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Empirical Study of Effectiveness of EvoSuite on the SBST 2020 Tool Competition Benchmark
- Issue Date
- Oct-2021
- Publisher
- Springer Science and Business Media Deutschland GmbH
- Keywords
- Empirical study; EvoSuite; SBST tool competition
- Citation
- Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v.12914 LNCS, pp.121 - 135
- Indexed
- SCOPUS
- Volume
- 12914 LNCS
- Start Page
- 121
- End Page
- 135
- ISSN
- 0302-9743
- Abstract
- EvoSuite is a state-of-the-art search-based software testing tool for Java programs and many researchers have applied EvoSuite to achieve high test coverage. However, due to high complexity of object-oriented programs, EvoSuite still suffers several limitations in terms of test coverage achievement. In this paper, to improve the effectiveness of EvoSuite by analyzing EvoSuite’s limitations, we conducted an empirical study to identify the limitations of EvoSuite on the most recent SBST 2020 Tool Competition benchmark that consists of 70 classes selected from real-world Java projects. We have manually classified the branches of the target programs that EvoSuite could not cover and reported corresponding limitations of EvoSuite with concrete examples.
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Related Researcher
- Kim, Yunho
- COLLEGE OF ENGINEERING (SCHOOL OF COMPUTER SCIENCE)