An efficient approach to computing fixpoints for complex program analysis

  • Authors:

  • Li-Ling Chen;Williams Ludwell Harrison, III

  • Affiliations:

  • Center for Supercomputing Research and Development, University of Illinois at Urbana-Champaign, 1308 West Main Street, Urbana, IL;Center for Supercomputing Research and Development, University of Illinois at Urbana-Champaign, 1308 West Main Street, Urbana, IL

  • Venue:
  • ICS '94 Proceedings of the 8th international conference on Supercomputing
  • Year:
  • 1994

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Abstract

A chief source of inefficiency in program analysis using abstract interpretation comes from the fact that a large context (i.e., problem state) is propagated from node to node during the course of an analysis. This problem can be addressed and largely alleviated by a technique we call context projection, which projects an input context for a node to the portion that is actually relevant and determines whether the node should be reevaluated based on the projected context. This technique reduces the cost of an evaluation and eliminates unnecessary evaluations. Therefore, the efficiency of computing fixpoints over general lattices is greatly improved. A specific method, reachability, is presented as an example to accomplish context projection. Experimental results using reachability show very convincing speedups (more than eight for larger programs) that demonstrate the practical significance of context projection.