Btor2-Cert: A Certifying Hardware-Verification Framework Using Software Analyzers

Formal verification is essential but challenging: Even the best verifiers may produce wrong verification verdicts. Certifying verifiers enhance the confidence in verification results by generating a witness for other tools to validate the verdict independently. Recently, translating the hardware-modeling language Btor2 to software, such as the programming language C or LLVM intermediate representation, has been actively studied and facilitated verifying hardware designs by software analyzers. However, it remained unknown whether witnesses produced by software verifiers contain helpful information about the original circuits and how such information can aid hardware analysis. We propose a certifying and validating framework Btor2-Cert to verify safety properties of Btor2 circuits, combining Btor2-to-C translation, software verifiers, and a new witness validator Btor2-Val, to answer the above open questions. Btor2-Cert translates a software violation witness to a Btor2 violation witness; As the Btor2 language lacks a format for correctness witnesses, we encode invariants in software correctness witnesses as Btor2 circuits. The validator Btor2-Val checks violation witnesses by circuit simulation and correctness witnesses by validation via verification. In our evaluation, Btor2-Cert successfully utilized software witnesses to improve quality assurance of hardware. By invoking the software verifier Cbmc on translated programs, it uniquely solved, with confirmed witnesses, 8 % of the unsafe tasks for which the hardware verifier ABC failed to detect bugs.

Btor2-Cert: A Certifying Hardware-Verification Framework Using Software Analyzers

Ádám,

Beyer,

Chien

et al. 2024

The MoXI Model Exchange Tool Suite

Johannsen,

Nukala,

Dureja

et al. 2024

We release the first tool suite implementing MoXI (Model eXchange Interlingua), an intermediate language for symbolic model checking designed to be an international research-community standard and developed by a widespread collaboration under a National Science Foundation (NSF) CISE Community Research Infrastructure initiative. Although we focus here on hardware verification, the MoXI language is useful for software model checking and verification of infinite-state systems in general. MoXI builds on elements of SMT-LIB 2; it is easy to add new theories and operators. Our contributions include: (1) introducing the first tool suite of automated translators into and out of the new model-checking intermediate language; (2) composing an initial example benchmark set enabling the model-checking research community to build future translations; (3) compiling details for utilizing, extending, and improving upon our tool suite, including usage characteristics and initial performance data. Experimental evaluations demonstrate that compiling SMV-language models through MoXI to perform symbolic model checking with the tools from the last Hardware Model Checking Competition performs competitively with model checking directly via nuXmv.

Safeguarding AI-Based Software Development and Verification using Witnesses (Position Paper)

Beyer

2024

This position paper accompanies a presentation and discussion at AISoLA 2023 on the topic of how (generative) AI influences software engineering, namely, the development and verification of software programs. We outline a few opportunities and challenges that are posed by the application of AI. AI-based techniques can be an efficient method to produce software code. Not only this, AI can also be efficient in producing invariants that help proving correctness of software programs. But unfortunately, the results generated by AI-based approaches are often still imprecise or wrong: Code produced with the help of AI often does not satisfy the specification, and AI-generated invariants are often not helpful to prove the correctness of the program. The solution is to safeguard the process by independently checking the results using verification witnesses and witness validation. The goal of this paper is to convince readers that software witnesses are important and that independent result validation is of utmost importance to ensure correctness.