Finding optimum abstractions in parametric dataflow analysis

  • Authors:
  • Xin Zhang;Mayur Naik;Hongseok Yang

  • Affiliations:
  • Georgia Institute of Technology, Atlanta, GA, USA;Georgia Institute of Technology, Atlanta, GA, USA;University of Oxford, Oxford, United Kingdom

  • Venue:
  • Proceedings of the 34th ACM SIGPLAN conference on Programming language design and implementation
  • Year:
  • 2013

Quantified Score

Hi-index 0.00

Visualization

Abstract

We propose a technique to efficiently search a large family of abstractions in order to prove a query using a parametric dataflow analysis. Our technique either finds the cheapest such abstraction or shows that none exists. It is based on counterexample-guided abstraction refinement but applies a novel meta-analysis on abstract counterexample traces to efficiently find abstractions that are incapable of proving the query. We formalize the technique in a generic framework and apply it to two analyses: a type-state analysis and a thread-escape analysis. We demonstrate the effectiveness of the technique on a suite of Java benchmark programs.