Smells in Software Test Code: a Survey of Knowledge in Industry and Academia

dc.authorid Garousi, Vahid/0000-0001-6590-7576
dc.authorscopusid 13408954200
dc.authorscopusid 57200086287
dc.contributor.author Garousi, Vahid
dc.contributor.author Kucuk, Baris
dc.contributor.other Software Engineering
dc.date.accessioned 2024-07-05T15:27:31Z
dc.date.available 2024-07-05T15:27:31Z
dc.date.issued 2018
dc.department Atılım University en_US
dc.department-temp [Garousi, Vahid] Wageningen Univ, Informat Technol Grp, Wageningen, Netherlands; [Kucuk, Baris] Atilim Univ, Dept Comp Engn, Ankara, Turkey; [Kucuk, Baris] Atilim Univ, Dept Software Engn, Ankara, Turkey en_US
dc.description Garousi, Vahid/0000-0001-6590-7576 en_US
dc.description.abstract As a type of anti-pattern, test smells are defined as poorly designed tests and their presence may negatively affect the quality of test suites and production code. Test smells are the subject of active discussions among practitioners and researchers, and various guidelines to handle smells are constantly offered for smell prevention, smell detection, and smell correction. Since there is a vast grey literature as well as a large body of research studies in this domain, it is not practical for practitioners and researchers to locate and synthesize such a large literature. Motivated by the above need and to find out what we, as the community, know about smells in test code, we conducted a 'multivocal' literature mapping (classification) on both the scientific literature and also practitioners' grey literature. By surveying all the sources on test smells in both industry (120 sources) and academia (46 sources), 166 sources in total, our review presents the largest catalogue of test smells, along with the summary of guidelines/techniques and the tools to deal with those smells. This article aims to benefit the readers (both practitioners and researchers) by serving as an "index" to the vast body of knowledge in this important area, and by helping them develop high-quality test scripts, and minimize occurrences of test smells and their negative consequences in large test automation projects. (C) 2017 Elsevier Inc. All rights reserved. en_US
dc.identifier.citationcount 84
dc.identifier.doi 10.1016/j.jss.2017.12.013
dc.identifier.endpage 81 en_US
dc.identifier.issn 0164-1212
dc.identifier.issn 1873-1228
dc.identifier.scopus 2-s2.0-85039428979
dc.identifier.startpage 52 en_US
dc.identifier.uri https://doi.org/10.1016/j.jss.2017.12.013
dc.identifier.uri https://hdl.handle.net/20.500.14411/2681
dc.identifier.volume 138 en_US
dc.identifier.wos WOS:000426233300004
dc.identifier.wosquality Q2
dc.institutionauthor Garousi, Vahid
dc.institutionauthor Küçük, Barış
dc.language.iso en en_US
dc.publisher Elsevier Science inc en_US
dc.relation.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.scopus.citedbyCount 132
dc.subject Software testing en_US
dc.subject Automated testing en_US
dc.subject Test automation en_US
dc.subject Test scripts en_US
dc.subject Test smells en_US
dc.subject Test anti-patterns en_US
dc.subject Multivocal literature mapping en_US
dc.subject Survey en_US
dc.subject Systematic mapping en_US
dc.title Smells in Software Test Code: a Survey of Knowledge in Industry and Academia en_US
dc.type Article en_US
dc.wos.citedbyCount 105
dspace.entity.type Publication
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