Header

UZH-Logo

Maintenance Infos

Investigating Severity Thresholds for Test Smells


Spadini, Davide; Schvarcbacher, Martin; Oprescu, Ana-Maria; Bruntink, Magiel; Bacchelli, Alberto (2020). Investigating Severity Thresholds for Test Smells. In: MSR '20: 17th International Conference on Mining Software Repositories, Seoul Republic of Korea, 29 July 2020 - 30 July 2020. ACM, 311-321.

Abstract

Test smells are poor design decisions implemented in test code, which can have an impact on the effectiveness and maintainability of unit tests. Even though test smell detection tools exist, how to rank the severity of the detected smells is an open research topic. In this work, we aim at investigating the severity rating for four test smells and investigate their perceived impact on test suite maintainability by the developers. To accomplish this, we first analyzed some 1,500 open-source projects to elicit severity thresholds for commonly found test smells. Then, we conducted a study with developers to evaluate our thresholds. We found that (1) current detection rules for certain test smells are considered as too strict by the developers and (2) our newly defined severity thresholds are in line with the participants' perception of how test smells have an impact on the maintainability of a test suite. Preprint [https://doi.org/10.5281/zenodo.3744281], data and material [https://doi.org/10.5281/zenodo.3611111].

Abstract

Test smells are poor design decisions implemented in test code, which can have an impact on the effectiveness and maintainability of unit tests. Even though test smell detection tools exist, how to rank the severity of the detected smells is an open research topic. In this work, we aim at investigating the severity rating for four test smells and investigate their perceived impact on test suite maintainability by the developers. To accomplish this, we first analyzed some 1,500 open-source projects to elicit severity thresholds for commonly found test smells. Then, we conducted a study with developers to evaluate our thresholds. We found that (1) current detection rules for certain test smells are considered as too strict by the developers and (2) our newly defined severity thresholds are in line with the participants' perception of how test smells have an impact on the maintainability of a test suite. Preprint [https://doi.org/10.5281/zenodo.3744281], data and material [https://doi.org/10.5281/zenodo.3611111].

Statistics

Citations

Dimensions.ai Metrics
15 citations in Web of Science®
33 citations in Scopus®
Google Scholar™

Altmetrics

Downloads

69 downloads since deposited on 15 Dec 2020
8 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
Dewey Decimal Classification:000 Computer science, knowledge & systems
Scopus Subject Areas:Physical Sciences > Computer Science Applications
Physical Sciences > Software
Language:English
Event End Date:30 July 2020
Deposited On:15 Dec 2020 12:16
Last Modified:27 Jan 2022 03:39
Publisher:ACM
ISBN:9781450375177
OA Status:Hybrid
Publisher DOI:https://doi.org/10.1145/3379597.3387453
Other Identification Number:merlin-id:20223
  • Content: Published Version