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Polyvariant Flow Analysis with Constrained Types

  • Scott F. Smith
  • Tiejun Wang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1782)

Abstract

The basic idea behind improving the quality of a monovariant control flow analysis such as 0CFAis the concept of polyvariant analyses such asAgesen’s Cartesian Product Algorithm (CPA) and Shivers’ nCFA. In this paper we develop a novel framework for polyvariant flow analysis based on Aiken-Wimmers constrained type theory. We develop instantiations of our framework to formalize various polyvariant algorithms, including nCFA and CPA. With our CPA formalization, we show the call-graph based termination condition for CPA will not always guarantee termination. We then develop a novel termination condition and prove it indeed leads to a terminating algorithm. Additionally, we show how data polymorphism can be modeled in the framework, by defining a simple extension to CPA that incorporates data polymorphism.

Keywords

Type Variable Inference Rule Type Inference Data Polymorphism Call Site 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Scott F. Smith
    • 1
  • Tiejun Wang
    • 1
  1. 1.Department of Computer ScienceThe Johns Hopkins UniversityBaltimoreUSA

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