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A Complexity Measure for Textual Requirements

Antinyan, Vard, 1984 (author)
Gothenburg University,Göteborgs universitet,Institutionen för data- och informationsteknik (GU),Department of Computer Science and Engineering (GU),Computer Science and Engineering, University of Gothenburg, Gothenburg, Sweden / Computer Science and Engineering, Chalmers, Gothenburg, Sweden
Staron, Miroslaw, 1977 (author)
Gothenburg University,Göteborgs universitet,Institutionen för data- och informationsteknik (GU),Department of Computer Science and Engineering (GU),Computer Science and Engineering, University of Gothenburg, Gothenburg, Sweden / Computer Science and Engineering, Chalmers, Gothenburg, Sweden
Sandberg, A. (author)
Ericsson, Sweden
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Hansson, Jörgen (author)
Högskolan i Skövde,Institutionen för informationsteknologi,Forskningscentrum för Informationsteknologi
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 (creator_code:org_t)
IEEE, 2016
2016
English.
In: Proceedings of 2016 Joint Conference of the International Workshop on Software Measurement and the International Conference on Software Process and Product Measurement (Iwsm-Mensura). - : IEEE. - 9781509041473 - 9781509041480
  • Conference paper (peer-reviewed)
Abstract Subject headings
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  • Unequivocally understandable requirements are vital for software design process. However, in practice it is hard to achieve the desired level of understandability, because in large software products a substantial amount of requirements tend to have ambiguous or complex descriptions. Over time such requirements decelerate the development speed and increase the risk of late design modifications, therefore finding and improving them is an urgent task for software designers. Manual reviewing is one way of addressing the problem, but it is effort-intensive and critically slow for large products. Another way is using measurement, in which case one needs to design effective measures. In recent years there have been great endeavors in creating and validating measures for requirements understandability: most of the measures focused on ambiguous patterns. While ambiguity is one property that has major effect on understandability, there is also another important property, complexity, which also has major effect on understandability, but is relatively less investigated. In this paper we define a complexity measure for textual requirements through an action research project in a large software development organization. We also present its evaluation results in three large companies. The evaluation shows that there is a significant correlation between the measurement values and the manual assessment values of practitioners. We recommend this measure to be used with earlier created ambiguity measures as means for automated identification of complex specifications.

Subject headings

NATURVETENSKAP  -- Data- och informationsvetenskap (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences (hsv//eng)
NATURVETENSKAP  -- Data- och informationsvetenskap -- Programvaruteknik (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Software Engineering (hsv//eng)
NATURVETENSKAP  -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Sciences (hsv//eng)

Keyword

measure
requirement
quality
complexity
automation
quality
success
measure

Publication and Content Type

ref (subject category)
kon (subject category)

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