摘要 : We show that recursive programs where variables range over finite domains can be effectively and efficiently analyzed by describing the analysis algorithm using a formula in a fixed-point calculus. In contrast with programming in ... 展开 We show that recursive programs where variables range over finite domains can be effectively and efficiently analyzed by describing the analysis algorithm using a formula in a fixed-point calculus. In contrast with programming in traditional languages, a fixed-point calculus serves as a high-level programming language to easily, correctly, and succinctly describe model-checking algorithms. While there have been declarative high-level formalisms that have been proposed earlier for analysis problems (e.g., Datalog), the fixed-point calculus we propose has the salient feature that it also allows algorithmic aspects to be specified. We exhibit two classes of algorithms of symbolic (BDD-based) algorithms written using this framework-one for checking for errors in sequential recursive Boolean programs, and the other to check for errors reachable within a bounded number of context-switches in a concurrent recursive Boolean program. Our formalization of these otherwise complex algorithms is extremely simple, and spans just a page of fixed-point formulae. Moreover, we implement these algorithms in a tool called GETAFIX which expresses algorithms as fixed-point formulae and evaluates them efficiently using a symbolic fixed-point solver called MUCKE. The resulting model-checking tools are surprisingly efficient and are competitive in performance with mature existing tools that have been fine-tuned for these problems. 收起