On Locally Strongest Assumption Generation Method for Component-Based Software Verification

Abstract

Assume-guarantee reasoning, a well-known approach in component-based software (CBS) verification, is in
fact a language containment problem whose computational cost depends on the sizes of languages of the software
components under checking and the assumption to be generated. Therefore, the smaller language assumptions,
the more computational cost we can reduce in software verification. Moreover, strong assumptions are more
important in CBS verification in the context of software evolution because they can be reused many times in the
verification process. For this reason, this paper presents a method for generating locally strongest assumptions with
locally smallest languages during CBS verification. The key idea of this method is to create a variant technique
for answering membership queries of the Teacher when responding to the Learner in the L–based assumption
learning process. This variant technique is then integrated into an algorithm in order to generate locally strongest
assumptions. These assumptions will effectively reduce the computational cost when verifying CBS, especially
for large–scale and evolving ones. The correctness proof, experimental results, and some discussions about the
proposed method are also presented.
Keywords: Assume-guarantee reasoning, Model checking, Component-based software verification, Locally
strongest assumptions, Locally smallest language assumptions.