Declarative Programming and Knowledge Management: by Michael Hanus, Ricardo Rocha (eds.)

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By Michael Hanus, Ricardo Rocha (eds.)

This ebook constitutes the court cases of the Kiel Declarative Programming Days, KDPD 2013, unifying the next meetings: the 20 th overseas convention on functions of Declarative Programming and information administration (INAP 2013), the twenty second foreign Workshop on useful and (Constraint) good judgment Programming (WFLP 2013) and the twenty seventh Workshop on common sense Programming (WLP 2013), held in Kiel, Germany, in September 2013. The 15 papers offered have been rigorously and reviewed and chosen for inclusion during this e-book. They hide the next themes: good judgment programming, constraint challenge fixing, programmable common sense solvers, useful programming and constraint programming.

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Extra info for Declarative Programming and Knowledge Management: Declarative Programming Days, KDPD 2013, Unifying INAP, WFLP, and WLP, Kiel, Germany, September 11-13, 2013, Revised Selected Papers

Example text

Also, for any two MUDSE solutions J1 and J2 for I and M under S, it is the case that J1 and J2 are isomorphic. Proof. The proof of the first part of this theorem is very similar to the proof of Proposition 1, with the difference that steps 2, 3, and 4 in CompMUDSEsolS seem to be non-deterministic since they involve choosing a set of witnesses {w1 , . . , wm } for {C1 , . . , Cm }. Clearly, different sets of witnesses may yield different Sharing and Exchanging Data 29 target instances. However, each possible choice of witnesses leads to a minimal universal DSE solution.

We use abstract environments EA that map program variables to abstract values, and an abstract evaluation function abstract-value : EA × P ⊆ A. Allocators. As explained in the introduction, the constraint program receives known and unknown arguments. The compiled program operates on abstract values. The abstract value that represents a (finite) set of concrete values of an unknown argument is obtained from an allocator. For a property q : C ⊆ B of concrete values, a q-allocator constructs an object a ← A that represents all concrete objects that satisfy q: ∈c ← C : q(c) ∩∅ ∃β ← ν : c = decode(a, β).

Polymorphic types do not change the compilation process. The important information is the same as with monomorphic typing: the total number of constructors of a type, and the number (the encoding) of one constructor. In all, we can use in CO4 a large part of the Haskell Prelude functions. , and xs = foldl (&&) True xs ; a ++ b = foldr (:) b a Memoization. We describe another optimization: in the abstract program, we use memoization for all subprograms. That is, during execution of the abstract program, we keep a map from (function name, argument tuple) to result.

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