Empirical Study of Effectiveness of EvoSuite on the SBST 2020 Tool Competition Benchmark
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Herlim, Robert Sebastian | - |
dc.contributor.author | Hong, Shin | - |
dc.contributor.author | Kim, Yunho | - |
dc.contributor.author | Kim, Moonzoo | - |
dc.date.accessioned | 2022-07-06T11:55:21Z | - |
dc.date.available | 2022-07-06T11:55:21Z | - |
dc.date.created | 2021-12-08 | - |
dc.date.issued | 2021-10 | - |
dc.identifier.issn | 0302-9743 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/140668 | - |
dc.description.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. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | Springer Science and Business Media Deutschland GmbH | - |
dc.title | Empirical Study of Effectiveness of EvoSuite on the SBST 2020 Tool Competition Benchmark | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kim, Yunho | - |
dc.identifier.doi | 10.1007/978-3-030-88106-1_9 | - |
dc.identifier.scopusid | 2-s2.0-85117074873 | - |
dc.identifier.wosid | 000866469000010 | - |
dc.identifier.bibliographicCitation | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v.12914 LNCS, pp.121 - 135 | - |
dc.relation.isPartOf | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | - |
dc.citation.title | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | - |
dc.citation.volume | 12914 LNCS | - |
dc.citation.startPage | 121 | - |
dc.citation.endPage | 135 | - |
dc.type.rims | ART | - |
dc.type.docType | Proceedings Paper | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Software Engineering | - |
dc.subject.keywordPlus | Java programming language | - |
dc.subject.keywordPlus | Software testing | - |
dc.subject.keywordPlus | Empirical studies | - |
dc.subject.keywordPlus | Evosuite | - |
dc.subject.keywordPlus | High complexity | - |
dc.subject.keywordPlus | Java program | - |
dc.subject.keywordPlus | Object-oriented program | - |
dc.subject.keywordPlus | SBST tool competition | - |
dc.subject.keywordPlus | Search-based software testing | - |
dc.subject.keywordPlus | State of the art | - |
dc.subject.keywordPlus | Test-coverage | - |
dc.subject.keywordPlus | Testing tools | - |
dc.subject.keywordPlus | Object oriented programming | - |
dc.subject.keywordAuthor | Empirical study | - |
dc.subject.keywordAuthor | EvoSuite | - |
dc.subject.keywordAuthor | SBST tool competition | - |
dc.identifier.url | https://link.springer.com/chapter/10.1007/978-3-030-88106-1_9 | - |
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