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Control-flow refinement and progress invariants for bound analysis
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Conference on Programming Language Design and Implementation archive
Proceedings of the 2009 ACM SIGPLAN conference on Programming language design and implementation table of contents
Dublin, Ireland
SESSION: Program analysis and invariants table of contents
Pages 375-385  
Year of Publication: 2009
ISBN:978-1-60558-392-1
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Authors
Sumit Gulwani  Microsoft Research, Redmond, Redmond, WA, USA
Sagar Jain  IIT Kanpur, Kanpur, India
Eric Koskinen  University of Cambridge, Cambridge, United Kingdom
Sponsors
SIGPLAN: ACM Special Interest Group on Programming Languages
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

Symbolic complexity bounds help programmers understand the performance characteristics of their implementations. Existing work provides techniques for statically determining bounds of procedures with simple control-flow. However, procedures with nested loops or multiple paths through a single loop are challenging.

In this paper we describe two techniques, control-flow refinement and progress invariants, that together enable estimation of precise bounds for procedures with nested and multi-path loops. Control-flow refinement transforms a multi-path loop into a semantically equivalent code fragment with simpler loops by making the structure of path interleaving explicit. We show that this enables non-disjunctive invariant generation tools to find a bound on many procedures for which previous techniques were unable to prove termination. Progress invariants characterize relationships between consecutive states that can arise at a program location. We further present an algorithm that uses progress invariants to compute precise bounds for nested loops. The utility of these two techniques goes beyond our application to symbolic bound analysis. In particular, we discuss applications of control-flow refinement to proving safety properties that otherwise require disjunctive invariants.

We have applied our methodology to over 670,000 lines of code of a significant Microsoft product and were able to find symbolic bounds for 90% of the loops. We are not aware of any other published results that report experiences running a bound analysis on a real code-base.


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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Collaborative Colleagues:
Sumit Gulwani: colleagues
Sagar Jain: colleagues
Eric Koskinen: colleagues