Deciding floating-point logic with abstract conflict driven clause learning
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Publication:479837
DOI10.1007/s10703-013-0203-7zbMath1317.68110OpenAlexW2127145687WikidataQ59395541 ScholiaQ59395541MaRDI QIDQ479837
Vijay D'Silva, Daniel Kroening, Martin Brain, Alberto Griggio, Leopold Haller
Publication date: 5 December 2014
Published in: Formal Methods in System Design (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10703-013-0203-7
Learning and adaptive systems in artificial intelligence (68T05) Specification and verification (program logics, model checking, etc.) (68Q60) Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20)
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Abstract interpretation as automated deduction, An approximation framework for solvers and decision procedures, Semantically-guided goal-sensitive reasoning: model representation, Abstract Interpretation as Automated Deduction, Correct approximation of IEEE 754 floating-point arithmetic for program verification, Analysis and Transformation of Constrained Horn Clauses for Program Verification, raSAT: an SMT solver for polynomial constraints, A two-phase approach for conditional floating-point verification, Rigorous Estimation of Floating-Point Round-off Errors with Symbolic Taylor Expansions, Optimization modulo the theories of signed bit-vectors and floating-point numbers, \textsc{OptiMathSAT}: a tool for optimization modulo theories, Optimization modulo the theory of floating-point numbers, A Survey of Satisfiability Modulo Theory, An SMT theory of fixed-point arithmetic
Uses Software
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