset will lose some required test, and therefore increase quality risk. The goal of test set optimization is to select an appropriate test case subset which can satisfy the test requirement for each unit or iteration test while reducing the test resource as much as possible. In this paper, a systematic literature review is performed to reveal the current status of CI-test set optimization based on existing literature. More specifically, the related studies published between 2007 and 2017 from four databases of electronic literature are searched to finally select 39 important studies for careful review. Five research questions are presented in order to achieve the above goal, and data from the selected studies are extracted to analyze and answer the questions. The analysis results contribute some useful findings and new challenges for researches and practitioners.

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李英玲,王青.持续集成测试用例集优化综述研究.软件学报,2018,29(10):3021-3050

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History
  • Received:January 11,2018
  • Revised:May 01,2018
  • Adopted:
  • Online: October 12,2018
  • Published:
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