Semi-sparse flow-sensitive pointer analysis

  • Authors:
  • Ben Hardekopf;Calvin Lin

  • Affiliations:
  • The University of Texas at Austin, Austin, TX, USA;The University of Texas at Austin, Austin, TX, USA

  • Venue:
  • Proceedings of the 36th annual ACM SIGPLAN-SIGACT symposium on Principles of programming languages
  • Year:
  • 2009

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Abstract

Pointer analysis is a prerequisite for many program analyses, and the effectiveness of these analyses depends on the precision of the pointer information they receive. Two major axes of pointer analysis precision are flow-sensitivity and context-sensitivity, and while there has been significant recent progress regarding scalable context-sensitive pointer analysis, relatively little progress has been made in improving the scalability of flow-sensitive pointer analysis. This paper presents a new interprocedural, flow-sensitive pointer analysis algorithm that combines two ideas-semi-sparse analysis and a novel use of BDDs-that arise from a careful understanding of the unique challenges that face flow-sensitive pointer analysis. We evaluate our algorithm on 12 C benchmarks ranging from 11K to 474K lines of code. Our fastest algorithm is on average 197x faster and uses 4.6x less memory than the state of the art, and it can analyze programs that are an order of magnitude larger than the previous state of the art.