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Title Pointer analysis : building a foundation for effective program analysis
Publication Date
Date Accessioned
Degree PhD
Discipline/Department Computer Sciences
Degree Level doctoral
University/Publisher University of Texas – Austin
Abstract Pointer analysis is a fundamental enabling technology for program analysis. By improving the scalability of precise pointer analysis we can make a positive impact across a wide range of program analyses used for many different purposes, including program verification and model checking, optimization and parallelization, program understanding, hardware synthesis, and more. In this thesis we present a suite of new algorithms aimed at improving pointer analysis scalability. These new algorithms make inclusion-based analysis (the most precise flow- and context-insensitive pointer analysis) over 4x faster while using 7x less memory than the previous state-of-the-art; they also enable flow-sensitive pointer analysis to handle programs with millions of lines of code, two orders of magnitude greater than the previous state-of-the-art. We present a formal framework for describing the space of pointer analysis approximations. The space of possible approximations is complex and multidimensional, and until now has not been well-defined in a formal manner. We believe that the framework is useful as a method to meaningfully compare the precision of the multitude of existing pointer analyses, as well as aiding in the systematic exploration of the entire space of approximations.
Subjects/Keywords Computer algorithms; Computer programs; Parallel programming (Computer science)
Contributors Lin, Yun Calvin (advisor)
Language en
Rights Copyright is held by the author. Presentation of this material on the Libraries' web site by University Libraries, The University of Texas at Austin was made possible under a limited license grant from the author who has retained all copyrights in the works.
Country of Publication us
Record ID handle:2152/18408
Repository texas
Date Indexed 2020-10-15
Grantor The University of Texas at Austin
Note [] text; [department] Computer Sciences;

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