A proposal and assessment of an improved heuristic for the Eager Test smell detection

The evidence for the prevalence of test smells at the unit testing level has relied on the accuracy of detection tools, which have seen intense research in the last two decades. The Eager Test smell, one of the most prevalent, is often identified using simplified detection rules that practitioners find inadequate. We aim to improve the rules for detecting the Eager Test smell. We reviewed the literature on test smells to analyze the definitions and detection rules of the Eager Test smell. We proposed a novel, unambiguous definition of the test smell and a heuristic to address the limitations of the existing rules. We evaluated our heuristic against existing detection rules by manually applying it to 300 unit test cases in Java. Our review identified 56 relevant studies. We found that inadequate interpretations of original definitions of the Eager Test smell led to imprecise detection rules, resulting in a high level of disagreement in detection outcomes. Also, our heuristic detected patterns of eager and non-eager tests that existing rules missed. Our heuristic captures the essence of the Eager Test smell more precisely; hence, it may address practitioners’ concerns regarding the adequacy of existing detection rules. • An overview of the definitions and detection rules of the Eager Test smell. • A novel, unambiguous definition of Eager Test based on the original definitions. • A novel heuristic with pseudocode for detecting eager tests. • The identification of common patterns of eager tests and non-eager tests.

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Publication Details

Journal
Journal of Systems and Software
Published
2025-03-24
DOI
https://doi.org/10.1016/j.jss.2025.112438
Citations
2
Primary Topic
Software Testing and Debugging Techniques
Type
article
Field-Weighted Citation Impact
4.62
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article

A proposal and assessment of an improved heuristic for the Eager Test smell detection

Huynh Khanh Vi Tran, Nauman bin Ali, Jürgen Börstler, Michael Unterkalmsteiner
2 citations
Journal of Systems and Software
Software Testing and Debugging Techniques
4.62
article

A proposal and assessment of an improved heuristic for the Eager Test smell detection

Huynh Khanh Vi Tran, Nauman bin Ali, Jürgen Börstler, Michael Unterkalmsteiner
article en
2 citations

Abstract

The evidence for the prevalence of test smells at the unit testing level has relied on the accuracy of detection tools, which have seen intense research in the last two decades. The Eager Test smell, one of the most prevalent, is often identified using simplified detection rules that practitioners find inadequate. We aim to improve the rules for detecting the Eager Test smell. We reviewed the literature on test smells to analyze the definitions and detection rules of the Eager Test smell. We proposed a novel, unambiguous definition of the test smell and a heuristic to address the limitations of the existing rules. We evaluated our heuristic against existing detection rules by manually applying it to 300 unit test cases in Java. Our review identified 56 relevant studies. We found that inadequate interpretations of original definitions of the Eager Test smell led to imprecise detection rules, resulting in a high level of disagreement in detection outcomes. Also, our heuristic detected patterns of eager and non-eager tests that existing rules missed. Our heuristic captures the essence of the Eager Test smell more precisely; hence, it may address practitioners’ concerns regarding the adequacy of existing detection rules. • An overview of the definitions and detection rules of the Eager Test smell. • A novel, unambiguous definition of Eager Test based on the original definitions. • A novel heuristic with pseudocode for detecting eager tests. • The identification of common patterns of eager tests and non-eager tests.

Journal of Systems and SoftwareVol. 226
Blekinge Institute of Technology (SE)
Openalex Percentile: Top 7%
Software Testing and Debugging Techniques
4.62
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A proposal and assessment of an improved heuristic for the Eager Test smell detection — Huynh Khanh Vi Tran, Nauman bin Ali, et al. · Journal of Systems and Software (2025) | TGRS Research Map | TGRS