Interprocedural dataflow analysis in the presence of large libraries

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3923 LNCS, Issue , 2006, Pages 2-16

  Rountev, Atanas ^a   Kagan, Scott ^a   Marlowe, Thomas ^b  

^a OHIO STATE UNIVERSITY   (United States)

^b SETON HALL UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER PROGRAMMING; COMPUTER SOFTWARE REUSABILITY; DATA FLOW ANALYSIS; INFORMATION ANALYSIS; LIBRARIES;

COMPONENT-LEVEL ANALYSIS; LIBRARY COMPONENTS; SOFTWARE OPTIMIZATION; WHOLE-PROGRAM ANALYSIS;

COMPUTER SOFTWARE;

EID: 33745786611     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11688839_2     Document Type: Conference Paper

References (31)

1. D. Callahan. The program summary graph and (low-sensitive interproccdural data flow analysis. In Conf. Programming Language Design and implementation, pages 47-56, 1988.
2. R. Chatterjee, B. G. Ryder, and W. Landi. Relevant context inference. In Symp. Principles of Programming Languages, pages 133-146, 1999.
3. B. Cheng and W. Hwu. Modular interprocedural pointer analysis using access paths. In Conf. Programming Language Design and Implementation, 2000.
4. J. Choi, M. Gupta, M. Serrano, V. Sreedhar, and S. Midkiff. Escape analysis for Java. In Conf. Object-Oriented Programming Systems, Languages, and Applications, pages 1-19, 1999.
5. M. Codish, S. Debray, and R. Giacobazzi. Compositional analysis of modular logic programs. In Symp. Principles of Programming Languages, pages 451-464, 1993.
6. M. Das. Unification-based pointer analysis with directional assignments. In Conf. Programming Language Design and Implementation, pages 35-46, 2000.
7. D. Dhamdhere, B. Rosen, and K. Zadeck. How to analyze large programs efficiently and informatively. In Conf. Programming Language Design and Implementation, pages 212-223, 1992.
8. C. Flanagan and M. Felleisen. Componential set-based analysis. ACM Trans. Programming Languages and Systems, 21(2):370-416, Mar. 1999.
9. D. Grove and C. Chambers. A framework for call graph construction algorithms. ACM Trans. Programming Languages and Systems, 23(6):685-746, Nov. 2001.
10. D. Grove and L. Torczon. Interprocedural constant propagation: a study of jump function implementation. In Conf. Programming Language Design and Implementation, pages 90-99, 1993.
11. M. J. Harrold and G. Rothermel. Separate computation of alias information for reuse. IEEE Tran. Software Engineering, 22(7):442-460, July 1996.
12. N. Heintze and O. Tardieu. Ultra-fast aliasing analysis using CLA. In Conf. Programming Language Design and Implementation, pages 254-263, 2001.
13. F. C. Kuck. Class analysis for extensible Java software. Master's thesis, Ohio State University, Sept. 2004.
14. Y.-F. Lee and B. G. Ryder. A comprehensive approach to parallel data flow analysis. In Int. Conf. Supercomputing, pages 236-247, 1992.
15. O. Lhoták and L. Hendren. Scaling Java points-to analysis using Spark. In Int. Conf. Compiler Construction, LNCS 2622, pages 153-169, 2003.
16. T. J. Marlowe and B. G. Ryder. An efficient hybrid algorithm for incremental data flow analysis. In Symp. Principles of Programming Languages, pages 184-196, 1990.
17. A. Milanova, A. Rountev, and B. G. Ryder. Precise call graphs for C programs with function pointers. Int. J. Automated Software Engineering, 11(1):7-26, 2004.
18. T. Reps, S. Horwitz, and M. Sagiv. Precise interprocedural dataflow analysis via graph reachability. In Symp. Principles of Programming Languages, p. 49-61, 1995.
19. T. Reps, M. Sagiv, and S. Horwitz. Interprocedural dataflow analysis via graph reachability. Technical Report TR 94-14, Datalogisk Institut, University of Copenhagen, Apr. 1994.
20. A. Rountev. Component-level dataflow analysis. In Int. Symp. Component-Based Software Engineering, LNCS 3489, pages 82-89, 2005.
21. A. Rountev and B. H. Connell. Object naming analysis for reverse-engineered sequence diagrams. In Int. Conf. Software Engineering, pages 254-263, 2005.
22. A. Rountev, S. Kagan, and T. Marlowe. Interprocedural dataflow analysis in the presence of large libraries. Technical Report OSU-CISRC-1/06-TR01, Jan. 2006.
23. A. Rountev, A. Milanova, and B. G. Ryder. Fragment class analysis for testing of polymorphism in Java software. IEEE Tran. Software Engineering, 30(6):372-387, June 2004.
24. A. Rountev and B. G. Ryder. Points-to and side-effect analyses for programs built with precompiled libraries. In Int. Conf. Compiler Construction, LNCS 2027, pages 20-36, 2001.
25. E. Ruf. Effective synchronization removal for Java. In Conf. Programming Language Design and Implementation, pages 208-218, 2000.
26. B. G. Ryder and M. C. Paull. Elimination algorithms for data flow analysis. ACM Computing Surveys, 18(3):277-316, 1986.
27. M. Sagiv, T. Reps, and S. Horwitz. Precise interprocedural dataflow analysis with applications to constant propagation. Theoretical Comp. Sci., 167:131-170, 1996.
28. M. Sharir and A. Pnueli. Two approaches to interprocedural data flow analysis. In Program Flow Analysis: Theory and Applications, pages 189-234. 1981.
29. F. Tip, P. Sweeney, C. Laffra, A. Eisma, and D. Streeter. Practical extraction techniques for Java. ACM Trans. Programming Languages and Systems, 24(6):625-666, 2002.
30. R. Vallée-Rai, E. Gagnon, L. Hendren, P. Lam, P. Pominville, and V. Sundaresan. Optimizing Java bytecode using the Soot framework: Is it feasible? In Int. Conf. Compiler Construction, LNCS 1781, pages 18-34, 2000.
31. J. Whaley and M. Rinard. Compositional pointer and escape analysis for Java programs. In Conf. Object-Oriented Programming Systems, Languages, and Applications, pages 187-206, 1999.