Level by level: making flow- and context-sensitive pointer analysis scalable for millions of lines of code

  • Authors:

  • Hongtao Yu;Jingling Xue;Wei Huo;Xiaobing Feng;Zhaoqing Zhang

  • Affiliations:

  • Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China;University of New South Wales, Australia, Sydney, Australia;Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China;Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China;Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China

  • Venue:
  • Proceedings of the 8th annual IEEE/ACM international symposium on Code generation and optimization
  • Year:
  • 2010

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Abstract

We present a practical and scalable method for flow- and context-sensitive (FSCS) pointer analysis for C programs. Our method analyzes the pointers in a program level by level in terms of their points-to levels, allowing the points-to relations of the pointers at a particular level to be discovered based on the points-to relations of the pointers at this level and higher levels. This level-by-level strategy can enhance the scalability of the FSCS pointer analysis in two fundamental ways, by enabling (1) fast and accurate flow-sensitive analysis on full sparse SSA form using a flow-insensitive algorithm and (2) fast and accurate context-sensitive analysis using a full transfer function and a meet function for each procedure. Our level-by-level algorithm, LevPA, gives rises to (1) a precise and compact SSA representation for subsequent program analysis and optimization tasks and (2) a flow- and context-sensitive MAY/MUST mod (modification) set and read set for each procedure. Our preliminary results show that LevPA can analyze some programs with over a million lines of C code in minutes, faster than the state-of-the-art FSCS methods.