Authors:
Olivia Rodríguez-Valdés
1
;
Domenico Amalfitano
2
;
Otto Sybrandi
3
;
Beatriz Marín
4
and
Tanja Vos
4
;
1
Affiliations:
1
Open Universiteit, Heerlen, The Netherlands
;
2
University of Naples Federico II, Naples, Italy
;
3
Marviq, The Netherlands
;
4
Universitat Politècnica de València, València, Spain
Keyword(s):
Code Smells, Random Testing, Scriptless Testing, GUI Testing, Testing Adequacy Criteria.
Abstract:
This paper presents an industrial experience applying random scriptless GUI testing to the Yoho web application developed by Marviq. The study was motivated by several key challenges faced by the company, including the need to optimise testing resources, explore how random testing can complement manual testing, and investigate new coverage metrics, such as “code smell coverage”, to assess software quality and maintainability. We conducted an experiment to explore the impact of the number and length of random GUI test sequences on traditional adequacy metrics, the complementarity of random with manual testing, and the relationship between code smell coverage and traditional code coverage. Using Testar for scriptless testing and SonarQube code smell identification, results show that longer random test sequences yielded better test adequacy metrics and increased code smell coverage. In addition, random testing offers promising efficiency in test coverage and detects unique smells that m
anual testing might overlook. Additionally, including code smell coverage provides valuable insights into long-term code maintainability, revealing gaps that traditional metrics may not capture. These findings highlight the benefits of combining functional testing with metrics assessing code quality, particularly in resource-constrained environments.
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