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A Blame-Based Approach to Generating Proposals for Handling Inconsistency in Software Requirements

Author

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  • Kedian Mu

    (Peking University, China)

  • Weiru Liu

    (Queen’s University Belfast, UK)

  • Zhi Jin

    (Peking University, China)

Abstract

Inconsistency has been considered one of the main classes of defects in software requirements specification. Various logic-based techniques have been proposed to manage inconsistencies in requirements engineering. However, identifying an appropriate proposal for resolving inconsistencies in software requirements is still a challenging problem. This paper proposes a logic-based approach to generating appropriate proposals for handling inconsistency in software requirements. Informally speaking, given an inconsistent requirements specification, the authors identify which requirements should be given priority to be changed for resolving the inconsistency in that specification, by balancing the blame of each requirement for the inconsistency against its value for that requirements specification. The authors follow the viewpoint that minimal inconsistent subsets of a set of formulas are the purest forms of inconsistencies in that set. According to this viewpoint, a potential proposal for resolving inconsistencies can be described by a possible combination of some requirements to be changed that can eliminate minimal inconsistent subsets. Then a method is proposed of evaluating the degree of disputability of each requirement involved in the inconsistency in a requirements specification. Finally, an algorithm is provided of generating appropriate proposals for resolving the inconsistency in a given requirements specification based on the degree of disputability of requirements.

Suggested Citation

  • Kedian Mu & Weiru Liu & Zhi Jin, 2012. "A Blame-Based Approach to Generating Proposals for Handling Inconsistency in Software Requirements," International Journal of Knowledge and Systems Science (IJKSS), IGI Global, vol. 3(1), pages 1-17, January.
  • Handle: RePEc:igg:jkss00:v:3:y:2012:i:1:p:1-17
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