xNose: A Test Smell Detector for C#

Test smells, similar to code smells, can negatively impact both the test code and the production code being tested. Despite extensive research on test smells in languages like Java, Scala, and Python, automated tools for detecting test smells in C# are lacking. This paper aims to bridge this gap by...

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Bibliographic Details
Published in:	arXiv.org
Main Authors:	Paul, Partha P, Akanda, Md Tonoy, Ullah, M Raihan, Mondal, Dipto, Chowdhury, Nazia S, Tawsif, Fazle M
Format:	Paper
Language:	English
Published:	Ithaca Cornell University Library, arXiv.org 07.05.2024
Subjects:	Empirical analysis Python Software testing Source code
ISSN:	2331-8422
Online Access:	Get full text
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Summary:	Test smells, similar to code smells, can negatively impact both the test code and the production code being tested. Despite extensive research on test smells in languages like Java, Scala, and Python, automated tools for detecting test smells in C# are lacking. This paper aims to bridge this gap by extending the study of test smells to C#, and developing a tool (xNose) to identify test smells in this language and analyze their distribution across projects. We identified 16 test smells from prior studies that were language-independent and had equivalent features in C# and evaluated xNose, achieving a precision score of 96.97% and a recall score of 96.03%. In addition, we conducted an empirical study to determine the prevalence of test smells in xUnit-based C# projects. This analysis sheds light on the frequency and distribution of test smells, deepening our understanding of their impact on C# projects and test suites. The development of xNose and our analysis of test smells in C# code aim to assist developers in maintaining code quality by addressing potential issues early in the development process.
Bibliography:	SourceType-Working Papers-1 ObjectType-Working Paper/Pre-Print-1 content type line 50
ISSN:	2331-8422
DOI:	10.48550/arxiv.2405.04063