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Decision procedures = an algorithmic...

Kroening, Daniel.

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Decision procedures = an algorithmic point of view /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Decision procedures/ by Daniel Kroening, Ofer Strichman.
Reminder of title:	an algorithmic point of view /
Author:	Kroening, Daniel.
other author:	Strichman, Ofer.
Published:	Berlin, Heidelberg :Springer Berlin Heidelberg : : 2016.,
Description:	xxi, 356 p. :ill., digital ;24 cm.
[NT 15003449]:	Introduction and Basic Concepts -- Decision Procedures for Propositional Logic -- From Propositional to Quantifier-Free Theories -- Equalities and Uninterpreted Functions -- Linear Arithmetic -- Bit Vectors -- Arrays -- Pointer Logic -- Quantified Formulas -- Deciding a Combination of Theories -- Propositional Encodings -- Applications in Software Engineering -- SMT-LIB 2.0: A Brief Tutorial -- A C++ Library for Developing Decision Procedures.
Contained By:	Springer eBooks
Subject:	Decision making - Mathematical models. -
Online resource:	http://dx.doi.org/10.1007/978-3-662-50497-0
ISBN:	9783662504970

Decision procedures = an algorithmic point of view /
Kroening, Daniel.

Decision proceduresan algorithmic point of view /[electronic resource] :by Daniel Kroening, Ofer Strichman. - 2nd ed. - Berlin, Heidelberg :Springer Berlin Heidelberg :2016. - xxi, 356 p. :ill., digital ;24 cm. - Texts in theoretical computer science. an EATCS series,1862-4499. - Texts in theoretical computer science. an EATCS series..

Introduction and Basic Concepts -- Decision Procedures for Propositional Logic -- From Propositional to Quantifier-Free Theories -- Equalities and Uninterpreted Functions -- Linear Arithmetic -- Bit Vectors -- Arrays -- Pointer Logic -- Quantified Formulas -- Deciding a Combination of Theories -- Propositional Encodings -- Applications in Software Engineering -- SMT-LIB 2.0: A Brief Tutorial -- A C++ Library for Developing Decision Procedures.

A decision procedure is an algorithm that, given a decision problem, terminates with a correct yes/no answer. Here, the authors focus on theories that are expressive enough to model real problems, but are still decidable. Specifically, the book concentrates on decision procedures for first-order theories that are commonly used in automated verification and reasoning, theorem-proving, compiler optimization and operations research. The techniques described in the book draw from fields such as graph theory and logic, and are routinely used in industry. The authors introduce the basic terminology of SAT, Satisfiability Modulo Theories (SMT) and the DPLL(T) framework. Then, in separate chapters, they study decision procedures for propositional logic; equalities and uninterpreted functions; linear arithmetic; bit vectors; arrays; pointer logic; and quantified formulas. They also study the problem of deciding combined theories based on the Nelson-Oppen procedure. The first edition of this book was adopted as a textbook in courses worldwide. It was published in 2008 and the field now called SMT was then in its infancy, without the standard terminology and canonic algorithms it has now; this second edition reflects these changes. It brings forward the DPLL(T) framework. It also expands the SAT chapter with modern SAT heuristics, and includes a new section about incremental satisfiability, and the related Constraints Satisfaction Problem (CSP) The chapter about quantifiers was expanded with a new section about general quantification using E-matching and a section about Effectively Propositional Reasoning (EPR) The book also includes a new chapter on the application of SMT in industrial software engineering and in computational biology, coauthored by Nikolaj Bjorner and Leonardo de Moura, and Hillel Kugler, respectively. Each chapter includes a detailed bibliography and exercises. Lecturers' slides and a C++ library for rapid prototyping of decision procedures are available from the authors' website.

ISBN: 9783662504970

Standard No.: 10.1007/978-3-662-50497-0doiSubjects--Topical Terms:

565918
Decision making
--Mathematical models.

LC Class. No.: QA279.4 / .K76 2016

Dewey Class. No.: 519.542

Decision procedures = an algorithmic point of view /
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100 1 $a Kroening, Daniel. $3 900580
245 1 0 $a Decision procedures $h [electronic resource] : $b an algorithmic point of view / $c by Daniel Kroening, Ofer Strichman.
250 $a 2nd ed.
260 $a Berlin, Heidelberg : $b Springer Berlin Heidelberg : $b Imprint: Springer, $c 2016.
300 $a xxi, 356 p. : $b ill., digital ; $c 24 cm.
490 1 $a Texts in theoretical computer science. an EATCS series, $x 1862-4499
505 0 $a Introduction and Basic Concepts -- Decision Procedures for Propositional Logic -- From Propositional to Quantifier-Free Theories -- Equalities and Uninterpreted Functions -- Linear Arithmetic -- Bit Vectors -- Arrays -- Pointer Logic -- Quantified Formulas -- Deciding a Combination of Theories -- Propositional Encodings -- Applications in Software Engineering -- SMT-LIB 2.0: A Brief Tutorial -- A C++ Library for Developing Decision Procedures.
520 $a A decision procedure is an algorithm that, given a decision problem, terminates with a correct yes/no answer. Here, the authors focus on theories that are expressive enough to model real problems, but are still decidable. Specifically, the book concentrates on decision procedures for first-order theories that are commonly used in automated verification and reasoning, theorem-proving, compiler optimization and operations research. The techniques described in the book draw from fields such as graph theory and logic, and are routinely used in industry. The authors introduce the basic terminology of SAT, Satisfiability Modulo Theories (SMT) and the DPLL(T) framework. Then, in separate chapters, they study decision procedures for propositional logic; equalities and uninterpreted functions; linear arithmetic; bit vectors; arrays; pointer logic; and quantified formulas. They also study the problem of deciding combined theories based on the Nelson-Oppen procedure. The first edition of this book was adopted as a textbook in courses worldwide. It was published in 2008 and the field now called SMT was then in its infancy, without the standard terminology and canonic algorithms it has now; this second edition reflects these changes. It brings forward the DPLL(T) framework. It also expands the SAT chapter with modern SAT heuristics, and includes a new section about incremental satisfiability, and the related Constraints Satisfaction Problem (CSP) The chapter about quantifiers was expanded with a new section about general quantification using E-matching and a section about Effectively Propositional Reasoning (EPR) The book also includes a new chapter on the application of SMT in industrial software engineering and in computational biology, coauthored by Nikolaj Bjorner and Leonardo de Moura, and Hillel Kugler, respectively. Each chapter includes a detailed bibliography and exercises. Lecturers' slides and a C++ library for rapid prototyping of decision procedures are available from the authors' website.
650 0 $a Decision making $x Mathematical models. $3 565918
650 0 $a Algorithms. $3 536374
650 0 $a Logic, Symbolic and mathematical. $3 532051
650 1 4 $a Computer Science. $3 626642
650 2 4 $a Theory of Computation. $3 892514
650 2 4 $a Software Engineering/Programming and Operating Systems. $3 891214
650 2 4 $a Optimization. $3 891104
700 1 $a Strichman, Ofer. $3 900579
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a Texts in theoretical computer science. an EATCS series. $3 3200634
856 4 0 $u http://dx.doi.org/10.1007/978-3-662-50497-0
950 $a Computer Science (Springer-11645)