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Compositional pointer and escape analysis for Java programs

Authors:

Martin RinardAuthors Info & Claims

OOPSLA '99: Proceedings of the 14th ACM SIGPLAN conference on Object-oriented programming, systems, languages, and applications

Pages 187 - 206

https://doi.org/10.1145/320384.320400

Published: 01 October 1999 Publication History

Abstract

This paper presents a combined pointer and escape analysis algorithm for Java programs. The algorithm is based on the abstraction of points-to escape graphs, which characterize how local variables and fields in objects refer to other objects. Each points-to escape graph also contains escape information, which characterizes how objects allocated in one region of the program can escape to be accessed by another region. The algorithm is designed to analyze arbitrary regions of complete or incomplete programs, obtaining complete information for objects that do not escape the analyzed regions.

We have developed an implementation that uses the escape information to eliminate synchronization for objects that are accessed by only one thread and to allocate objects on the stack instead of in the heap. Our experimental results are encouraging. We were able to analyze programs tens of thousands of lines long. For our benchmark programs, our algorithms enable the elimination of between 24% and 67% of the synchronization operations. They also enable the stack allocation of between 22% and 95% of the objects.

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Cited By

Halalingaiah SSundaresan VMaier DNandivada V(2024)The ART of Sharing Points-to Analysis: Reusing Points-to Analysis Results Safely and EfficientlyProceedings of the ACM on Programming Languages10.1145/36898038:OOPSLA2(2606-2632)Online publication date: 8-Oct-2024
https://dl.acm.org/doi/10.1145/3689803
Ding BLi QZhang YTang FChen J(2024)MEA2: A Lightweight Field-Sensitive Escape Analysis with Points-to Calculation for GolangProceedings of the ACM on Programming Languages10.1145/36897598:OOPSLA2(1362-1389)Online publication date: 8-Oct-2024
https://dl.acm.org/doi/10.1145/3689759
Zhang YDhawal ONandivada VChiba SUgawa TLaemmel RPereira JMosses P(2024)Reducing Write Barrier Overheads for Orthogonal PersistenceProceedings of the 17th ACM SIGPLAN International Conference on Software Language Engineering10.1145/3687997.3695646(210-223)Online publication date: 17-Oct-2024
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cover image ACM Conferences

OOPSLA '99: Proceedings of the 14th ACM SIGPLAN conference on Object-oriented programming, systems, languages, and applications

October 1999

462 pages

ISBN:1581132387

DOI:10.1145/320384

Chairmen:
Brent Hailpern
IBM T. J. Watson Research Center
,
Linda M. Northrop
Carnegie Mellon Univ., Pittsburgh, PA
,
Editor:
A. Michael Berman

ACM SIGPLAN Notices Volume 34, Issue 10
Oct. 1999
460 pages
ISSN:0362-1340
EISSN:1558-1160
DOI:10.1145/320385
Chairman:
Brent Hailpern,
Editors:
A. Michael Berman,
Linda M. Northrop
Issue’s Table of Contents

Copyright © 1999 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGPLAN: ACM Special Interest Group on Programming Languages

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New York, NY, United States

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Published: 01 October 1999

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OOPSLA99: Conference on Object Oriented Programming Systems Languages and Applications

November 1 - 5, 1999

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OOPSLA '99 Paper Acceptance Rate 30 of 152 submissions, 20%;

Overall Acceptance Rate 268 of 1,244 submissions, 22%

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Cited By

Halalingaiah SSundaresan VMaier DNandivada V(2024)The ART of Sharing Points-to Analysis: Reusing Points-to Analysis Results Safely and EfficientlyProceedings of the ACM on Programming Languages10.1145/36898038:OOPSLA2(2606-2632)Online publication date: 8-Oct-2024
https://dl.acm.org/doi/10.1145/3689803
Ding BLi QZhang YTang FChen J(2024)MEA2: A Lightweight Field-Sensitive Escape Analysis with Points-to Calculation for GolangProceedings of the ACM on Programming Languages10.1145/36897598:OOPSLA2(1362-1389)Online publication date: 8-Oct-2024
https://dl.acm.org/doi/10.1145/3689759
Zhang YDhawal ONandivada VChiba SUgawa TLaemmel RPereira JMosses P(2024)Reducing Write Barrier Overheads for Orthogonal PersistenceProceedings of the 17th ACM SIGPLAN International Conference on Software Language Engineering10.1145/3687997.3695646(210-223)Online publication date: 17-Oct-2024
https://dl.acm.org/doi/10.1145/3687997.3695646
Anand AAdithya SRustagi SSeth PSundaresan VMaier DNandivada VThakur M(2024)Optimistic Stack Allocation and Dynamic Heapification for Managed RuntimesProceedings of the ACM on Programming Languages10.1145/36563898:PLDI(296-319)Online publication date: 20-Jun-2024
https://dl.acm.org/doi/10.1145/3656389
Anand AThakur M(2024)Partial program analysis for staged compilation systemsFormal Methods in System Design10.1007/s10703-024-00458-xOnline publication date: 13-Jun-2024
https://doi.org/10.1007/s10703-024-00458-x
Utture APalsberg JChandra SBlincoe KTonella P(2023)From Leaks to Fixes: Automated Repairs for Resource Leak WarningsProceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering10.1145/3611643.3616267(159-171)Online publication date: 30-Nov-2023
https://dl.acm.org/doi/10.1145/3611643.3616267
Liu JLiu JDi PWu DZheng HLiu AXue JJust RFraser G(2023)Hybrid Inlining: A Framework for Compositional and Context-Sensitive Static AnalysisProceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis10.1145/3597926.3598042(114-126)Online publication date: 12-Jul-2023
https://dl.acm.org/doi/10.1145/3597926.3598042
He DLu JXue J(2023)IFDS-based Context Debloating for Object-Sensitive Pointer AnalysisACM Transactions on Software Engineering and Methodology10.1145/357964132:4(1-44)Online publication date: 27-May-2023
https://dl.acm.org/doi/10.1145/3579641
Madhav C HCheramangalath U(2023)Memory leak detection using Heap Object Flow Graph (HOFG)Proceedings of the 16th Innovations in Software Engineering Conference10.1145/3578527.3578528(1-11)Online publication date: 23-Feb-2023
https://dl.acm.org/doi/10.1145/3578527.3578528
Keshani MGousios GProksch S(2023)Frankenstein: fast and lightweight call graph generation for software buildsEmpirical Software Engineering10.1007/s10664-023-10388-729:1Online publication date: 16-Nov-2023
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