Garousi, Vahid

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https://hdl.handle.net/20.500.14411/8468
Name Variants
Garousi-Yusifoglu, Vahid
G.,Vahid
G., Vahid
Garousi, Vahid
V.,Garousi
V., Garousi
Garousi,V.
Vahid, Garousi
Yusifoglu, Vahid Garousi
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Doçent Doktor
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Main Affiliation
Software Engineering
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Former Staff
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Scopus Author ID
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WoS Researcher ID

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Scholarly Output

13

Articles

9

Views / Downloads

1/0

Supervised MSc Theses

0

Supervised PhD Theses

0

WoS Citation Count

611

Scopus Citation Count

788

WoS h-index

10

Scopus h-index

11

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0

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0

WoS Citations per Publication

47.00

Scopus Citations per Publication

60.62

Open Access Source

3

Supervised Theses

0

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JournalCount
Journal of Systems and Software4
Information and Software Technology3
ACM International Conference Proceeding Series -- 2014 International Conference on Software and Systems Process, ICSSP 2014 -- 26 May 2014 through 28 May 2014 -- Nanjing -- 1056081
CEUR Workshop Proceedings -- 9th Turkish National Software Engineering Symposium, UYMS 2015 -- 9 September 2015 through 11 September 2015 -- Izmir -- 1176651
17th International Conference on Evaluation and Assessment in software Engineering -- APR 14-16, 2013 -- Porto de Galinhas, BRAZIL1
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Author: Garousi, VahidSubject: Multivocal literature mapping

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    Article
    Citation - WoS: 116
    Citation - Scopus: 144
    Smells in Software Test Code: a Survey of Knowledge in Industry and Academia
    (Elsevier Science inc, 2018) Garousi, Vahid; Kucuk, Baris
    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.