September 2022
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32 Reads
Requirements Engineering
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September 2022
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32 Reads
Requirements Engineering
June 2022
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352 Reads
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51 Citations
Requirements Engineering
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.
... These smells can signify ambiguous, incomplete, inconsistent, or overly complex requirements, resulting in increased costs, delays, or defects in the final product [8]. Frattini et al. [9] published a catalog of 206 requirements quality indicators (aka smells) extracted from a systematic mapping study on 105 relevant primary studies [10]. The authors also categorized requirements smells into three categories: (1) lexical smells describe issues in single words or terms, e.g., code = "program source" or "set of rules"?; (2) syntactic smells describe issues in word or sentence structures, e.g., When the system sends a message to the receiver, it shall provide an acknowledgment (it = "system" or "receiver"?); and (3) semantic smells describe issues in interpreting the requirements within its context, e.g., The system shall generate a report at the end of each day, (strictly at midnight or at the end of the business hours?). ...
June 2022
Requirements Engineering