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Elementary Probability Theory in the Eindhoven Style

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Mathematics of Program Construction (MPC 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7342))

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Abstract

We extend the Eindhoven quantifier notation to elementary probability theory by adding “distribution comprehensions” to it.

Even elementary theories can be used in complicated ways, and this occurs especially when reasoning about computer programs: an instance of this is the multi-level probabilistic structures that arise in probabilistic semantics for security.

Our exemplary case study in this article is therefore the probabilistic reasoning associated with a quantitative noninterference semantics based on Hidden Markov Models of computation. But we believe the proposal here will be more generally applicable than that, and so we also revisit a number of popular puzzles, to illustrate the new notation’s wider utility.

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References

  1. Cheng, S.: A crash course on the Lebesgue integral and measure theory (December 2011), www.gold-saucer.org/math/lebesgue/lebesgue.pdf

  2. Dijkstra, E.W.: A Discipline of Programming. Prentice-Hall (1976)

    Google Scholar 

  3. Dijkstra, E.W., Scholten, C.S.: Predicate Calculus and Program Semantics. Springer (1990)

    Google Scholar 

  4. Erwig, M., Kollmansberger, S.: Probabilistic functional programming in Haskell. Journal of Functional Programming 16, 21–34 (2006)

    Article  MATH  Google Scholar 

  5. Fremlin, D.H.: Measure Theory. Torres Fremlin (2000)

    Google Scholar 

  6. Gibbons, J., Hinze, R.: Just do it: simple monadic equational reasoning. In: Chakravarty, M.M.T., Hu, Z., Danvy, O. (eds.) ICFP, pp. 2–14. ACM (2011)

    Google Scholar 

  7. Giry, M.: A categorical approach to probability theory. In: Categorical Aspects of Topology and Analysis. Lecture Notes in Mathematics, vol. 915, pp. 68–85. Springer (1981)

    Google Scholar 

  8. Goguen, J.A., Meseguer, J.: Unwinding and inference control. In: Proc. IEEE Symp. on Security and Privacy, pp. 75–86. IEEE Computer Society (1984)

    Google Scholar 

  9. Hehner, E.C.R.: A probability perspective. Form. Asp. Comput. 23, 391–419 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  10. Jones, C., Plotkin, G.: A probabilistic powerdomain of evaluations. In: Proceedings of the IEEE 4th Annual Symposium on Logic in Computer Science, pp. 186–195. Computer Society Press, Los Alamitos (1989)

    Chapter  Google Scholar 

  11. Jurafsky, D., Martin, J.H.: Speech and Language Processing. Prentice Hall International (2000)

    Google Scholar 

  12. Kiselyov, O., Shan, C.-C.: Embedded probabilistic programming. In: Taha, W.M. (ed.) DSL 2009. LNCS, vol. 5658, pp. 360–384. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  13. E Kowalski. Measure and integral (December 2011), www.math.ethz.ch/~kowalski/measure-integral.pdf

  14. McIver, A.K., Morgan, C.C.: Abstraction, Refinement and Proof for Probabilistic Systems. Tech. Mono. Comp. Sci. Springer, New York (2005)

    MATH  Google Scholar 

  15. McIver, A., Meinicke, L., Morgan, C.: Compositional closure for bayes risk in probabilistic noninterference. In: Abramsky, S., Gavoille, C., Kirchner, C., Meyer auf der Heide, F., Spirakis, P.G. (eds.) ICALP 2010. LNCS, vol. 6199, pp. 223–235. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  16. McIver, A., Meinicke, L., Morgan, C.: Hidden-Markov program algebra with iteration. At arXiv:1102.0333v1; to appear in Mathematical Structures in Computer Science in 2012 (2011)

    Google Scholar 

  17. McIver, A., Meinicke, L., Morgan, C.: A Kantorovich-monadic powerdomain for information hiding, with probability and nondeterminism. In: Proc. Logic in Computer Science, LiCS (2012)

    Google Scholar 

  18. Morgan, C.: Compositional noninterference from first principles. Formal Aspects of Computing, pp. 1–24 (2010), dx.doi.org/10.1007/s00165-010-0167-y

  19. Morgan, C.: The shadow knows: refinement of ignorance in sequential programs. In: Yu, H.-J. (ed.) MPC 2006. LNCS, vol. 4014, pp. 359–378. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  20. Morgan, C.C.: The shadow knows: refinement of ignorance in sequential programs. Science of Computer Programming 74(8), 629–653 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  21. Morgan, C.C., McIver, A.K., Seidel, K.: Probabilistic predicate transformers. ACM Trans. Prog. Lang. Sys. 18(3), 325–353 (1996), doi.acm.org/10.1145/229542.229547

    Article  Google Scholar 

  22. Ramsey, N., Pfeffer, A.: Stochastic lambda calculus and monads of probability distributions. SIGPLAN Not. 37, 154–165 (2002)

    Article  Google Scholar 

  23. Smith, G.: Adversaries and Information Leaks (Tutorial). In: Barthe, G., Fournet, C. (eds.) TGC 2007. LNCS, vol. 4912, pp. 383–400. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

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Morgan, C. (2012). Elementary Probability Theory in the Eindhoven Style. In: Gibbons, J., Nogueira, P. (eds) Mathematics of Program Construction. MPC 2012. Lecture Notes in Computer Science, vol 7342. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31113-0_5

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  • DOI: https://doi.org/10.1007/978-3-642-31113-0_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31112-3

  • Online ISBN: 978-3-642-31113-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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