Advertisement

Using Combined Static Analysis and Profiling for Logic Program Execution Time Estimation

  • Edison Mera
  • Pedro López-García
  • Germán Puebla
  • Manuel Carro
  • Manuel Hermenegildo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4079)

Abstract

Predicting statically the running time of programs has many applications ranging from task scheduling in parallel execution to proving the ability of a program to meet strict time constraints. A starting point in order to attack this problem is to infer the computational complexity of such programs (or fragments thereof). This is one of the reasons why the development of static analysis techniques for inferring cost-related properties of programs (usually upper and/or lower bounds of actual costs) has received considerable attention.

Keywords

Execution Time Logic Program Cost Model Task Schedule Static Analysis Technique 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Craig, S.J., Leuschel, M.: Self-tuning resource aware specialisation for Prolog. In: Proc. of PPDP 2005, pp. 23–34. ACM Press, New York (2005)CrossRefGoogle Scholar
  2. 2.
    Debray, S.K., Lin, N.W.: Cost analysis of logic programs. ACM Transactions on Programming Languages and Systems 15(5), 826–875 (1993)CrossRefGoogle Scholar
  3. 3.
    Debray, S.K., López-García, P., Hermenegildo, M., Lin, N.-W.: Lower Bound Cost Estimation for Logic Programs. In: 1997 International Logic Programming Symposium, pp. 291–305. MIT Press, Cambridge (1997)Google Scholar
  4. 4.
    Hermenegildo, M., Albert, E., López-García, P., Puebla, G.: Abstraction Carrying Code and Resource-Awareness. In: Proc. of PPDP 2005. ACM Press, New York (2005)Google Scholar
  5. 5.
    Hermenegildo, M.V., Puebla, G., Bueno, F., López-García, P.: Integrated Program Debugging, Verification, and Optimization Using Abstract Interpretation (and The Ciao System Preprocessor). Science of Computer Programming 58(1-2), 115–140 (2005)MATHCrossRefMathSciNetGoogle Scholar
  6. 6.
    López-García, P., Hermenegildo, M., Debray, S.K.: A Methodology for Granularity Based Control of Parallelism in Logic Programs. J. of Symbolic Computation 22, 715–734 (1996) (Special Issue on Parallel Symbolic Computation)CrossRefGoogle Scholar
  7. 7.
    Mera, E., López-García, P., Puebla, G., Carro, M., Hermenegildo, M.: Towards Combining Static Analysis and Profiling for Estimating Execution Times in Logic Programs. Technical Report CLIP5/2006.0, Technical University of Madrid (UPM), School of Computer Science, UPM (April 2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Edison Mera
    • 1
  • Pedro López-García
    • 1
  • Germán Puebla
    • 1
  • Manuel Carro
    • 1
  • Manuel Hermenegildo
    • 1
    • 2
  1. 1.Technical University of Madrid 
  2. 2.University of New Mexico 

Personalised recommendations