Deriving static and dynamic concepts from software requirements using sophisticated tagging

  • Authors:

  • Günther Fliedl;Christian Kop;Heinrich C. Mayr;Alexander Salbrechter;Jürgen Vöhringer;Georg Weber;Christian Winkler

  • Affiliations:

  • Institute of Business Informatics and Application Systems, University of Klagenfurt, Austria;Institute of Business Informatics and Application Systems, University of Klagenfurt, Austria;Institute of Business Informatics and Application Systems, University of Klagenfurt, Austria;Institute of Business Informatics and Application Systems, University of Klagenfurt, Austria;Institute of Business Informatics and Application Systems, University of Klagenfurt, Austria;Institute of Business Informatics and Application Systems, University of Klagenfurt, Austria;Institute of Linguistic and Computational Linguistic, University of Klagenfurt, Austria

  • Venue:
  • Data & Knowledge Engineering
  • Year:
  • 2007

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Abstract

Natural language requirements specifications form the basis for the subsequent phase of the information system development process, namely the development of conceptual schemata. Both, the textual as well as the conceptual representations are not really appropriate for being thoroughly captured and validated by the 'requirement holders', i.e. the end users. Therefore, in our approach the textual specifications are firstly linguistically analyzed and translated into a so-called conceptual predesign schema. That schema is formulated using an interlingua which is based on a lean semantic model, thus allowing users to participate more efficiently in the design and validation process. After validation, the predesign schema is mapped to a conceptual representation (e.g. UML). The sequence of these translation and transformation steps is described by the ''NIBA workflow''. This paper focuses on the information supporting a step by step mapping of natural language requirements specifications to a conceptual model, and on how that information is gained. On particular, we present a four-level interpretation of tagging-output.