License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.ECOOP.2021.16
URN: urn:nbn:de:0030-drops-140592
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2021/14059/
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He, Dongjie ; Lu, Jingbo ; Gao, Yaoqing ; Xue, Jingling

Accelerating Object-Sensitive Pointer Analysis by Exploiting Object Containment and Reachability

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Abstract

Object-sensitive pointer analysis for an object-oriented program can be accelerated if context-sensitivity can be selectively applied to some precision-critical variables/objects in the program. Existing pre-analyses, which are performed to make such selections, either preserve precision but achieve limited speedups by reasoning about all the possible value flows in the program conservatively or achieve greater speedups but sacrifice precision (often unduly) by examining only some but not all the value flows in the program heuristically. In this paper, we introduce a new approach, named Turner, that represents a sweet spot between the two existing ones, as it is designed to enable object-sensitive pointer analysis to run significantly faster than the former approach and achieve significantly better precision than the latter approach. Turner is simple, lightweight yet effective due to two novel aspects in its design. First, we exploit a key observation that some precision-uncritical objects can be approximated based on the object-containment relationship pre-established (by applying Andersen’s analysis). This approximation introduces a small degree yet the only source of imprecision into Turner. Second, leveraging this initial approximation, we introduce a simple DFA to reason about object reachability for a method intra-procedurally from its entry to its exit along all the possible value flows established by its statements to finalize its precision-critical variables/objects identified. We have validated Turner with an implementation in Soot against the state of the art using a set of 12 popular Java benchmarks and applications.

BibTeX - Entry

@InProceedings{he_et_al:LIPIcs.ECOOP.2021.16,
  author =	{He, Dongjie and Lu, Jingbo and Gao, Yaoqing and Xue, Jingling},
  title =	{{Accelerating Object-Sensitive Pointer Analysis by Exploiting Object Containment and Reachability}},
  booktitle =	{35th European Conference on Object-Oriented Programming (ECOOP 2021)},
  pages =	{16:1--16:31},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-190-0},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{194},
  editor =	{M{\o}ller, Anders and Sridharan, Manu},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2021/14059},
  URN =		{urn:nbn:de:0030-drops-140592},
  doi =		{10.4230/LIPIcs.ECOOP.2021.16},
  annote =	{Keywords: Object-Sensitive Pointer Analysis, CFL Reachability, Object Containment}
}

Keywords: Object-Sensitive Pointer Analysis, CFL Reachability, Object Containment
Collection: 35th European Conference on Object-Oriented Programming (ECOOP 2021)
Issue Date: 2021
Date of publication: 06.07.2021
Supplementary Material: Software (ECOOP 2021 Artifact Evaluation approved artifact): https://doi.org/10.4230/DARTS.7.2.12

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