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Understanding Test-Artifact Quality in Software EngineeringTran, Huynh Khanh Vi January 2022 (has links)
Context: The core of software testing is test artifacts, i.e., test cases, test suites, test scripts, test code, test specifications, and natural language tests. Hence, the quality of test artifacts can negatively or positively impact the reliability of the software testing process. Several empirical studies and secondary studies have investigated the test artifact quality. Nevertheless, little is known about how practitioners by themselves perceive test artifact quality, and the evidence on test artifact quality in the literature has not been synthesized in one place. Objective: This thesis aims to identify and synthesize the knowledge in test artifact quality from both academia and industry. Hence, our objectives are: (1) To understand practitioners’ perspectives on test artifact quality, (2) To investigate how test artifact quality has been characterized in the literature, (3) To increase the reliability of the research method for conducting systematic literature reviews (SLR) in software engineering. Method: In this thesis, we conducted an interview-based exploratory study and a tertiary study to achieve the first two objectives. We used the tertiary study as a case and referred to related observations from other researchers to achieve the last objective. Results: We provided two quality models based on the findings of the interview-based and tertiary studies. The two models were synthesized and combined to provide a broader view of test artifact quality. Also, the context information that can be used to characterize the environment in which test artifact quality is investigated was aggregated based on these studies’ findings. Based on our experience in constructing and validating automated search results using a quality gold standard (QGS) in the tertiary study, we provided recommendations for the QGS construction and proposed an extension to the current search validation approach. Conclusions: The context information and the combined quality model provide a comprehensive view of test artifact quality. Researchers can use the quality model to develop guidelines, templates for designing new test artifacts, or assessment tools for evaluating existing test artifacts. The model also can serve as a guideline for practitioners to search for test-artifact quality information, i.e., definitions for the quality attributes and measurements. For future work, we aim at investigating how to improve relevant test artifact quality attributes that are challenging to deal with.
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