Configuration problems are a thriving application area for declarative knowledge representation that currently experiences a constant increase in size and complexity of knowledge bases. Automated support of the debugging process of such knowledge bases is a necessary prerequisite for effective development of configurators. We show that this task can be achieved by consistency-based diagnosis techniques. Based on the formal definition of consistency-based configuration we develop a framework suitable for diagnosing configuration knowledge bases. During the test phase of configurators, valid and invalid examples are used to test the correctness of the system. In case such examples lead to unintended results, debugging of the knowledge base is initiated. Starting from a clear definition of diagnosis in the configuration domain we develop an algorithm based on conflicts. Our framework is general enough for its adaptation to diagnosing customer requirements to identify unachievable conditions during configuration sessions. A prototype implementation using commercial constraint-based configurator libraries shows the feasibility of diagnosis within the tight time bounds of interactive debugging sessions. Finally, we discuss the usefulness of the outcomes of the diagnostic process in different scenarios.

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This paper describes the technical principles and representation behind the constraint-based, automated configurator COCOS. Traditionally, representation methods for technical configuration have focused either on reasoning about structure of systems or quantity of components, which is not satisfactory in many target areas that need both. Starting from general requirements on configuration systems, we have developed an extension of the standard CSP model. The constraint-based approach allows a simple system architecture, and a declarative description of the different types of configuration knowledge. Knowledge bases are described in terms of a component-centered knowledge base written in an object-oriented representation language with semantics directly based on the underlying constraint model. The approach combines a simple, declarative representation with the ability to configure large-scale systems and is in use for actual production applications.

Object-oriented design methodologies represent the behavior of instances of an object type not merely by a set of operations, but also by providing an overall description on how instances evolve over time. Such a description is often referred to as "object life cycle."Object-oriented systems organize object types in hierarchies in which subtypes inherit and specialize the structure and behavior of their supertypes. Past experience has shown that unrestricted use of inheritance mechanisms leads to system architectures that are hard to understand and to maintain, since arbitrary differences between supertype and subtype are possible. Evidently, this is not a desirable state of affairs and the behavior of a subtype should specialize the behavior of its supertype according to some clearly defined consistency criteria. Such criteria have been formulated in terms of type systems for semantic data models and object-oriented programming languages. But corresponding criteria for the specialization of object life cycles have so far not been thoroughly investigated.This paper defines such criteria in the realm of Object Behavior Diagrams, which have been originally developed for the design of object-oriented databases. Its main contributions are necessary and sufficient rules for checking behavior consistency between object life cycles of object types in specialization hierarchies with multiple inheritance.

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Today's economy exhibits a growing trend toward highly specialized solution providers cooperatively offering configurable products and services to their customers. This paradigm shift requires the extension of current standalone configuration technology with capabilities of knowledge sharing and distributed problem solving. In this context a standardized configuration knowledge representation language with formal semantics is needed in order to support knowledge interchange between different configuration environments. Languages such as Ontology Inference Layer OIL! and DARPA Agent Markup Language~DAMLϩOIL! are based on such formal semantics~description logic! and are very popular for knowledge representation in the Semantic Web. In this paper we analyze the applicability of those languages with respect to configuration knowledge representation and discuss additional demands on expressivity. For joint configuration problem solving it is necessary to agree on a common problem definition. Therefore, we give a description logic based definition of a configuration problem and show its equivalence with existing consistency-based definitions, thus joining the two major streams in knowledge-based configuration~description logics and predicate logic0constraint based configuration!.

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