A Systematic Mapping Study of the Metrics, Uses and Subjects of Diversity‐Based Testing Techniques

• Published in: Software testing, verification & reliability Vol. 35; no. 2
• Main Authors: Elgendy, Islam T., Hierons, Robert M., McMinn, Phil
• Format: Journal Article
• Language: English
• Published: Chichester Wiley Subscription Services, Inc 01.03.2025
• Subjects: Artifact identification; diversity artefacts; diversity‐based testing; diversity‐based tools; fault localization; Mapping; Similarity; similarity metrics; similarity‐based testing; Software testing; test case prioritization; test case selection; test data generation; test suite reduction; Trends
• ISSN: 0960-0833; 1099-1689; 1099-1689
• DOI: 10.1002/stvr.1914

ABSTRACT There has been a significant amount of interest regarding the use of DBTtsfull in software testing over the past two decades. Diversity‐based testing (DBT) technique uses similarity metrics to leverage the dissimilarity between software artefacts—such as requirements, models, programme structures or inputs—in order to address a software testing problem. DBT techniques have been used to assist in finding solutions to several different types of problems including generating test cases, prioritizing them and reducing very large test suites. This paper is a systematic mapping study of DBT techniques that summarizes the key aspects and trends of 167 papers that report the use of 79 different similarity metrics with 22 different types of software artefacts, which have been used by researchers to tackle 11 different types of software testing problems. We further present an analysis of the recent trends in DBT techniques and review the different application domains to which the techniques have been applied, giving an overview of the tools developed by researchers in order to do so. Finally, the paper identifies some DBT challenges that are potential topics for future work, such as exploring other diversity artefacts and measuring diversity for complex data input. This paper is a systematic mapping study of diversity‐based testing (DBT) techniques that summarizes the key aspects and trends of 167 papers. The study reports the use of 79 similarity metrics with 22 types of software artefacts, which researchers have used to tackle 11 types of software testing problems.