Skip navigation
Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp0108612q910
Full metadata record
DC FieldValueLanguage
dc.contributor.advisorAppel, Andrew Wen_US
dc.contributor.authorDodds, Joeyen_US
dc.contributor.otherComputer Science Departmenten_US
dc.date.accessioned2015-12-08T15:23:40Z-
dc.date.available2015-12-08T15:23:40Z-
dc.date.issued2015en_US
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/dsp0108612q910-
dc.description.abstractAs it becomes more prevalent throughout our lives, correct software is more important than it has ever been before. Verifiable C is an expressive Hoare logic (higher-order impredicative concurrent separation logic) for proving functional correctness of C programs. The program logic is foundational---it is proved sound in Coq w.r.t. the operational semantics of CompCert Clight. Users apply the program logic to C programs using semiautomated tactics in Coq, but these tactics are very slow. This thesis shows how to make an efficient (yet still foundational) symbolic executor based on this separation logic by using computational reflection in several different ways. Our execution engine is able to interact gracefully with the user by reflecting application-specific proof goals back to the user for interactive proof---necessary in functional correctness proofs where there is almost always domain-specific reasoning to be done. We use our ``mostly sound'' type system, computationally efficient finite-map data structures, and the MirrorCore framework for computationally reflected logics. Measurements show a 40x performance improvement.en_US
dc.language.isoenen_US
dc.publisherPrinceton, NJ : Princeton Universityen_US
dc.relation.isformatofThe Mudd Manuscript Library retains one bound copy of each dissertation. Search for these copies in the library's main catalog: http://catalog.princeton.edu/en_US
dc.subjectCoqen_US
dc.subjectFormal Methodsen_US
dc.subjectFoundationalen_US
dc.subjectProgramming Languagesen_US
dc.subjectSymbolic Executionen_US
dc.subjectVerificationen_US
dc.subject.classificationComputer scienceen_US
dc.titleComputation Improves Interactive Symbolic Executionen_US
dc.typeAcademic dissertations (Ph.D.)en_US
pu.projectgrantnumber690-2143en_US
Appears in Collections:Computer Science

Files in This Item:
File Description SizeFormat 
Dodds_princeton_0181D_11583.pdf548.4 kBAdobe PDFView/Download


Items in Dataspace are protected by copyright, with all rights reserved, unless otherwise indicated.