Towards scalable flow and context sensitive pointer analysis

  • Authors:
  • Jianwen Zhu

  • Affiliations:
  • University of Toronto, Toronto, Ontario, Canada

  • Venue:
  • Proceedings of the 42nd annual Design Automation Conference
  • Year:
  • 2005

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Abstract

Pointer analysis, a classic problem in software program analysis, has emerged as an important problem to solve in design automation, at a time when complex designs, specified in the form of C code, need to be synthesized or verified. However, precise pointer analysis algorithms that are both context and flow sensitive (FSCS), have not been shown to scale. In this paper, we report a new solution for FSCS analysis, which can evaluate the program states of all program points under billions of different calling paths. Our solution extends the recently proposed symbolic pointer analysis (SPA) technology, which exploits the efficiency of Binary Decision Diagrams (BDDs). With our new strategy of problem solving, called superposed symbolic computation, and its application on our generic pointer analysis framework, we are able to report the first result on all SPEC2000 benchmarks that completes context sensitive, flow insensitive analysis in seconds, and context sensitive, flow sensitive analysis in minutes.