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The paper discusses a new knowledge representation for rule-based systems called XTT2. It combines decision trees and decision tables forming a transparent and hierarchical visual representation of the decision units linked into a workflow-like structure. There are two levels of abstraction in the XTT2 model: the lower level, where a single knowledge component defined by a set of rules working in the same context is represented by a single decision table, and the higher level, where the structure of the whole knowledge base is considered. This model has a concise formalization which opens up possibility of well-defined, structured design and verification of formal characteristics. Based on the visual XTT2 model, a textual representation of the rule base is generated. A dedicated engine provides a unified run-time environment for the XTT2 rule bases. The focus of the paper is on the formalization of the presented approach. It is based on the so-called ALSV(FD) logic that provides an expressive calculus for rules.

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