Assume-guarantee reasoning, a well-known approach in component-based software (CBS) verification, is infact a language containment problem whose computational cost depends on the sizes of languages of the softwarecomponents 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 moreimportant in CBS verification in the context of software evolution because they can be reused many times in theverification process. For this reason, this paper presents a method for generating locally strongest assumptions withlocally smallest languages during CBS verification. The key idea of this method is to create a variant techniquefor answering membership queries of the Teacher when responding to the Learner in the L–based assumptionlearning process. This variant technique is then integrated into an algorithm in order to generate locally strongestassumptions. These assumptions will effectively reduce the computational cost when verifying CBS, especiallyfor large–scale and evolving ones. The correctness proof, experimental results, and some discussions about theproposed method are also presented.Keywords: Assume-guarantee reasoning, Model checking, Component-based software verification, Locallystrongest assumptions, Locally smallest language assumptions.
A Latent Implementation Error Detection Method for Software Validation
