Detection and recovery of high-level control structures, such as functions and their arguments, plays an important role in decompilation. It has a direct impact on the quality of the generated code because it is needed for generating functionally equivalent and highly readable code. In this paper, we present an innovative, platform-independent method of detection and recovery of functions and their arguments. This method is based on static code interpretation and iterative bidirectional search over reconstructed basic blocks. This approach has been adopted and tested in an existing retargetable decompiler. According to our experimental results, the proposed retargetable solution is fully competitive with existing hand-coded decompilers.

Abstract-Automated planning even in its simplest form, classical planning, is a computationally hard problem. With the increasing involvement of intelligent systems in everyday life there is a need for more and more advanced planning techniques able to solve planning problems in little (or real) time. However, planners designed to solve planning problems as fast as possible often provide solution plans of low quality. The quality of solution plans can be improved by their post-planning analysis by which redundant actions or optimizable subplans can be identified. In this paper, we present techniques for determining redundancy of actions in plans. Especially, we present techniques for efficient redundancy checking of pairs of inverse actions. These techniques are accompanied with necessary theoretical foundations and are also empirically evaluated using existing planning systems and standard planning benchmarks.