Recursive Decomposition of Progress Graphs

Abstract

Search of a state transition system is traditionally how deadlock detection for concurrent programs has been accomplished. This paper examines an approach to deadlock detection that uses geometric semantics involving the topological notion of dihomotopy to partition the state-space into components; after that the reduced state-space is exhaustively searched. Prior work partitioned the state-space inductively. In this paper we show that a recursive technique provides greater reduction of the size of the state transition system and therefore more efficient deadlock detection. If the preprocessing can be done efficiently, then for large problems we expect to see more efficient deadlock detection and eventually more efficient verification of some temporal properties.