Quantifier Instantiation Techniques for Finite Model Finding in SMT

Author(s):  
Andrew Reynolds ◽  
Cesare Tinelli ◽  
Amit Goel ◽  
Sava Krstić ◽  
Morgan Deters ◽  
...  
Author(s):  
Andrew Reynolds ◽  
Cesare Tinelli ◽  
Amit Goel ◽  
Sava Krstić
Keyword(s):  

10.29007/b923 ◽  
2018 ◽  
Author(s):  
Joshua Bax

Generalised Model Finding (GMF) is a quantifier instantiation heuristic for the superposition calculus in the presence of interpreted theories with arbitrarily quantified free function symbols ranging into theory sorts.The free function symbols are approximated by finite partial function graphs along with some simplifying assumptions which are iteratively refined.Here we present an outline of the GMF approach, give an improvementthat addresses some of these and then present someideas for extending it with concepts from instantiation based theorem proving.


10.29007/fjc4 ◽  
2018 ◽  
Author(s):  
Giles Reger

Question answering is the process of taking a conjecture existentially quantified at the outer- most level and providing one or more instantiations of the quantified variable(s) as a form of an answer to the implied question. For example, given the axioms p(a) and f(a)=a the question ?[X] : p(f(X)) could return the answer X=a. This paper reviews the question answering prob- lem focussing on how it is tackled within the VAMPIRE theorem prover. It covers how VAMPIRE extracts single answers, multiple answers, disjunctive answers, and answers involving theories such as arithmetic. The paper finishes by considering possible future directions, such as integration with finite model finding.


2017 ◽  
Vol 17 (4) ◽  
pp. 516-558
Author(s):  
ANDREW REYNOLDS ◽  
CESARE TINELLI ◽  
CLARK BARRETT

AbstractSatisfiability modulo theories (SMT) solvers have been used successfully as reasoning engines for automated verification and other applications based on automated reasoning. Current techniques for dealing with quantified formulas in SMT are generally incomplete, forcing SMT solvers to report “unknown” when they fail to prove the unsatisfiability of a formula with quantifiers. This inability to return counter models limits their usefulness in applications that produce queries involving quantified formulas. In this paper, we reduce these limitations by integrating finite model finding techniques based on constraint solving into the architecture used by modern SMT solvers. This approach is made possible by a novel solver for cardinality constraints, as well as techniques for on-demand instantiation of quantified formulas. Experiments show that our approach is competitive with the state of the art in SMT, and orthogonal to approaches in automated theorem proving.


Author(s):  
Heinz-Dieter Ebbinghaus ◽  
Jörg Flum

Author(s):  
Tengfei Li ◽  
Jing Liu ◽  
Haiying Sun ◽  
Xiang Chen ◽  
Lipeng Zhang ◽  
...  

AbstractIn the past few years, significant progress has been made on spatio-temporal cyber-physical systems in achieving spatio-temporal properties on several long-standing tasks. With the broader specification of spatio-temporal properties on various applications, the concerns over their spatio-temporal logics have been raised in public, especially after the widely reported safety-critical systems involving self-driving cars, intelligent transportation system, image processing. In this paper, we present a spatio-temporal specification language, STSL PC, by combining Signal Temporal Logic (STL) with a spatial logic S4 u, to characterize spatio-temporal dynamic behaviors of cyber-physical systems. This language is highly expressive: it allows the description of quantitative signals, by expressing spatio-temporal traces over real valued signals in dense time, and Boolean signals, by constraining values of spatial objects across threshold predicates. STSL PC combines the power of temporal modalities and spatial operators, and enjoys important properties such as finite model property. We provide a Hilbert-style axiomatization for the proposed STSL PC and prove the soundness and completeness by the spatio-temporal extension of maximal consistent set and canonical model. Further, we demonstrate the decidability of STSL PC and analyze the complexity of STSL PC. Besides, we generalize STSL to the evolution of spatial objects over time, called STSL OC, and provide the proof of its axiomatization system and decidability.


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