A case study validation of a knowledge-based approach for the selection of requirements engineering techniques

  • Authors:

  • Li Jiang;Armin Eberlein;Behrouz H. Far

  • Affiliations:

  • The University of Adelaide, School of Computer Science, 5005, Adelaide, SA, Australia;American University of Sharjah, Computer Engineering Department, P.O. Box 26666, 5005, Sharjah, SA, United Arab Emirates;University of Calgary, Department of Electrical and Computer Engineering, P.O. Box 26666, 2500 University Drive, 5005, N.W. Calgary, AB, Canada

  • Venue:
  • Requirements Engineering
  • Year:
  • 2008

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Abstract

Requirements engineering (RE) is a critical phase in the software engineering process and plays a vital role in ensuring the overall quality of a software product. Recent research has shown that industry increasingly recognizes the importance of good RE practices and the use of appropriate RE techniques. However, due to the large number of RE techniques, requirements engineers find it challenging to select suitable techniques for a particular project. Unfortunately, technique selection based on personal experience has limitations with regards to the scope, effectiveness and suitability of the RE techniques for the project at hand. In this paper, a Knowledge-based Approach for the Selection of Requirements Engineering Techniques (KASRET) is proposed that helps during RE techniques selection. This approach has three major features. First, a library of requirements techniques was developed which includes detailed knowledge about RE techniques. Second, KASRET integrates advantages of different knowledge representation schemata and reasoning mechanisms. Thus, KASRET provides mechanisms for the management of knowledge about requirements techniques and support for RE process development. Third, as a major decision support mechanism, an objective function evaluates the overall ability and cost of RE techniques, which is helpful for the selection of RE techniques. This paper makes not only a contribution to RE but also to research and application of knowledge management and decision support in process development. A case study using an industrial project shows the support of KASRET for RE techniques selection.