By Ran Canetti (auth.), Luca Aceto, Ivan Damgård, Leslie Ann Goldberg, Magnús M. Halldórsson, Anna Ingólfsdóttir, Igor Walukiewicz (eds.)
The two-volume set LNCS 5125 and LNCS 5126 constitutes the refereed complaints of the thirty fifth foreign Colloquium on Automata, Languages and Programming, ICALP 2008, held in Reykjavik, Iceland, in July 2008.
The 126 revised complete papers provided including four invited lectures have been rigorously reviewed and chosen from a complete of 407 submissions. The papers are grouped in 3 significant tracks on algorithms, automata, complexity and video games, on common sense, semantics, and thought of programming, and on defense and cryptography foundations. LNCS 5126 includes fifty six contributions of music B and song C chosen from 208 submissions and a pair of invited lectures. The papers for tune B are equipped in topical sections on bounds, allotted computation, real-time and probabilistic structures, good judgment and complexity, phrases and timber, nonstandard versions of computation, reasoning approximately computation, and verification. The papers of song C hide themes in defense and cryptography resembling conception, safe computation, two-party protocols and zero-knowledge, encryption with precise properties/quantum cryptography, numerous kinds of hashing, in addition to public-key cryptography and authentication.
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Additional resources for Automata, Languages and Programming: 35th International Colloquium, ICALP 2008, Reykjavik, Iceland, July 7-11, 2008, Proceedings, Part II
Let N be a class of ﬁnite automata. If δNFA ⊆ N then DFA → N minimization is NP-hard. Corollary 3. For each class N of ﬁnite automata such that δNFA ⊆ N , the minimization problem for N is NP-hard. We start by formally deﬁning the decision problems that are of interest to us, and then sketch an intuitive overview of our proof. Given an undirected graph G = (V, E) such that V is its set of vertices and E ⊆ V × V is its set of edges, we say that a set of vertices V C ⊆ V is a vertex cover of G if, for every edge (v1 , v2 ) ∈ E, V C contains v1 , v2 , or both.
LNCS, vol. 4588, pp. 157–168. Springer, Heidelberg (2007) 5. : On fixed point equations over commutative semirings. , Weil, P. ) STACS 2007. LNCS, vol. 4393, pp. 296–307. Springer, Heidelberg (2007) 6. : Convergence thresholds of Newton’s method for monotone polynomial equations. In: Proceedings of STACS, pp. 289–300 (2008) 7. : Solving monotone polynomial equations. In: Proceedings of IFIP TCS 2008. Springer, Heidelberg (to appear, 2008) 8. : Model checking probabilistic pushdown automata. In: LICS 2004.
Mk where k ≥ 0 and m1 , . . , mk are monomials. A vector is a mapping v that assigns to every variable X ∈ X a value denoted by v X or vX , called the X-component of v. The value of a monomial m = a1 X1 a2 · · · ak Xk ak+1 at v is m(v) = a1 vX1 a2 · · · ak vXk ak+1 . The value of a polynomial at v is the sum of the values of its monomials at v. A polynomial induces a mapping from vectors to values that assigns to v the vector f (v). A vector of polynomials is a mapping f that assigns a polynomial fX to each variable X ∈ X ; it induces a mapping from vectors to vectors that assigns to a vector v the vector f (v) whose X-component is fX (v).
Automata, Languages and Programming: 35th International Colloquium, ICALP 2008, Reykjavik, Iceland, July 7-11, 2008, Proceedings, Part II by Ran Canetti (auth.), Luca Aceto, Ivan Damgård, Leslie Ann Goldberg, Magnús M. Halldórsson, Anna Ingólfsdóttir, Igor Walukiewicz (eds.)