Constraint sets can become inconsistent in different contexts. For example, during a configuration session the set of customer requirements can become inconsistent with the configuration knowledge base. Another example is the engineering phase of a configuration knowledge base where the underlying constraints can become inconsistent with a set of test cases. In such situations we are in the need of techniques that support the identification of minimal sets of faulty constraints that have to be deleted in order to restore consistency. In this paper we introduce a divide and conquer-based diagnosis algorithm (FastDiag) that identifies minimal sets of faulty constraints in an overconstrained problem. This algorithm is specifically applicable in scenarios where the efficient identification of leading (preferred) diagnoses is crucial. We compare the performance of FastDiag with the conflict-directed calculation of hitting sets and present an in-depth performance analysis that shows the advantages of our approach.

Abstract. Requirements engineering is one of the most critical phases in software development. Requirements verbalize decision alternatives that are negotiated by stakeholders. In this paper we present the results of an empirical analysis of the effects of applying group recommendation technologies to requirements negotiation. This analysis has been conducted within the scope of software development projects at our university where development teams were supported with group recommendation technologies when deciding which requirements should be implemented. A major result of the study is that group recommendation technologies can improve the perceived usability (in certain cases) and the perceived quality of decision support. Furthermore, it is not recommended to disclose preferences of individual group members at the beginning of a decision process -this could lead to an insufficient exchange of decision-relevant information.

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