IMMizer: An Innovative Cost-Effective Method for Minimizing Assertion Sets

Abstract

Assertion-based verification is one of the viable solutions for the verification of computer systems. Assertions can be automatically generated by assertion miners however, these miners typically generate a high number of possibly redundant assertions. In turn, this results in higher costs and overheads in the verification process. Furthermore, these assertions have every so often low readability due to the high number of propositions that they contain. In this paper, an Innovative cost-effective Method for Minimizing assertion sets (IMMizer) has been proposed. IMMizer is performed by iden-tifying Contradictory Terms. These terms present the behaviors of the design under verification which are not specified by the initial assertion sets. Subsequently, a new assertion set is extracted based on the identified Contradictory Terms. Contrary to data-mining approaches that are unable to minimize the initial assertion set, but can only rank the set according to data-mining measurements, or mutant analysis approaches that require a long execution time, IMMizer is able to minimize the initial assertion set in a very short execution time. Experimental results showed that in the best case, this method has drastically reduced the number of assertions by 93% and the memory overhead imposed on the system by 87%, without any reduction in the detection of injected mutants.