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Jack B. Dennis. Uhler, Richard Stephen Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science 2015-01-20T15:30:42Z 2015-01-20T15:30:42Z 2014 2014 http://hdl.handle.net/1721.1/92967 900007004 Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2014. This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. Cataloged from student-submitted PDF version of thesis. Includes bibliographical references (pages 177-182). Satisfiability (SAT) and Satisfiability Modulo Theories (SMT) have been leveraged in solving a wide variety of important and challenging combinatorial search problems, including automatic test generation, logic synthesis, model checking, program synthesis, and software verification. Though in principle SAT and SMT solvers simplify the task of developing practical solutions to these hard combinatorial search problems, in practice developing an application that effectively uses a SAT or SMT solver can be a daunting task. SAT and SMT solvers have limited support, if any, for queries described using the wide array of features developers rely on for describing their programs: procedure calls, loops, recursion, user-defined data types, recursively defined data types, and other mechanisms for abstraction, encapsulation, and modularity. As a consequence, developers cannot rely solely on the sophistication of SAT and SMT solvers to efficiently solve their queries; they must also optimize their own orchestration and construction of queries. This thesis presents Smten, a search primitive based on SAT and SMT that supports all the features of a modern, general purpose functional programming language. Smten exposes a simple yet powerful search interface for the Haskell programming language that accepts user-level constraints directly. We address the challenges of supporting general purpose, Turing-complete computation in search descriptions, and provide an approach for eciently evaluating Smten search using SAT and SMT solvers. We show that applications developed using Smten require significantly fewer lines of code and less developer effort for results comparable to standard SMT-based tools. by Richard S. Uhler. Ph.D. 182 pages eng Massachusetts Institute of Technology M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 Electrical Engineering and Computer Science. Smten and the art of satisfiability-based search Thesis application/pdf Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="d6290fc3-77c2-4103-9a92-7eb6ae7a0f60"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Smten and the art of satisfiability-based search</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2014</PublicationDate> <Authors> <Author> <DisplayName>Uhler, Richard Stephen</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Electrical Engineering and Computer Science.</Keyword> <Abstract>Satisfiability (SAT) and Satisfiability Modulo Theories (SMT) have been leveraged in solving a wide variety of important and challenging combinatorial search problems, including automatic test generation, logic synthesis, model checking, program synthesis, and software verification. Though in principle SAT and SMT solvers simplify the task of developing practical solutions to these hard combinatorial search problems, in practice developing an application that effectively uses a SAT or SMT solver can be a daunting task. SAT and SMT solvers have limited support, if any, for queries described using the wide array of features developers rely on for describing their programs: procedure calls, loops, recursion, user-defined data types, recursively defined data types, and other mechanisms for abstraction, encapsulation, and modularity. As a consequence, developers cannot rely solely on the sophistication of SAT and SMT solvers to efficiently solve their queries; they must also optimize their own orchestration and construction of queries. This thesis presents Smten, a search primitive based on SAT and SMT that supports all the features of a modern, general purpose functional programming language. Smten exposes a simple yet powerful search interface for the Haskell programming language that accepts user-level constraints directly. We address the challenges of supporting general purpose, Turing-complete computation in search descriptions, and provide an approach for eciently evaluating Smten search using SAT and SMT solvers. We show that applications developed using Smten require significantly fewer lines of code and less developer effort for results comparable to standard SMT-based tools.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>