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A scalable mixed-level approach to dynamic analysis of C and C++ programs

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dc.contributor.advisor Michael D. Ernst. en_US
dc.contributor.author Guo, Philip Jia en_US
dc.contributor.other Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. en_US
dc.date.accessioned 2007-03-12T17:51:53Z
dc.date.available 2007-03-12T17:51:53Z
dc.date.copyright 2006 en_US
dc.date.issued 2006 en_US
dc.identifier.uri http://hdl.handle.net/1721.1/36767
dc.description Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006. en_US
dc.description Includes bibliographical references (p. 107-112). en_US
dc.description.abstract This thesis addresses the difficult task of constructing robust and scalable dynamic program analysis tools for programs written in memory-unsafe languages such as C and C++, especially those that are interested in observing the contents of data structures at run time. In this thesis, I first introduce my novel mixed-level approach to dynamic analysis, which combines the advantages of both source- and binary-based approaches. Second, I present a tool framework that embodies the mixed-level approach. This framework provides memory safety guarantees, allows tools built upon it to access rich source- and binary-level information simultaneously at run time, and enables tools to scale to large, real-world C and C++ programs on the order of millions of lines of code. Third, I present two dynamic analysis tools built upon my framework - one for performing value profiling and the other for performing dynamic inference of abstract types - and describe how they far surpass previous analyses in terms of scalability, robustness, and applicability. Lastly, I present several case studies demonstrating how these tools aid both humans and automated tools in several program analysis tasks: improving human understanding of unfamiliar code, invariant detection, and data structure repair. en_US
dc.description.statementofresponsibility by Philip Jia Guo. en_US
dc.format.extent 112 p. en_US
dc.language.iso eng en_US
dc.publisher Massachusetts Institute of Technology en_US
dc.rights 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. en_US
dc.rights.uri http://dspace.mit.edu/handle/1721.1/7582
dc.subject Electrical Engineering and Computer Science. en_US
dc.title A scalable mixed-level approach to dynamic analysis of C and C++ programs en_US
dc.type Thesis en_US
dc.description.degree M.Eng. en_US
dc.contributor.department Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. en_US
dc.identifier.oclc 78924529 en_US


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