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Sound, complete and scalable path-sensitive analysis
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Conference on Programming Language Design and Implementation archive
Proceedings of the 2008 ACM SIGPLAN conference on Programming language design and implementation table of contents
Tucson, AZ, USA
SESSION: Session IX table of contents
Pages 270-280  
Year of Publication: 2008
ISBN:978-1-59593-860-2
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Authors
Isil Dillig  Stanford University, Stanford, CA, USA
Thomas Dillig  Stanford University, Stanford, CA, USA
Alex Aiken  Stanford University, Stanford, CA, USA
Sponsors
ACM: Association for Computing Machinery
SIGPLAN: ACM Special Interest Group on Programming Languages
Publisher
ACM  New York, NY, USA
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ABSTRACT

We present a new, precise technique for fully path- and context-sensitive program analysis. Our technique exploits two observations: First, using quantified, recursive formulas, path- and context-sensitive conditions for many program properties can be expressed exactly. To compute a closed form solution to such recursive constraints, we differentiate between observable and unobservable variables, the latter of which are existentially quantified in our approach. Using the insight that unobservable variables can be eliminated outside a certain scope, our technique computes satisfiability- and validity-preserving closed-form solutions to the original recursive constraints. We prove the solution is as precise as the original system for answering may and must queries as well as being small in practice, allowing our technique to scale to the entire Linux kernel, a program with over 6 million lines of code.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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M. Sharir and A. Pnueli. Two approaches to interprocedural data flow analysis. Program Flow Analysis: Theory and Applications, pages 189--234, 1981.
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Collaborative Colleagues:
Isil Dillig: colleagues
Thomas Dillig: colleagues
Alex Aiken: colleagues