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Quality assurance is the overarching term used to describe the activities employed to ensure the proper performance of a system. These activities can be classified into three categories: quality control, quality assessment, and internal corrective measures. Typically, these activities work cyclically: quality control is performed before and during the analysis, while quality assessment occurs during and after the investigation. Internal corrective measures are implemented based on the findings...
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Empirical research on requirements quality: a systematic mapping study.

Lloyd Montgomery1, Davide Fucci2, Abir Bouraffa1

  • 1University of Hamburg, Hamburg, Germany.

Requirements Engineering
|May 23, 2022
PubMed
Summary
This summary is machine-generated.

This study maps research on requirements quality, finding most work focuses on improvement techniques, not definitions. Key quality attributes like ambiguity and completeness are prominent, but research needs broader methods and focus on specific requirement types.

Keywords:
Empirical researchRequirements qualitySecondary studySystematic mapping study

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Area of Science:

  • Software Engineering
  • Requirements Engineering

Background:

  • High-quality requirements are crucial for project success.
  • Existing research on requirements quality is extensive but lacks a comparative overview of specific quality attributes.

Purpose of the Study:

  • To systematically map and compare concrete quality attributes addressed in requirements engineering research.
  • To identify knowledge gaps in the empirical study of requirements quality.

Main Methods:

  • Conducted a systematic mapping study of scientific literature.
  • Retrieved 6905 articles from six databases, filtering down to 105 primary empirical studies.
  • Analyzed studies focusing on defining, improving, or evaluating requirements quality.

Main Results:

  • Empirical research predominantly focuses on improvement techniques, with limited studies on evidence-based definitions and evaluations of quality attributes.
  • The most prominent quality attributes identified are ambiguity, completeness, consistency, and correctness.
  • 111 sub-types of quality attributes were identified, with ambiguity having the largest share; research primarily targets 'requirements' broadly, not specific types like user stories.

Conclusions:

  • There is a need for more empirically grounded research defining requirements quality.
  • Future research should employ more diverse research methods and address a wider range of requirements types.