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  • Automatic early defects detection in use case documents

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    LiuPUB2094.pdf (388.4Kb)
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    Accepted Manuscript (AM)
    Author(s)
    Liu, S
    Sun, J
    Liu, Y
    Zhang, Y
    Wadhwa, B
    Dong, JS
    Wang, X
    Griffith University Author(s)
    Dong, Jin-Song
    Year published
    2014
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    Abstract
    Use cases, as the primary techniques in the user requirement analysis, have been widely adopted in the requirement engineering practice. As developed early, use cases also serve as the basis for function requirement development, system design and testing. Errors in the use cases could potentially lead to problems in the system design or implementation. It is thus highly desirable to detect errors in use cases. Automatically analyzing use case documents is challenging primarily because they are written in natural languages. In this work, we aim to achieve automatic defect detection in use case documents by leveraging on ...
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    Use cases, as the primary techniques in the user requirement analysis, have been widely adopted in the requirement engineering practice. As developed early, use cases also serve as the basis for function requirement development, system design and testing. Errors in the use cases could potentially lead to problems in the system design or implementation. It is thus highly desirable to detect errors in use cases. Automatically analyzing use case documents is challenging primarily because they are written in natural languages. In this work, we aim to achieve automatic defect detection in use case documents by leveraging on advanced parsing techniques. In our approach, we first parse the use case document using dependency parsing techniques. The parsing results of each use case are further processed to form an activity diagram. Lastly, we perform defect detection on the activity diagrams. To evaluate our approach, we have conducted experiments on 200+ real-world as well as academic use cases. The results show the effectiveness of our method.
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    Conference Title
    ASE 2014 - Proceedings of the 29th ACM/IEEE International Conference on Automated Software Engineering
    DOI
    https://doi.org/10.1145/2642937.2642969
    Copyright Statement
    © ACM, 2014. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in Proceedings of the 29th ACM/IEEE international conference on Automated software engineering, ISBN: 978-1-4503-3013-8, DOI: 10.1145/2642937.2642969
    Subject
    Software engineering not elsewhere classified
    Publication URI
    http://hdl.handle.net/10072/269506
    Collection
    • Conference outputs

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