2020/08/11 by Jan Haltermann, Haltermann, Jan, Heike Wehrheim +1
Computer Science · #Advanced Malware Detection Techniques #D.2.4 #FOS: Computer and information sciences #Software Engineering (cs.SE) #Software Engineering Research #Software Testing and Debugging Techniques
paper · pdf · doi:10.48550/arxiv.2008.04551
openalex publication_date 2020/08/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Software verification has recently made enormous progress due to the development of novel verification methods and the speed-up of supporting technologies like SMT solving. To keep software verification tools up to date with these advances, tool developers keep on integrating newly designed methods into their tools, almost exclusively by re-implementing the method within their own framework. While this allows for a conceptual re-use of methods, it requires novel implementations for every new technique. In this paper, we employ cooperative verification in order to avoid reimplementation and enable usage of novel tools as black-box components in verification. Specifically, cooperation is employed for the core ingredient of software verification which is invariant generation. Finding an adequate loop invariant is key to the success of a verification run. Our framework named CoVerCIG allows a master verification tool to delegate the task of invariant generation to one or several specialized helper invariant generators. Their results are then utilized within the verification run of the master verifier, allowing in particular for crosschecking the validity of the invariant. We experimentally evaluate our framework on an instance with two masters and three different invariant generators using a number of benchmarks from SV-COMP 2020. The experiments show that the use of CoVerCIG can increase the number of correctly verified tasks without increasing the used resources