Precise interprocedural analysis using random interpretation

ACM SIGPLAN Notices

Volumn 40, Issue 1, 2005, Pages 324-337

  Gulwani, Sumit ^a   Necula, George C ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Interprocedural Analysis; Interprocedural Value Numbering; Linear Relationships; Random Interpretation; Randomized Algorithm; Uninterpreted Functions

Indexed keywords

INTERPROCEDURAL ANALYSIS; INTERPROCEDURAL VALUE NUMBERING; LINEAR RELATIONSHIPS; RANDOM INTERPRETATION; RANDOMIZED ALGORITHMS; UNINTERPRETED FUNCTIONS;

COMPUTATIONAL COMPLEXITY; ERRORS; GRAPH THEORY; POLYNOMIALS; PROBABILITY; TRANSFER FUNCTIONS;

RANDOM PROCESSES;

EID: 17044391332     PISSN: 03621340     EISSN: None     Source Type: Journal    
DOI: 10.1145/1047659.1040332     Document Type: Conference Paper

References (20)

1. P. Briggs, K. D. Cooper, and L. T. Simpson. Value numbering. Software Practice and Experience, 27(6):701-724, June 1997.
2. P. Cousot and R. Cousot. Abstract interpretation: A unified lattice model for static analysis of programs by construction or approximation of fixpoints. In Proceedings of the 4th ACM Symposium on Principles of Programming Languages, pages 234-252, 1977.
3. R. Cytron, J. Ferrante, B. K. Rosen, M. N. Wegman, and F. K. Zadeck. Efficiently computing static single assignment form and the control dependence graph. ACM Transactions on Programming Languages and Systems, 13(4):451-490, Oct. 1990.
4. J. Y. Gil and A. Itai. The complexity of type analysis of object oriented programs. Lecture Notes in Computer Science, 1445:601-634, 1998.
5. S. Gulwani and G. C. Necula. Discovering affine equalities using random interpretation. In 30th ACM Symposium on Principles of Programming Languages, pages 74-84. ACM, Jan. 2003.
6. S. Gulwani and G. C. Necula. Global value numbering using random interpretation. In 31st ACM Symposium on Principles of Programming Languages, pages 342-352, Jan. 2004.
7. S. Gulwani and G. C. Necula. A polynomial-time algorithm for global value numbering. In 11th Static Analysis Symposium, volume 3148 of Lecture Notes in Computer Science. Springer, 2004.
8. S. Gulwani and G. C. Necula. Precise interprocedural analysis using random interpretation. Technical Report UCB//CSD-04-1353, University of California, Berkeley, 2004.
9. M. Karr. Affine relationships among variables of a program. In Acta Informatica, pages 133-151. Springer, 1976.
10. G. A. Kildall. A unified approach to global program optimization. In 1st ACM Symposium on Principles of Programming Language, pages 194-206. ACM, Oct. 1973.
11. W. Landi. Undecidability of static analysis. ACM Letters on Programming Languages and Systems, 1(4):323-337, Dec. 1992.
12. R. Motwani and P. Raghavan. Randomized Algorithms. Cambridge University Press, 1995.
13. S.S. Muchnick. Advanced Compiler Design and Implementation. Morgan Kaufmann, San Francisco, 2000.
14. M. Müller-Olm and H. Seidl. Precise interprocedural analysis through linear algebra. In 31st Annual ACM Symposium on Principles of Programming Languages, pages 330-341. ACM, Jan. 2004.
15. T. Reps. On the sequential nature of interprocedural program-analysis problems. Acta Informatica, 33(8):739-757, Nov. 1996.
16. T. Reps, S. Horwitz, and M. Sagiv. Precise interprocedural dataflow analysis via graph reachability. In 22nd ACM Symposium on POPL, pages 49-61. ACM, 1995.
17. B. K. Rosen, M. N. Wegman, and F. K. Zadeck. Global value numbers and redundant computations. In 15th ACM Symposium on Principles of Programming Languages, pages 12-27, 1988.
18. O. Rüthing, J. Knoop, and B. Steffen. Detecting equalities of variables: Combining efficiency with precision. In Static Analysis Symposium, volume 1694 of Lecture Notes in Computer Science, pages 232-247. Springer, 1999.
19. M. Sagiv, T. Reps, and S. Horwitz. Precise interprocedural dataflow analysis with applications to constant propagation. Theoretical Computer Science, 167(1-2):131-170, 30 Oct. 1996.
20. M. Sharir and A. Pnueli. Two approaches to interprocedural data flow analysis. In S.S. Muchnick and N.D. Jones, editors,. Program Flow Analysis: Theory and Applications, pages 189-234, 1981.