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Pinpointing Ambiguity and Incompleteness in Requirements Engineering via Information Visualization and NLP

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Requirements Engineering: Foundation for Software Quality (REFSQ 2018)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 10753))

Abstract

[Context and motivation] Identifying requirements defects such as ambiguity and incompleteness is an important and challenging task in requirements engineering (RE). [Question/Problem] We investigate whether combining humans’ cognitive and analytical capabilities with automated reasoning is a viable method to support the identification of requirements quality defects. [Principal ideas/results] We propose a tool-supported approach for pinpointing terminological ambiguities between viewpoints as well as missing requirements. To do so, we blend natural language processing (conceptual model extraction and semantic similarity) with information visualization techniques that help interpret the type of defect. [Contribution] Our approach is a step forward toward the identification of ambiguity and incompleteness in a set of requirements, still an open issue in RE. A quasi-experiment with students, aimed to assess whether our tool delivers higher accuracy than manual inspection, suggests a significantly higher recall but does not reveal significant differences in precision.

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Notes

  1. 1.

    http://api.cortical.io/.

  2. 2.

    Using triangular shapes, it is possible to show six viewpoints on a 2D space [20].

  3. 3.

    http://www.staff.science.uu.nl/~dalpi001/revv/.

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Acknowledgment

This project has received funding from the SESAR Joint Undertaking under grant agreement No 699306 under European Union’s Horizon 2020 research and innovation programme.

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Authors and Affiliations

  1. RE-Lab, Department of Information and Computing Sciences, Utrecht University, Utrecht, Netherlands

    Fabiano Dalpiaz, Ivor van der Schalk & Garm Lucassen

Authors
  1. Fabiano Dalpiaz
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  2. Ivor van der Schalk
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  3. Garm Lucassen
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Corresponding author

Correspondence to Fabiano Dalpiaz .

Editor information

Editors and Affiliations

  1. Dortmund University of Applied Sciences and Arts, Dortmund, Germany

    Erik Kamsties

  2. Chalmers and University of Gothenburg, Gothenburg, Sweden

    Jennifer Horkoff

  3. Utrecht University, Utrecht, The Netherlands

    Fabiano Dalpiaz

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Dalpiaz, F., van der Schalk, I., Lucassen, G. (2018). Pinpointing Ambiguity and Incompleteness in Requirements Engineering via Information Visualization and NLP. In: Kamsties, E., Horkoff, J., Dalpiaz, F. (eds) Requirements Engineering: Foundation for Software Quality. REFSQ 2018. Lecture Notes in Computer Science(), vol 10753. Springer, Cham. https://doi.org/10.1007/978-3-319-77243-1_8

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  • DOI: https://doi.org/10.1007/978-3-319-77243-1_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-77242-4

  • Online ISBN: 978-3-319-77243-1

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