Article

Scaling Java points-to analysis using SPARK

Authors:

Ondřej Lhoták,

Laurie HendrenAuthors Info & Claims

CC'03: Proceedings of the 12th international conference on Compiler construction

Pages 153 - 169

Published: 07 April 2003 Publication History

Abstract

Most points-to analysis research has been done on different systems by different groups, making it difficult to compare results, and to understand interactions between individual factors each group studied. Furthermore, points-to analysis for Java has been studied much less thoroughly than for C, and the tradeoffs appear very different. We introduce SPARK, a flexible framework for experimenting with points-to analyses for Java. SPARK supports equality- and subset-based analyses, variations in field sensitivity, respect for declared types, variations in call graph construction, off-line simplification, and several solving algorithms. SPARK is composed of building blocks on which new analyses can be based.

We demonstrate SPARK in a substantial study of factors affecting precision and efficiency of subset-based points-to analyses, including interactions between these factors. Our results show that SPARK is not only flexible and modular, but also offers superior time/space performance when compared to other points-to analysis implementations.

References

[1]

Ashes suite collection. http://www.sable.mcgill.ca/software/.

[2]

jEdit: Open source programmer's text editor. http://www.jedit.org/.

[3]

Soot: a Java optimization framework. http://www.sable.mcgill.ca/soot/.

[4]

SPEC JVM98 benchmarks. http://www.spec.org/osg/jvm98/.

[5]

A. Aiken, M. Fähndrich, J. S. Foster, and Z. Su. Atoolkit for constructing type- and constraint-based program analyses. In Types in Compilation, Second International Workshop, TIC '98, volume 1473 of LNCS, pages 78-96, 1998.

Digital Library

[6]

L.O. Andersen. Program Analysis and Specialization for the C Programming Language. PhD thesis, University of Copenhagen, May 1994. (DIKU report 94/19).

[7]

D. F. Bacon and P. F. Sweeney. Fast static analysis of C++ virtual function calls. In Proceedings of the 1996 OOPSLA, pages 324-341, 1996.

Digital Library

[8]

M. Das. Unification-based pointer analysis with directional assignments. In Proceedings of PLDI'00, volume 35.5 of ACM Sigplan Notices, pages 35-46, June 2000.

Digital Library

[9]

J. Dean, D. Grove, and C. Chambers. Optimization of object-oriented programs using static class hierarchy analysis. In ECOOP'95--Object-Oriented Programming, 9th European Conference , volume 952 of LNCS, pages 77-101, Aug. 1995.

Digital Library

[10]

A. Diwan, K. S. McKinley, and J. E. B. Moss. Type-based alias analysis. In Proceedings of PLDI'98, pages 106-117, 1998.

Digital Library

[11]

M. Emami, R. Ghiya, and L. J. Hendren. Context-sensitive interprocedural points-to analysis in the presence of function pointers. In Proceedings of PLDI'94, pages 242-256, 1994.

Digital Library

[12]

M. Fähndrich, J. S. Foster, Z. Su, and A. Aiken. Partial online cycle elimination in inclusion constraint graphs. In Proceedings of PLDI'98, pages 85-96, June 1998.

Digital Library

[13]

N. Heintze. Analysis of large code bases: The compile-link-analyze model. http://cm.bell-labs.com/cm/cs/who/nch/cla.ps, 1999.

[14]

N. Heintze and O. Tardieu. Demand-driven pointer analysis. In Proceedings of PLDI'01, pages 24-34, 2001.

Digital Library

[15]

N. Heintze and O. Tardieu. Ultra-fast aliasing analysis using CLA:A million lines of C code in a second. In Proceedings of PLDI'01, volume 36.5 of ACM SIGPLAN Notices, pages 254-263, June 2001.

Digital Library

[16]

M. Hind. Pointer analysis: Haven't we solved this problem yet? In Proceedings of PASTE'01, pages 54-61, June 2001.

Digital Library

[17]

D. Liang, M. Pennings, and M. J. Harrold. Extending and evaluating flow-insensitive and context-insensitive points-to analyses for Java. In Proceedings of PASTE'01, pages 73-79, 2001.

Digital Library

[18]

P. Pominville, F. Qian, R. Vallée-Rai, L. Hendren, and C. Verbrugge. A framework for optimizing Java using attributes. In Compiler Construction (CC 2001), volume 2027 of LNCS, pages 334-554, 2001.

Digital Library

[19]

A. Rountev and S. Chandra. Off-line variable substitution for scaling points-to analysis. In Proceedings of PLDI'00, pages 47 - 56, Jun 2000.

Digital Library

[20]

A. Rountev, A. Milanova, and B. G. Ryder. Points-to analysis for Java using annotated constraints. In Proceedings of the 2001 OOPSLA, pages 43-55, 2001.

Digital Library

[21]

M. Shapiro and S. Horwitz. Fast and accurate flow-insensitive points-to analysis. In Conference Record of 24th POPL '97, pages 1-14, Jan. 1997.

Digital Library

[22]

B. Steensgaard. Points-to analysis in almost linear time. In Conference Record of 23rd POPL'96, pages 32-41, Jan. 1996.

Digital Library

[23]

Z. Su, M. Fähndrich, and A. Aiken. Projection merging: reducing redundancies in inclusion constraint graphs. In Proceedings of the 27th POPL'00, pages 81-95, 2000.

Digital Library

[24]

V. Sundaresan, L. Hendren, C. Razafimahefa, R. Vallée-Rai, P. Lam, E. Gagnon, and C. Godin. Practical virtual method call resolution for Java. In Proceedings of the 2000 OOPSLA, pages 264-280, 2000.

Digital Library

[25]

R. E. Tarjan. Efficiency of a good but not linear set union algorithm. Journal of the ACM (JACM), 22(2):215-225, 1975.

Digital Library

[26]

R. Vallée-Rai, E. Gagnon, L. J. Hendren, P. Lam, P. Pominville, and V. Sundaresan. Optimizing Java bytecode using the Soot framework: Is it feasible? In Compiler Construction (CC 2000), volume 1781 of LNCS, pages 18-34, 2000.

Digital Library

[27]

J. Whaley and M. Lam. An efficient inclusion-based points-to analysis for strictly-typed languages. In Static Analysis 9th International Symposium, SAS 2002, volume 2477 of LNCS, pages 180-195, 2002.

Digital Library

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Published In

cover image Guide Proceedings

CC'03: Proceedings of the 12th international conference on Compiler construction

April 2003

335 pages

ISBN:3540009043

Editor:
Görel Hedin
Lund University, Department of Computer Science, Lund, Sweden

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 07 April 2003

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