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ThinkMind // ICSEA 2019, The Fourteenth International Conference on Software Engineering Advances // View article icsea_2019_1_10_10093


An Empirical Study of Mutation-Based Test Case Clustering Prioritization and Reduction Technique

Authors:
Longbo Li
Yanhui Zhou
Yong Yu
Feiyan Zhao
Shenghua Wu
Zhe Yang

Keywords: test case prioritization; regression test; clustering algorithms

Abstract:
Regression testing is an important activity to ensure software quality throughout the software life-cycle. However,due to the expansion of the software scale, a large number oftest cases are generated in the regression test. In the actual regression test process, it is impossible for us to execute all the test cases. In order to save time and improve efficiency, we need to prioritize and reduce the test cases. In this paper, we propose a new concept mutation program unit priority that works well in the prioritization and reduction of test cases. To evaluate our approach, we designed the experiment and validated it using the Defects4J data set, which contains the real fault programs. We experimented with 350 real faults and 550254 developer-written test cases for Defects4J. The average reduction rate for test cases is 40%, and the fault detection capability is only reduced by 1.38%. The results show that the mutation-based test case prioritization and reduction method improves the effectiveness of test case prioritization and reduction technique.

Pages: 1 to 6

Copyright: Copyright (c) IARIA, 2019

Publication date: November 24, 2019

Published in: conference

ISSN: 2308-4235

ISBN: 978-1-61208-752-8

Location: Valencia, Spain

Dates: from November 24, 2019 to November 28, 2019

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