Empirical Research on Requirements Quality: A Systematic Mapping Study - Dataset

We conducted a systematic mapping study on the empirical research into the quality of requirements titled "Empirical Research on Requirements Quality: A SystematicMapping Study" in the Requirements Engineering Journal. This is our replication package.

Full Abstract:

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 6,905 articles from six academic databases, which we filtered down to our 105 relevant primary studies: explicitly defining, improving, or evaluating quality attributes while including an empirical research component. We found that 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. We present and discuss our detailed analysis along the various quality attributes. Our findings highlightthe need to conduct more grounded research aimed at “definitions,” to use more diverse research methods, and to address a more diverse set of requirements types.