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A framework for combining analysis and verification
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Source Annual Symposium on Principles of Programming Languages archive
Proceedings of the 27th ACM SIGPLAN-SIGACT symposium on Principles of programming languages table of contents
Boston, MA, USA
Pages: 26 - 39  
Year of Publication: 2000
ISBN:1-58113-125-9
Authors
Nevin Heintze  Bell Laboratories, 600 Mountain Avenue, Murray Hill, NJ
Joxan Jaffar  School of Computing, National University of Singapore, Republic of Singapore 117543
Răzvan Voicu  School of Computing, National University of Singapore, Republic of Singapore 117543
Sponsors
SIGPLAN: ACM Special Interest Group on Programming Languages
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
Publisher
ACM  New York, NY, USA
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ABSTRACT

We present a general framework for combining program verification and program analysis. This framework enhances program analysis because it takes advantage of user assertions, and it enhances program verification because assertions can be refined using automatic program analysis. Both enhancements in general produce a better way of reasoning about programs than using verification techniques alone or analysis techniques alone. More importantly, the combination is better than simply running the verification and analysis in isolation and then combining the results at the last step. In other words, our framework explores synergistic interaction between verification and analysis. In this paper, we start with a representation of a program, user assertions, and a given analyzer for the program. The framework we describe induces an algorithm which exploits the assertions and the analyzer to produce a generally more accurate analysis. Further, it has some important features: it is flexible: any number of assertions can be used anywhere; it is open: it can employ an arbitrary analyzer; it is modular: we reason with conditional correctness of assertions; it is incremental: it can be tuned for the accuracy/efficiency tradeoff.


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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P. Cousot and R. Cousot. "Abstract Interpretation Frameworks" Journal of Logic and Computation, 2(4), 511-547, August 1992.
 
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D. Gries, "Science of Programming", Springer-Verlag, 1991.
 
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N. Heintze and J. Jaffar, "A Generic Algorithm for CLP Analysis", 12th International Conference on Logic Programming, 49-63, 1995.
 
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N. Heintze and J. Jaffar, "An Engine for Logic Program Analysis", Proc. 7th IEEE Syrup. on Logic in Computer Science, pp 318-328, 1992.
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Collaborative Colleagues:
Nevin Heintze: colleagues
Joxan Jaffar: colleagues
Răzvan Voicu: colleagues