The application of a medical guideline to the treatment of a patient's disease can be seen as the execution of tasks, sequentially or in parallel, in the face of patient data. It has been shown that many of such guidelines can be represented as a "network of tasks," that is, as a sequence of steps that have a specific function or goal. In this paper, a novel methodology for verifying the quality of such guidelines is introduced. To investigate the quality of such guidelines, we propose to include medical background knowledge to task networks and to formalize criteria for good medical practice that a guideline should comply with. This framework was successfully applied to a guideline dealing with the management of diabetes mellitus type 2 by using KIV.

Current techniques for interactively proving temporal properties of concurrent systems translate transition systems into temporal formulas by introducing program counter variables. Proofs are not intuitive, because control flow is not explicitly considered. For sequential programs symbolic execution is a very intuitive, interactive proof strategy. In this paper we will adopt this technique for parallel programs. Properties are formulated in interval temporal logic. An inplementation in the interactive theorem prover KIV has shown that this technique offers a high degree of automation and allows simple, local invariants.