A Parametric Interpolation Framework for First-Order Theories
Paper in proceedings, 2013

Craig interpolation is successfully used in both hardware and software model checking. Generating good interpolants, and hence automatic understanding of the quality of interpolants is however a very hard problem, requiring non-trivial reasoning in first-order theories. An important class of state-of-the-art interpolation algorithms is based on recursive procedures that generate interpolants from refutations of unsatisfiable conjunctions of formulas. We analyze this type of algorithms and develop a theoretical framework, called a parametric interpolation framework, for arbitrary first-order theories and inference systems. As interpolation-based verification approaches depend on the quality of interpolants, our method can be used to derive interpolants of different structure and strength, with or without quantifiers, from the same proof. We show that some well-known interpolation algorithms are instantiations of our framework.

first-order logic

theorem proving

interpolation

formal methods

program verification

Author

Laura Kovacs

Chalmers, Computer Science and Engineering (Chalmers), Software Technology (Chalmers)

Natasha Sharygina

Simone Fulvio Rollini

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

03029743 (ISSN) 16113349 (eISSN)

Vol. LNCS 8265 PART 1 24-40

Areas of Advance

Information and Communication Technology

Subject Categories

Computer and Information Science

Software Engineering

Computer Science

DOI

10.1007/978-3-642-45114-0_3

ISBN

978-3-642-45113-3

More information

Created

10/8/2017