References

  1. A.V. Aho, M.S. Lam, R. Sethi & J.D. Ullman (2007): Compilers: Principles, Techniques, and Tools, second edition. Pearson Education.
  2. A. A. Belevantsev, S. S. Gaisaryan & V. P. Ivannikov (2008): Construction of Speculative Optimization Algorithms. Programming and Computer Software 34(3), pp. 138–153, doi:10.1134/S036176880803002X.
  3. A. Ben-Israel & T.N.E. Greville (2003): Generalised Inverses, 2nd edition. Springer Verlag.
  4. A. Bhowmik & M. Franklin (2004): A General Compiler Framework for Speculative Multithreaded Processors. IEEE Transactions on Parallel and Distributed Syststems 15(8), pp. 713–724, doi:10.1109/TPDS.2004.26.
  5. S.L. Campbell & D. Meyer (1979): Generalized Inverse of Linear Transformations. Constable, London.
  6. P. Cousot & R. Cousot (1977): Abstract Interpretation: A Unified Lattice Model for Static Analysis of Programs by Construction or Approximation of Fixpoints. In: POPL'77, pp. 238–252, doi:10.1145/512950.512973.
  7. F. Deutsch (2001): Bet Approximation in Inner Product Spaces. CMS Books in Mathematics 7. Springer Verlag, New York — Berlin, doi:10.1007/978-1-4684-9298-9.
  8. A. Di Pierro, C. Hankin & H. Wiklicky (2007): Abstract Interpretation for Worst and Average Case Analysis. In: Program Analysis and Compilation, Theory and Practice, LNCS 4444. Springer Verlag, pp. 160–174, doi:10.1007/978-3-540-71322-7_8.
  9. A. Di Pierro, C. Hankin & H. Wiklicky (2007): A Systematic Approach to Probabilistic Pointer Analysis. In: Z. Shao: Proceedings of APLAS'07, LNCS 4807. Springer Verlag, pp. 335–350, doi:10.1007/978-3-540-76637-7_23.
  10. A. Di Pierro, C. Hankin & H. Wiklicky (2010): Probabilistic Semantics and Analysis. In: Formal Methods for Quantitative Aspects of Programming Languages, LNCS 6155. Springer Verlag, pp. 1–42, doi:10.1007/978-3-642-13678-8_1.
  11. A. Di Pierro, P. Sotin & H. Wiklicky (2008): Relational Analysis and Precision via Probabilistic Abstract Interpretation. In: C. Baier & A. Aldini: Proceedings of QAPL'08, Electronic Notes in Theoretical Computer Science. Elsevier, pp. 23–42, doi:10.1016/j.entcs.2008.11.017.
  12. A. Di Pierro & H. Wiklicky (2000): Concurrent Constraint Programming: Towards Probabilistic Abstract Interpretation. In: PPDP'00, pp. 127–138, doi:10.1145/351268.351284.
  13. M.-Y. Hung, P.-S. Chen, Y-S. Hwang, R. D.-C. Ju & J. K. Lee (2012): Support of Probabilistic Pointer Analysis in the SSA Form. IEEE Transactions on Parallel Distributed Syststems 23(12), pp. 2366–2379, doi:10.1109/TPDS.2012.73.
  14. M.Z. Kwiatkowska, G. Norman & D. Parker (2004): PRISM 2.0: A Tool for Probabilistic Model Checking. In: International Conference on Quantitative Evaluation of Systems (QEST 2004). IEEE Computer Society, pp. 322–323, doi:10.1109/QEST.2004.10016.
  15. J. Lin, T. Chen, W.-C. Hsu, P.-C. Yew, R. D.-C. Ju, T.-F. Ngai & S. Chan (2003): A compiler framework for speculative analysis and optimizations. In: Proceedings Conference on Programming Language Design and Implementation (PLDI), pp. 289–299, doi:10.1145/781131.781164.
  16. S. McFarling (1993): Combining Branch Predictors. Technical Report WLR TN-36. Digital.
  17. D. Nicolaescu, B. Salamat & A.V. Veidenbaum (2006): Fast Speculative Address Generation and Way Caching for Reducing L1 Data Cache Energy. In: Proceedings of the 24th International Conference on Computer Design (ICCD 2006). IEEE, pp. 101–107, doi:10.1109/ICCD.2006.4380801.
  18. F. Nielson, H. Riis Nielson & C. Hankin (1999): Principles of Program Analysis. Springer Verlag, Berlin – Heidelberg, doi:10.1007/978-3-662-03811-6.
  19. S. Roman (2005): Advanced Linear Algebra, 2nd edition. Springer Verlag.
  20. H. Styles & W. Luk (2004): Exploiting Program Branch Probabilities in Hardware Compilation. IEEE Transaction on Computers 53(11), pp. 1408–1419, doi:10.1109/TC.2004.96.

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