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A broad variety of knowledge-based applications such as recommender, expert,planning or configuration systems usually operate on the basis of knowledgerepresented by means of some logical language. Such a logical knowledge base(KB) enables intelligent behavior of such systems by allowing them toautomatically reason, answer queries of interest or solve complex real-worldproblems. Nowadays, where information acquisition comes at low costs and oftenhappens automatically, the applied KBs are continuously growing in terms ofsize, information content and complexity. These developments foster theemergence of errors in these KBs and thus pose a significant challenge on allpeople and tools involved in KB evolution, maintenance and application.  If some minimal quality criteria such as logical consistency are not met bysome KB, it becomes useless for knowledge-based applications. To guarantee thecompliance of KBs with given requirements, (non-interactive) KB debuggers havebeen proposed. These however often cannot localize all potential faults,suggest too large or incorrect modifications of the faulty KB or suffer frompoor scalability due to the inherent complexity of the KB debugging problem.  As a remedy to these issues, based on a well-founded theoretical basis thiswork proposes complete, sound and optimal methods for the interactive debuggingof KBs that suggest the one (minimally invasive) error correction of the faultyKB that yields a repaired KB with exactly the intended semantics. Users, e.g.domain experts, are involved in the debugging process by answeringautomatically generated queries whether some given statements must or must nothold in the domain that should be modeled by the problematic KB at hand.

A Theory of Interactive Debugging of Knowledge Bases in Monotonic Logics