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

Fabiano Dalpiaz, Ivor van der Schalk, Garm Lucassen

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    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.
    [Principalideas/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.
    Original languageEnglish
    Title of host publicationRequirements engineering: foundation for software quality
    Subtitle of host publication24th international working conference, REFSQ 2018, Utrecht, The Netherlands, March 19-22, 2018 : proceedings
    EditorsErik Kamsties, Jennifer Horkoff, Fabiano Dalpiaz
    Pages119-135
    Number of pages17
    ISBN (Electronic)9783319772431
    DOIs
    Publication statusPublished - 2018

    Publication series

    NameLecture notes in computer science
    Volume10753

    Keywords

    • Natural language processing
    • Requirements engineering
    • Information visualization
    • User stories
    • Ambiguity
    • European Union (EU)
    • Horizon 2020
    • Euratom
    • Euratom research & training programme 2014-2018

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