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Towards scalable flow and context sensitive pointer analysis
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Source Annual ACM IEEE Design Automation Conference archive
Proceedings of the 42nd annual Design Automation Conference table of contents
Anaheim, California, USA
SESSION: Optimization techniques in high-level synthesis table of contents
Pages: 831 - 836  
Year of Publication: 2005
ISBN:1-59593-058-2
Author
Jianwen Zhu  University of Toronto, Toronto, Ontario, Canada
Sponsors
ACM: Association for Computing Machinery
SIGDA: ACM Special Interest Group on Design Automation
Publisher
ACM  New York, NY, USA
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ABSTRACT

Pointer analysis, a classic problem in software program analysis, has emerged as an important problem to solve in design automation, at a time when complex designs, specified in the form of C code, need to be synthesized or verified. However, precise pointer analysis algorithms that are both context and flow sensitive (FSCS), have not been shown to scale. In this paper, we report a new solution for FSCS analysis, which can evaluate the program states of all program points under billions of different calling paths. Our solution extends the recently proposed symbolic pointer analysis (SPA) technology, which exploits the efficiency of Binary Decision Diagrams (BDDs). With our new strategy of problem solving, called superposed symbolic computation, and its application on our generic pointer analysis framework, we are able to report the first result on all SPEC2000 benchmarks that completes context sensitive, flow insensitive analysis in seconds, and context sensitive, flow sensitive analysis in minutes.


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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