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dc.contributor.authorGorbovitski, Michaelen_US
dc.contributor.otherDepartment of Computer Scienceen_US
dc.date.accessioned2012-05-17T12:20:42Z
dc.date.available2012-05-17T12:20:42Z
dc.date.issued1-May-11en_US
dc.date.submittedMay-11en_US
dc.identifierGorbovitski_grad.sunysb_0771E_10423.pdfen_US
dc.identifier.urihttp://hdl.handle.net/1951/56010
dc.description.abstractTransformation systems are important for program manipulations such as optimization, instrumentation, and refactoring. Even though not always stated explicitly, these transformations are always driven by invariants, such as maintaining invariants for optimization, checking invariants for verification, and so on. This dissertation describes a system that allows coordinated transformations driven by invariants to be specified declaratively, as invariant rules, and applied automatically. We specially describe our implementation for applying invariant rules to Python and C programs, alias and type analyses developed for applying invariant rules, and a method for composing and optimizing invariant rules. We also describe successful applications of the system in generating efficient implementations from clear and modular specifications, in instrumenting programs for runtime invariant checking, query-based debugging, and profiling, and in code refactoring.en_US
dc.description.sponsorshipStony Brook University Libraries. SBU Graduate School in Department of Computer Science. Lawrence Martin (Dean of Graduate School).en_US
dc.formatElectronic Resourceen_US
dc.language.isoen_USen_US
dc.publisherThe Graduate School, Stony Brook University: Stony Brook, NY.en_US
dc.subject.lcshComputer Scienceen_US
dc.subject.otherAlias Analysis, Dynamic Languages, Incrementalization, Rule Composition, Transformation Systemsen_US
dc.titleA System for Invariant-Driven Transformationsen_US
dc.typeDissertationen_US
dc.description.advisorAdvisor(s): Yanhong A. Liu. Committee Member(s): Scott D. Stoller; Rob Johnson; John Field.en_US
dc.mimetypeApplication/PDFen_US


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