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International Working Conference on Requirements Engineering: Foundation for Software Quality

REFSQ 2013: Requirements Engineering: Foundation for Software Quality pp 50–64Cite as

Automatic Requirement Categorization of Large Natural Language Specifications at Mercedes-Benz for Review Improvements

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Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 7830))

Abstract

Context and motivation: Today’s industry specifications, in particular those of the automotive industry, are complex and voluminous. At Mercedes-Benz, a specification and its referenced documents often sums up to 3,000 pages. Question/problem: A common way to ensure the quality in such natural language specifications is technical review. Given such large specifications, reviewers have major problems in finding defects, especially consistency or completeness defects, between requirements with related information, spread over the various documents. Principal ideas/results: In this paper, we investigate two specifications from Mercedes-Benz, whether requirements with related information spread over many sections of many documents can be automatically classified and extracted using text classification algorithms to support reviewers with their work. We further research enhancements to improve these classifiers. The results of this work demonstrate that an automatic classification of requirements for multiple aspects is feasible with high accuracy. Contribution: In this paper, we show how an automatic classification of requirements can be used to improve the review process. We discuss the limitations and potentials of using this approach.

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Author information

Authors and Affiliations

  1. Research and Development, Daimler AG, P.O. Box 2360, 89013, Ulm, Germany

    Daniel Ott

Authors
  1. Daniel Ott
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Editor information

Editors and Affiliations

  1. Fraunhofer-Institut Experimentelles Software Engineering, Fraunhofer-Platz 1, 67663, Kaiserslautern, Germany

    Joerg Doerr

  2. Department of Information Science and Media Studies, University of Bergen, NO-5020, Bergen, Norway

    Andreas L. Opdahl

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Ott, D. (2013). Automatic Requirement Categorization of Large Natural Language Specifications at Mercedes-Benz for Review Improvements. In: Doerr, J., Opdahl, A.L. (eds) Requirements Engineering: Foundation for Software Quality. REFSQ 2013. Lecture Notes in Computer Science, vol 7830. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37422-7_4

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  • DOI: https://doi.org/10.1007/978-3-642-37422-7_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37421-0

  • Online ISBN: 978-3-642-37422-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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