Towards Formal Verification of Optimized and Industrial Multipliers

Mahzoon, Alireza; Grose, Daniel; Scholl, Christoph; Drechsler, Rolf

doi:10.23919/date48585.2020.9116485

Cited by 36 publications

(1 citation statement)

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“…Formal verification [8][9][10] illustrates the behaviors of complex hardware and software systems as a formal model, specifies the expected properties of requirements as strict logic formulas, and then uses mathematical deduction to check whether the properties are satisfied by the system model. For instance, model checking 11 verifies the system properties through automatically investigating the finite state space of the system model.…”

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confidence: 99%

Requirement specification extraction and analysis based on propositional projection temporal logic

Wang

Zhao

2023

J Software Evolu Process

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At present, formal methods significantly facilitate the specification and verification of security requirements in requirement engineering, which can reduce requirement errors in the early stage of system development. Extracting formal specifications from security requirements and then evaluating the quality of the requirements are regarded as a promising solution to ensure software quality. Propositional projection temporal logic (PPTL) with a strong mathematical basis and full regular expressiveness is a suitable language for formal specifications. Inspired by natural language processing and text mining techniques, this paper designs and implements a tool, namely, NL2PPTL, to generate formal coarse‐grained and fine‐grained specifications in terms of PPTL formulas automatically. In specific, the grammatical production rules are defined to construct the syntax tree, and then, the formula is obtained by post‐order traversal of the tree. The satisfiability of the PPTL specifications can be checked utilizing PPTLSAT. In addition, the state transformation model is constructed from fine‐grained specifications, so as to discover scope conflicts and verify the security properties of the requirement case.

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confidence: 99%