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dc.contributor.advisorDaniel N. Jackson.en_US
dc.contributor.authorDennis, Gregory D. (Gregory David), 1980-en_US
dc.contributor.otherMassachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.en_US
dc.date.accessioned2010-05-25T20:41:44Z
dc.date.available2010-05-25T20:41:44Z
dc.date.copyright2009en_US
dc.date.issued2009en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/55097
dc.descriptionThesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (p. 131-138).en_US
dc.description.abstractAll software verification techniques, from theorem proving to testing, share the common goal of establishing a program's correctness with both (1) a high degree of confidence and (2) a low cost to the user, two criteria in tension with one another. Theorem proving offers the benefit of high confidence, but requires significant expertise and effort from the user. Testing, on the other hand, can be performed for little cost, but low-cost testing does not yield high confidence in a program's correctness. Although many static analyses can quickly and with high confidence check a program's conformance to a specification, they achieve these goals by sacrificing the expressiveness of the specification. To date, static analyses have been largely limited to the detection of shallow properties that apply to a very large class of programs, such as absence of array-bound errors and conformance to API usage conventions. Few static analyses are capable of checking strong specifications, specifications whose satisfaction relies upon the program's precise behavior. This thesis presents a new program-analysis framework that allows a procedure in an object-oriented language to be automatically checked, with high confidence, against a strong specification of its behavior. The framework is based on an intermediate relational representation of code and an analysis that examines all executions of a procedure up to a bound on the size of the heap and the number of loop unrollings. If a counterexample is detected within the bound, it is reported to the user as a trace of the procedure, though defects outside the bound will be missed.en_US
dc.description.abstract(cont.) Unlike testing, many static analyses are not equipped with coverage metrics to detect which program behaviors the analysis failed to exercise. Our framework, in contrast, includes such a metric. When no counterexamples are found, the metric can report how thoroughly the code was covered. This information can, in turn, help the user change the bound on the analysis or strengthen the specification to make subsequent analyses more comprehensive.en_US
dc.description.statementofresponsibilityby Gregory D. Dennis.en_US
dc.format.extent138 p.en_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.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.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectElectrical Engineering and Computer Science.en_US
dc.titleA relational framework for bounded program verificationen_US
dc.typeThesisen_US
dc.description.degreePh.D.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.identifier.oclc587730355en_US


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