Symbolic trajectory evaluation for word-level verification: theory and implementation
Autor: | Tanmay Haldankar, Dinesh Chhatani, Zurab Khasidashvili, Rakesh Mistry, Carl-Johan H. Seger, Rajkumar Gajavelly, Supratik Chakraborty |
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Rok vydání: | 2017 |
Předmět: |
Model checking
Rtl Verification Computer science Symbolic Simulation Symbolic simulation Invalid-Bit Encoding 02 engineering and technology Smt Solving 020202 computer hardware & architecture Theoretical Computer Science Hardware and Architecture Lattice (order) Bounded function Hardware Verification Symbolic trajectory evaluation 0202 electrical engineering electronic engineering information engineering Word-Level Verification 020201 artificial intelligence & image processing Algorithm Implementation X-Based Abstraction Software Symbolic Trajectory Evaluation Electronic circuit |
Zdroj: | Formal Methods in System Design. 50:317-352 |
ISSN: | 1572-8102 0925-9856 |
DOI: | 10.1007/s10703-017-0268-9 |
Popis: | Symbolic trajectory evaluation (STE) is a model checking technique that has been successfully used to verify many industrial designs. Existing implementations of STE reason at the level of bits, allowing signals in a circuit to take values from a lattice comprised of three elements: 0, 1, and X. This limits the amount of abstraction that can be achieved, and presents limitations to scaling STE to even larger designs. The main contribution of this paper is to show how much more abstract lattices can be derived automatically from register-transfer level descriptions, and how a model checker for the general theory of STE instantiated with such abstract lattices can be implemented in practice. We discuss several implementation issues, including how word-level circuits can be symbolically simulated using a new encoding for words that allows representing X values of sub-words succinctly. This gives us the first practical word-level STE engine, called $$\mathsf {STEWord}$$STEWord. Experiments on a set of designs similar to those used in industry show that $$\mathsf {STEWord}$$STEWord scales better than bit-level STE, as well as word-level bounded model checking. |
Databáze: | OpenAIRE |
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