Abstract
This paper analyzes quality issues from three software testing glossaries used in academia and industry. The quality issues we analyzed primarily deal with a sub-characteristic of information quality such as consistency, which includes syntactic and semantic consistency. To conduct the study for the testing domain, eight terminological categories were conceived, in which, for each candidate glossary, a corresponding term is included in a category, considering the semantics intended by the authors of these standards. To count the occurrence frequency of a term in the glossaries, a tool was built that also takes into account the matching of synonyms. Then, a consistency analysis was performed for all terms ending with the word “testing”. This study identifies some inconsistencies that merit further attention and efforts to promote agreement and harmonization among the authors/editors of these three glossaries in order to provide their readers with the most consistent and easiest way to learn and understand software testing concepts.
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Acknowledgments
This line of research is supported partially by the Engineering School at UNLPam, Argentina, in the project coded 09/F079.
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Olsina, L., Lew, P., Tebes, G. (2022). Analyzing Quality Issues from Software Testing Glossaries Used in Academia and Industry. In: Vallecillo, A., Visser, J., Pérez-Castillo, R. (eds) Quality of Information and Communications Technology. QUATIC 2022. Communications in Computer and Information Science, vol 1621. Springer, Cham. https://doi.org/10.1007/978-3-031-14179-9_10
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DOI: https://doi.org/10.1007/978-3-031-14179-9_10
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