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An initial investigation of the effect of quality factors on Agile test case quality through experts’ review.
- Source :
- Cogent Engineering; 2022, Vol. 9 Issue 1, p1-25, 25p
- Publication Year :
- 2022
-
Abstract
- A test case is a cornerstone of the testing process; hence, it is quintessential to ensure the quality of the test cases. However, test case design in the Agile testing process has limitations that affect its quality standards, leading to the failure of many software projects. Previous studies are limited in providing a clear guideline for assessing the test case quality. However, evaluating the quality of test cases will help software testing practitioners to understand some critical issues in designing test cases from various perspectives. Therefore, this paper aims to present the verified factors and criteria of test case quality by software testing experts in an Agile environment. The proposed factors and criteria were verified through expert review techniques, which included an online survey of professionals and those in domain and knowledge experts. Twenty-three industry practitioners, including developers, testers, and systems analysts, were used to identify the domain experts. In contrast, the knowledge experts were drawn from 13 academic areas of software engineering and testing. The results showed that the quality of test cases is paramount in Agile projects; therefore, the experts accept seven factors and 32 criteria with a few mod- ifications and suggestions. The finding may assist the researchers in improving the proposed factors and criteria for validation purposes. Hence, may contribute to soft- ware testing practitioners as a guideline in constructing, designing, and assessing compelling test cases. Most significantly, the fixed factors and criteria may contribute to the body of knowledge in the software testing domain and industries. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 23311916
- Volume :
- 9
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- Cogent Engineering
- Publication Type :
- Academic Journal
- Accession number :
- 161674942
- Full Text :
- https://doi.org/10.1080/23311916.2022.2082121