Measuring Inconsistency in Requirements Specifications

Abstract

Abstract. In the field of requirements engineering, measuring inconsistency is crucial to effective inconsistency management. A practical measure must consider both the degree and significance of inconsistency in specification. The main contribution of this paper is providing an approach for measuring inconsistent specification in terms of the prioritybased scoring vector, which integrates the measure of the degree of inconsistency with the measure of the significance of inconsistency. In detail, for each specification ∆ that consists of a set of requirements statements, if L is a m-level priority set, we define a m-dimensional priority-based significance vector − → V to measure the significance of the inconsistency in ∆. Furthermore, a priority-based scoring vector − → SP : P(∆) → N m+1 has been defined to provide an ordering relation over specifications that describes which specification is "more essentially inconsistent than" others.

An Enhanced Negotiation-Style Framework for Requirements Change

“…Ke-Dian Mu, Zhi Jin etc., proposed a series of work [14][15][16][17][18] to manage the changes of the software requirements. In [14] they think that the framework based on the Booth negotiating architecture [19] can be used to manage the changes of the requirements and eliminate the inconsistencies.…”

A Characteristic Function Approach to Inconsistency Measures for Knowledge Bases

“…This assumption is often not applicable in practice, as argued in many research work discussing the inconsistency of a knowledge base (e.g., [18,7,8]). An obvious advantage of our merging methods is that they do not require this assumption.…”

“…Logic based knowledge representation is used in many cases, such as software requirements [18], expert systems [20], belief merging [9]. In most of the applications, logic based knowledge bases (KB) are flat, that is all formulae in the base are equally important.…”

“…One is on measuring the inconsistency of a knowledge base (e.g., [18,8]) and the other is the merging of multiple knowledge bases e.g., [9,12,13]). Most of these approaches deploy logic-based formalisms, even when priorities or degrees of certainty are involved.…”

An Anytime Algorithm for Computing Inconsistency Measurement

“…whether to ignore it or to resolve it. Furthermore, measuring inconsistency in a knowledge base can provide some context information which can be used to resolve inconsistency [2][3][4], and proves useful in different scenarios such as Software Engineering [5].…”