Advanced Functional Programming: 6th International School, by Umut A. Acar, Ruy Ley-Wild (auth.), Pieter Koopman, Rinus PDF

By Umut A. Acar, Ruy Ley-Wild (auth.), Pieter Koopman, Rinus Plasmeijer, Doaitse Swierstra (eds.)

This educational booklet offers seven conscientiously revised lectures given on the sixth foreign tuition on sensible Programming, AFP 2008, in Heijen, The Netherlands in may possibly 2008.

The e-book provides the next seven, conscientiously cross-reviewed chapters, written by means of top experts within the box: Self-adjusting: Computation with Delta ML, spider spinning for dummies, from reduction-based to reduction-free normalization, libraries for everyday programming in Haskell, dependently typed programming in agda, parallel and concurrent programming in Haskell and an iTask case research: a convention administration system.

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Extra resources for Advanced Functional Programming: 6th International School, AFP 2008, Heijen, The Netherlands, May 2008, Revised Lectures

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The function dist computes the distance between two circles. To compute the diameter, we need some auxilary functions. The function farthestFrom takes a circle c and a list of circles l and returns the circle that is farthest away from c. The function computes its result by first calculating the distance between each circle in the list and c (by using map over the list of circles) and then selecting the maximum of the list (by using reduce on the list). Since the function performs calls to adaptive functions, it itself is an adaptive function.

In: Automata, Languages and Programming, pp. 270–280 (1997) 18. : Maintaining information in fully-dynamic trees with top trees. DS/0310065) 19. : Data structures for mobile data. In: Proceedings of the eighth annual ACM-SIAM symposium on Discrete algorithms. Society for Industrial and Applied Mathematics, pp. 747–756 (1997) 20. : Data structures for mobile data. Journal of Algorithms 31(1), 1–28 (1999) 21. : Dynamic Programming. Princeton University Press, Princeton (1957) 22. : Dynamic planar convex hull.

Applications. Self-adjusting computation has been applied to a number of problems from a broad set of application domains such as motion simulation, machine learning, and incremental invariant checking. Some of these applications are developed and implemented using the linguistic techniques described in earlier work and in this paper. One such class of applications is motion simulators for various geometric properties. In these applications, we employ a mutator that starts with an initial run of a self-adjusting program.

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