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Scalable error detection using Boolean satisfiability (2005)
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| Venue: | In Proc. 32Ç È POPL. ACM |
| Citations: | 118 - 10 self |
BibTeX
@INPROCEEDINGS{Xie05scalableerror,
author = {Yichen Xie and Alex Aiken},
title = {Scalable error detection using Boolean satisfiability},
booktitle = {In Proc. 32Ç È POPL. ACM},
year = {2005}
}
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Abstract
We describe a software error-detection tool that exploits recent advances in boolean satisfiability (SAT) solvers. Our analysis is path sensitive, precise down to the bit level, and models pointers and heap data. Our approach is also highly scalable, which we achieve using two techniques. First, for each program function, several optimizations compress the size of the boolean formulas that model the control- and data-flow and the heap locations accessed by a function. Second, summaries in the spirit of type signatures are computed for each function, allowing inter-procedural analysis without a dramatic increase in the size of the boolean constraints to be solved. We demonstrate the effectiveness of our approach by constructing a lock interface inference and checking tool. In an interprocedural analysis of more than 23,000 lock related functions in the latest Linux kernel, the checker generated 300 warnings, of which 179 were unique locking errors, a false positive rate of only 40%.
Keyphrases
boolean satisfiability scalable error detection model pointer inter-procedural analysis linux kernel boolean formula several optimization false positive rate heap data unique locking error software error-detection tool boolean constraint program function lock interface inference heap location type signature bit level interprocedural analysis dramatic increase recent advance
