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Journal of Systems and Software
Article . 2017 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
https://dx.doi.org/10.48550/ar...
Article . 2016
License: arXiv Non-Exclusive Distribution
Data sources: Datacite
DBLP
Article . 2016
Data sources: DBLP
DBLP
Article . 2017
Data sources: DBLP
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Rapid quality assurance with Requirements Smells

Authors: Henning Femmer; Daniel Méndez Fernández; Stefan Wagner 0001; Sebastian Eder;

Rapid quality assurance with Requirements Smells

Abstract

Bad requirements quality can cause expensive consequences during the software development lifecycle, especially if iterations are long and feedback comes late. %-- the faster a problem is found, the cheaper it is to fix. This makes explicit the need of a lightweight detection mechanism of requirements quality violations. We aim at a light-weight static requirements analysis approach that allows for rapid checks immediately when requirements are written down. We transfer the concept of code smells to Requirements Engineering as Requirements Smells. To evaluate the benefits and limitations, we define Requirements Smells, realize our concepts for a smell detection in a prototype called Smella and apply Smella in a series of cases provided by three industrial and a university context. The automatic detection yields an average precision of 59% at an average recall of 82% with high variation. The evaluation in practical environments indicates benefits such as an increase of the awareness of quality defects. Yet, some smells were not clearly distinguishable. Lightweight smell detection can uncover many practically relevant requirements defects in a reasonably precise way. Although some smells need to be defined more clearly, smell detection provides a helpful means to support quality assurance in Requirements Engineering, for instance, as a supplement to reviews.

The Journal of Systems and Software, 2016

Country
Germany
Keywords

Software Engineering (cs.SE), FOS: Computer and information sciences, Computer Science - Software Engineering, Requirements engineering , Qualitätssicherung , Fehlererkennung, Automatische Fehlererkennung , Smells in Anforderungen, Automatic Defect Detection , Requirements Smells, 004

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
117
Top 1%
Top 1%
Top 1%
Green
bronze