Value passing process algebras with infinite data domains need to be equipped with symbolic semantic models in order for their analysis to be possible. This means that appropriate symbolic models and the related verification algorithms must be developed, together with suitable semantic rules mapping the value passing process descriptions to such symbolic models. In this paper, we first introduce the model of the symbolic transition graphs with lookahead assignment (STGLA), a variant of the symbolic transition graphs with assignment (STGA) of Lin that can undergo to the strong, weak and observational bisimulation equivalence checking algorithms of Li and Chen. We then define a set of symbolic semantic rules that map a useful fragment of value passing CCS to finite STGLA without making any assumption on the variable names. We demonstrate that the symbolic semantic rules are correct with respect to both the usual concrete semantic rules and the novel issue of the assignment application order. Finally, we prove that, for the considered fragment of value passing CCS, the STGLA produced by the symbolic semantic rules are optimal with respect to a certain compactness criterion, thus improving on the symbolic models and the semantic rules previously proposed in the literature.
Symbolic Semantic Rules for Producing Compact STGLAs from Value Passing Process Descriptions
Bernardo, Marco
2004
Abstract
Value passing process algebras with infinite data domains need to be equipped with symbolic semantic models in order for their analysis to be possible. This means that appropriate symbolic models and the related verification algorithms must be developed, together with suitable semantic rules mapping the value passing process descriptions to such symbolic models. In this paper, we first introduce the model of the symbolic transition graphs with lookahead assignment (STGLA), a variant of the symbolic transition graphs with assignment (STGA) of Lin that can undergo to the strong, weak and observational bisimulation equivalence checking algorithms of Li and Chen. We then define a set of symbolic semantic rules that map a useful fragment of value passing CCS to finite STGLA without making any assumption on the variable names. We demonstrate that the symbolic semantic rules are correct with respect to both the usual concrete semantic rules and the novel issue of the assignment application order. Finally, we prove that, for the considered fragment of value passing CCS, the STGLA produced by the symbolic semantic rules are optimal with respect to a certain compactness criterion, thus improving on the symbolic models and the semantic rules previously proposed in the literature.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.