Empirical research on requirements quality: a systematic mapping studyShow others and affiliations
2022 (English)In: Requirements Engineering, ISSN 0947-3602, E-ISSN 1432-010X, Vol. 27, no 2, p. 183-209Article in journal (Refereed) Published
Abstract [en]
Research has repeatedly shown that high-quality requirements are essential for the success of development projects. While the term “quality” is pervasive in the field of requirements engineering and while the body of research on requirements quality is large, there is no meta-study of the field that overviews and compares the concrete quality attributes addressed by the community. To fill this knowledge gap, we conducted a systematic mapping study of the scientific literature. We retrieved 6905 articles from six academic databases, which we filtered down to 105 relevant primary studies. The primary studies use empirical research to explicitly define, improve, or evaluate requirements quality. We found that empirical research on requirements quality focuses on improvement techniques, with very few primary studies addressing evidence-based definitions and evaluations of quality attributes. Among the 12 quality attributes identified, the most prominent in the field are ambiguity, completeness, consistency, and correctness. We identified 111 sub-types of quality attributes such as “template conformance” for consistency or “passive voice” for ambiguity. Ambiguity has the largest share of these sub-types. The artefacts being studied are mostly referred to in the broadest sense as “requirements”, while little research targets quality attributes in specific types of requirements such as use cases or user stories. Our findings highlight the need to conduct more empirically grounded research defining requirements quality, using more varied research methods, and addressing a more diverse set of requirements types. © 2022, The Author(s).
Place, publisher, year, edition, pages
Springer, 2022. Vol. 27, no 2, p. 183-209
Keywords [en]
Empirical research, Requirements quality, Secondary study, Systematic mapping study, Mapping, Quality control, Development programmes, High quality, Meta-study, Quality attributes, Quality requirements, Requirement engineering, Requirement quality, Systematic mapping studies, Requirements engineering
National Category
Software Engineering
Identifiers
URN: urn:nbn:se:bth-22672DOI: 10.1007/s00766-021-00367-zISI: 000755402900001Scopus ID: 2-s2.0-85124746279OAI: oai:DiVA.org:bth-22672DiVA, id: diva2:1640664
Part of project
SERT- Software Engineering ReThought, Knowledge Foundation
Funder
EU, Horizon 2020, 732463Knowledge Foundation, 20180010
Note
open access
A correction to this paper has been published:
https://doi.org/10.1007/s00766-022-00378-4
2022-02-252022-02-252023-05-29Bibliographically approved