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dc.contributor.authorMilicevic, Aleksandar
dc.contributor.authorNear, Joseph P
dc.contributor.authorKang, Eunsuk
dc.contributor.authorJackson, Daniel
dc.date.accessioned2021-10-27T20:29:01Z
dc.date.available2021-10-27T20:29:01Z
dc.date.issued2019
dc.identifier.urihttps://hdl.handle.net/1721.1/135729
dc.description.abstract© 2017, Springer Science+Business Media New York. The last decade has seen a dramatic growth in the use of constraint solvers as a computational mechanism, not only for analysis of software, but also at runtime. Solvers are available for a variety of logics but are generally restricted to first-order formulas. Some tasks, however, most notably those involving synthesis, are inherently higher order; these are typically handled by embedding a first-order solver (such as a SAT or SMT solver) in a domain-specific algorithm. Using strategies similar to those used in such algorithms, we show how to extend a first-order solver (in this case Kodkod, a model finder for relational logic used as the engine of the Alloy Analyzer) so that it can handle quantifications over higher-order structures. The resulting solver is sufficiently general that it can be applied to a range of problems; it is higher order, so that it can be applied directly, without embedding in another algorithm; and it performs well enough to be competitive with specialized tools. Just as the identification of first-order solvers as reusable backends advanced the performance of specialized tools and simplified their architecture, factoring out higher-order solvers may bring similar benefits to a new class of tools.
dc.language.isoen
dc.publisherSpringer Science and Business Media LLC
dc.relation.isversionof10.1007/S10703-016-0267-2
dc.rightsCreative Commons Attribution-Noncommercial-Share Alike
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/
dc.sourceMIT web domain
dc.titleAlloy*: a general-purpose higher-order relational constraint solver
dc.typeArticle
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
dc.relation.journalFormal Methods in System Design
dc.eprint.versionAuthor's final manuscript
dc.type.urihttp://purl.org/eprint/type/JournalArticle
eprint.statushttp://purl.org/eprint/status/PeerReviewed
dc.date.updated2019-05-31T17:21:19Z
dspace.orderedauthorsMilicevic, A; Near, JP; Kang, E; Jackson, D
dspace.date.submission2019-05-31T17:21:20Z
mit.journal.volume55
mit.journal.issue1
mit.metadata.statusAuthority Work and Publication Information Needed


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