Parallelizing Flow-Sensitive Demand-Driven Points-to Analysis

Haibo Yu, Qiang Sun, Kejun Xiao, Yuting Chen, Tsunenori Mine, Jianjun Zhao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Ahstract-Points-to analysis is a fundamental, but computationally intensive technique for static program analysis, optimization, debugging and verification. Context-Free Language (CFL) reachability has been proposed and widely used in demand-driven points-to analyses that aims for computing specific points-to relations on demand rather than all variables in the program. However, CFL-reachability-based points-to analysis still faces challenges when applied in practice especially for flow-sensitive points-to analysis, which aims at improving the precision of points-to analysis by taking account of the execution order of program statements. We propose a scalable approach named Parseeker to parallelize flow-sensitive demand-driven points-to analysis via CFL-reachability in order to improve the performance of points-to analysis with high precision. Our core insights are to (1) produce and process a set of fine-grained, parallelizable queries of points-to relations for the objective program, and (2) take a CFL-reachability-based points-to analysis to answer each query. The MapReduce is used to parallelize the queries and three optimization strategies are designed for further enhancing the efficiency.

Original languageEnglish
Title of host publicationProceedings - Companion of the 2020 IEEE 20th International Conference on Software Quality, Reliability, and Security, QRS-C 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages91-97
Number of pages7
ISBN (Electronic)9781728189154
DOIs
Publication statusPublished - Dec 2020
Event20th IEEE International Conference on Software Quality, Reliability, and Security, QRS 2020 - Macau, China
Duration: Dec 11 2020Dec 14 2020

Publication series

NameProceedings - Companion of the 2020 IEEE 20th International Conference on Software Quality, Reliability, and Security, QRS-C 2020

Conference

Conference20th IEEE International Conference on Software Quality, Reliability, and Security, QRS 2020
CountryChina
CityMacau
Period12/11/2012/14/20

All Science Journal Classification (ASJC) codes

  • Software
  • Safety, Risk, Reliability and Quality

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