Planning proofs of equations in CCS.

*(English)*Zbl 1034.68646Summary: Most efforts to automate formal verification of communicating systems have centred around finite-state systems (FSSs). However, FSSs are incapable of modelling many practical communicating systems, including a novel class of problems, which we call VIPS. VIPSs are value-passing, infinite-state, parameterised systems. Existing approaches using model checking over FSSs are insufficient for VIPSs. This is due to their inability both to reason with and about domain-specific theories, and to cope with systems having an unbounded or arbitrary state space.

We use the Calculus of Communicating Systems (CCS) to express and specify VIPSs. We take program verification to be proving the program and its intended specification equivalent. We use the laws of CCS to conduct the verification task. This approach allows us to study communicating systems and the data such systems communicate. Automating theorem proving in this context is an extremely difficult task.

We provide automated methods for CCS analysis; they are applicable to both FSSs and VIPSs. Adding these methods to the \(CL^AM\) proof planner, we have implemented an automated verification planner capable of dealing with problems that previously required human interaction. This paper describes these methods, gives an account as to why they work, and provides a short summary of experimental results.

We use the Calculus of Communicating Systems (CCS) to express and specify VIPSs. We take program verification to be proving the program and its intended specification equivalent. We use the laws of CCS to conduct the verification task. This approach allows us to study communicating systems and the data such systems communicate. Automating theorem proving in this context is an extremely difficult task.

We provide automated methods for CCS analysis; they are applicable to both FSSs and VIPSs. Adding these methods to the \(CL^AM\) proof planner, we have implemented an automated verification planner capable of dealing with problems that previously required human interaction. This paper describes these methods, gives an account as to why they work, and provides a short summary of experimental results.