Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Empirical Study of Effectiveness of EvoSuite on the SBST 2020 Tool Competition Benchmark

Full metadata record
DC Field Value Language
dc.contributor.authorHerlim, Robert Sebastian-
dc.contributor.authorHong, Shin-
dc.contributor.authorKim, Yunho-
dc.contributor.authorKim, Moonzoo-
dc.date.accessioned2022-07-06T11:55:21Z-
dc.date.available2022-07-06T11:55:21Z-
dc.date.created2021-12-08-
dc.date.issued2021-10-
dc.identifier.issn0302-9743-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/140668-
dc.description.abstractEvoSuite 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.language영어-
dc.language.isoen-
dc.publisherSpringer Science and Business Media Deutschland GmbH-
dc.titleEmpirical Study of Effectiveness of EvoSuite on the SBST 2020 Tool Competition Benchmark-
dc.typeArticle-
dc.contributor.affiliatedAuthorKim, Yunho-
dc.identifier.doi10.1007/978-3-030-88106-1_9-
dc.identifier.scopusid2-s2.0-85117074873-
dc.identifier.wosid000866469000010-
dc.identifier.bibliographicCitationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v.12914 LNCS, pp.121 - 135-
dc.relation.isPartOfLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)-
dc.citation.titleLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)-
dc.citation.volume12914 LNCS-
dc.citation.startPage121-
dc.citation.endPage135-
dc.type.rimsART-
dc.type.docTypeProceedings Paper-
dc.description.journalClass1-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalWebOfScienceCategoryComputer Science, Software Engineering-
dc.subject.keywordPlusJava programming language-
dc.subject.keywordPlusSoftware testing-
dc.subject.keywordPlusEmpirical studies-
dc.subject.keywordPlusEvosuite-
dc.subject.keywordPlusHigh complexity-
dc.subject.keywordPlusJava program-
dc.subject.keywordPlusObject-oriented program-
dc.subject.keywordPlusSBST tool competition-
dc.subject.keywordPlusSearch-based software testing-
dc.subject.keywordPlusState of the art-
dc.subject.keywordPlusTest-coverage-
dc.subject.keywordPlusTesting tools-
dc.subject.keywordPlusObject oriented programming-
dc.subject.keywordAuthorEmpirical study-
dc.subject.keywordAuthorEvoSuite-
dc.subject.keywordAuthorSBST tool competition-
dc.identifier.urlhttps://link.springer.com/chapter/10.1007/978-3-030-88106-1_9-
Files in This Item
Go to Link
Appears in
Collections
서울 공과대학 > 서울 컴퓨터소프트웨어학부 > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Kim, Yunho photo

Kim, Yunho
COLLEGE OF ENGINEERING (SCHOOL OF COMPUTER SCIENCE)
Read more

Altmetrics

Total Views & Downloads

BROWSE