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Which requirements artifact quality defects are automatically detectable?: A case study
Technical University Munich, GER.
Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för programvaruteknik. (Software Engineering Research Lab Sweden)ORCID-id: 0000-0003-4118-0952
Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för programvaruteknik.
2017 (engelsk)Inngår i: Proceedings - 2017 IEEE 25th International Requirements Engineering Conference Workshops, REW 2017, IEEE, 2017, s. 400-406, artikkel-id 8054884Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

[Context:] The quality of requirements engineeringartifacts, e.g. requirements specifications, is acknowledged tobe an important success factor for projects. Therefore, manycompanies spend significant amounts of money to control thequality of their RE artifacts. To reduce spending and improvethe RE artifact quality, methods were proposed that combinemanual quality control, i.e. reviews, with automated approaches.[Problem:] So far, we have seen various approaches to auto-matically detect certain aspects in RE artifacts. However, westill lack an overview what can and cannot be automaticallydetected. [Approach:] Starting from an industry guideline forRE artifacts, we classify 166 existing rules for RE artifacts alongvarious categories to discuss the share and the characteristics ofthose rules that can be automated. For those rules, that cannotbe automated, we discuss the main reasons. [Contribution:] Weestimate that 53% of the 166 rules can be checked automaticallyeither perfectly or with a good heuristic. Most rules need onlysimple techniques for checking. The main reason why some rulesresist automation is due to imprecise definition. [Impact:] Bygiving first estimates and analyses of automatically detectable andnot automatically detectable rule violations, we aim to provide anoverview of the potential of automated methods in requirementsquality control.

sted, utgiver, år, opplag, sider
IEEE, 2017. s. 400-406, artikkel-id 8054884
Emneord [en]
Artifact quality, Automated methods, Requirement engineering
HSV kategori
Identifikatorer
URN: urn:nbn:se:bth-15453DOI: 10.1109/REW.2017.18ISI: 000427148000063ISBN: 9781538634882 (tryckt)OAI: oai:DiVA.org:bth-15453DiVA, id: diva2:1155358
Konferanse
Fourth International Workshop on Artificial Intelligence for Requirements Engineering (AIRE'17), Lisboa
Tilgjengelig fra: 2017-11-07 Laget: 2017-11-07 Sist oppdatert: 2018-04-04bibliografisk kontrollert

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