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Ontology-based automated support for goal–use case model analysis

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Abstract

Combining goal-oriented and use case modeling has been proven to be an effective method in requirements elicitation and elaboration. To ensure the quality of such modeled artifacts, a detailed model analysis needs to be performed. However, current requirements engineering approaches generally lack reliable support for automated analysis of consistency, correctness and completeness (3Cs problems) between and within goal models and use case models. In this paper, we present a goal–use case integration framework with tool support to automatically identify such 3Cs problems. Our new framework relies on the use of ontologies of domain knowledge and semantics and our goal–use case integration meta-model. Moreover, functional grammar is employed to enable the semiautomated transformation of natural language specifications into Manchester OWL Syntax for automated reasoning. The evaluation of our tool support shows that for representative example requirements, our approach achieves over 85 % soundness and completeness rates and detects more problems than the benchmark applications.

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Notes

  1. For a detailed account of FG, the interested reader is referred to (Nguyen 2014).

  2. http://protege.stanford.edu/.

  3. http://protegewiki.stanford.edu/.

  4. http://www.swoogle.umbc.edu.

  5. The verb collection can be found at http://goo.gl/gCUofM.

  6. http://oops.linkeddata.es/.

  7. Except requirements from TSN are confidential, original requirements for OPS and SPS can be found at http://www.cse.msu.edu/~chengb/RE-491/Papers/SRSExample-webapp.doc and http://www.cise.ufl.edu/class/cen3031sp13/SRS_Example_1_2011.pdf.

  8. http://www.reusecompany.com/requirements-quality-analyzer.

  9. http://www.sirius-requirements.com/product/.

  10. https://www.innoslate.com/.

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Acknowledgments

The authors gratefully acknowledge support from the Victorian Government under the Victorian International Research Scholarships scheme, Swinburne University of Technology, and the Australian Research Council under Linkage Project LP130100201.

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Authors and Affiliations

  1. Faculty of Science, Engineering and Technology, Swinburne University of Technology, Melbourne, VIC, Australia

    Tuong Huan Nguyen, John C. Grundy & Mohamed Almorsy

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  1. Tuong Huan Nguyen
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Correspondence to Tuong Huan Nguyen.

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Nguyen, T.H., Grundy, J.C. & Almorsy, M. Ontology-based automated support for goal–use case model analysis. Software Qual J 24, 635–673 (2016). https://doi.org/10.1007/s11219-015-9281-7

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