Acta Informatica最新文献

Parametric timed automata (PTA) extend timed automata (TA) with parameters instead of fixed timing constraints, providing the flexibility to accommodate uncertainties during the design phase. Once a parametric model is obtained, the next step is finding the optimal parameters such that the resulting TA satisfies the specifications. This paper introduces a new algorithm for determining parameters from safety specifications for PTA with bounded integer parameters and no nested cycles. The algorithm searches for unsafe paths through a depth-first search and generates parameter constraints. In particular, the realizability of simple and cyclic paths are encoded via mixed integer linear programming and non-linear programming problems. Then, the parameter constraints rendering the path unrealizable are derived via quantifier elimination. The accumulated constraints through the depth-first search guarantee that a parameter valuation satisfying these constraints solves the synthesis problem. The results are illustrated over benchmarks.

Motivated by computing duplication patterns in sequences, a new problem called the longest letter-duplicated subsequence (LLDS) is proposed. Given a sequence S of length n, a letter-duplicated subsequence is a subsequence of S in the form of (x_1^{d_1}x_2^{d_2}ldots x_k^{d_k}) with (x_iin Sigma ), (x_jne x_{j+1}) and (d_ige 2) for all i in [k] and j in ([k-1]). A linear time algorithm for computing a longest letter-duplicated subsequence (LLDS) of S can be easily obtained. In this paper, we focus on two variants of this problem: (1) ‘all-appearance’ version, i.e., all letters in (Sigma ) must appear in the solution, and (2) the weighted version. For the former, we obtain dichotomous results: We prove that, when each letter appears in S at least 4 times, the problem and a relaxed version on feasibility testing (FT) are both NP-hard. The reduction is from ((3^+,1,2^-))-SAT, where all 3-clauses (i.e., containing 3 lals) are monotone (i.e., containing only positive literals) and all 2-clauses contain only negative literals. We then show that when each letter appears in S at most 3 times, then the problem admits an O(n) time algorithm. Finally, we consider the weighted version, where the weight of a block (x_i^{d_i} (d_ige 2)) could be any positive function which might not grow with (d_i). We give a non-trivial (O(n^2)) time dynamic programming algorithm for this version, i.e., computing an LD-subsequence of S whose weight is maximized.

Invariant relations are used to analyze while loops; while their primary application is to derive the function of a loop, they can also be used to derive loop invariants, weakest preconditions, strongest postconditions, sufficient conditions of correctness, necessary conditions of correctness, and termination conditions of loops. In this paper we present two generic invariant relations that capture the semantics of loops whose loop body applies affine transformations on numeric variables.

In this paper, we propose a decision procedure of reachability for a linear system (xi '=Axi +u), where the matrix (A's) eigenvalues can be arbitrary algebraic number and the input u is a vector of trigonometric-exponential polynomials. If the initial set contains only one point, the reachability problem under consideration is reduced to the decidability of the sign of trigonometric-exponential polynomial and then achieved by being reduced to verification of a series of univariate polynomial inequalities through Taylor expansions of the related exponential functions and trigonometric functions. If the initial set is open semi-algebraic, we will propose a decision procedure based on OpenCAD and an algorithm of real root isolation derived from the sign-deciding procedure for the trigonometric-exponential polynomials. The experimental results indicate the efficiency of our approach. Under the assumption of Schanuel’s Conjecture, the above procedures are complete for bounded time except for several cases.

Red–black (RB) trees are one of the most efficient variants of balanced binary search trees. However, they have often been criticized for being too complicated, hard to explain, and unsuitable for pedagogical purposes, particularly their delete operation. Sedgewick (in: Dagstuhl Workshop on Data Structures, 2008. https://sedgewick.io/wp-content/themes/sedgewick/papers/2008LLRB.pdf) identified the length of code as the root of the problems and introduced left-leaning red–black (LLRB) trees. The delete operation of LLRB trees has a compact recursive code. Unfortunately, it may perform many unnecessary operations. The crux of the deletion algorithm is dealing with a “deficient” subtree, that is one whose black-height has become one less than that of its sibling subtree. In this paper, we revisit 2–3 red–black trees and propose a parity-seeking delete algorithm with the basic idea of making a deficient subtree on a par with its sibling: either by fixing the deficient subtree or by turning the sibling deficient as well, ascending deficiency to the parent node. Interestingly, the proposed parity-seeking delete algorithm also works for 2–3–4 RB trees. Our experiments show that the proposed parity-seeking delete algorithm is as efficient as the best preceding RB trees. The proposed parity-seeking delete algorithm is easily understandable and suitable for pedagogical and practical purposes.

It is important to be able to monitor the network and detect this failure when a connection (an edge) fails. For a vertex set M and an edge e of the graph G, let P(M, e) be the set of pairs (x, y) with a vertex x of M and a vertex y of V(G) such that e belongs to all shortest paths between x and y. A vertex set M of the graph G is distance-edge-monitoring set if every edge e of G is monitored by some vertex of M, that is, the set P(M, e) is nonempty. The distance-edge-monitoring number of a graph G, recently introduced by Foucaud, Kao, Klasing, Miller, and Ryan, is defined as the smallest size of distance-edge-monitoring sets of G. In this paper, we determine the bounds of the distance-edge-monitoring number of grid-based pyramids and the exact value of distance-edge-monitoring number for M(t)-graph and Sierpiński-type graphs. We also compare the distance-edge-monitoring set with average degree, the size of edge set and the size of vertex set of G, where G is M(t)-graph or Sierpiński-type graphs.

In this paper, we present an encoding of the (lambda )-calculus in a multiset rewriting system and provide a few applications of the construction. For this purpose, we choose the calculus named String MultiSet Rewriting, which was introduced in Barbuti et al. (Electron Notes Theor Comput Sci 194:19–34, 2008) by Barbuti et al. With the help of our encoding, we give alternative proofs for the standardization and the finiteness of developments theorems in the (lambda )-calculus.

Simon’s problem is one of the most important problems demonstrating the power of quantum algorithms, as it greatly inspired the proposal of Shor’s algorithm. The generalized Simon’s problem is a natural extension of Simon’s problem and also a special hidden subgroup problem: Given a function (f:{0,1}^n rightarrow {0,1}^m), it is promised that there exists a hidden subgroup (Sle mathbb {Z}_2^n) of rank k such that for any (x, yin {{0, 1}}^n), (f(x) = f(y)) iff (x oplus y in S). The goal of generalized Simon’s problem is to find the hidden subgroup S. In this paper, we present two key contributions. Firstly, we characterize the structure of the generalized Simon’s problem in distributed scenario and introduce a corresponding distributed quantum algorithm. Secondly, we refine the algorithm to ensure exactness due to the application of quantum amplitude amplification technique. Our algorithm offers exponential speedup compared to the distributed classical algorithm. When contrasted with the quantum algorithm for the generalized Simon’s problem, our algorithm’s oracle requires fewer qubits, thus making it easier to be physically implemented. Particularly, the exact distributed quantum algorithm we develop for the generalized Simon’s problem outperforms the best previously proposed distributed quantum algorithm for Simon’s problem in terms of generalizability and exactness.

Laplacian matrix and its spectrum are commonly used for giving a measure in networks in order to analyse its topological properties. In this paper, Laplacian matrix of graphs and their spectrum are studied. Laplacian energy of a graph G of order n is defined as ( mathrm{{LE}}(G) = sum _{i=1}^n|lambda _i(L)-{bar{d}}|), where (lambda _i(L)) is the i-th eigenvalue of Laplacian matrix of G, and ({bar{d}}) is their average. If (mathrm{{LE}}(G) = mathrm{{LE}}(K_n)) for the complete graph (K_n) of order n, then G is known as L-borderenergetic graph. In the first part of this paper, we construct three infinite families of non-complete disconnected L-borderenergetic graphs: (Lambda _1 = { G_{b,j,k} = [(((j-2)k-2j+2)b+1)K_{(j-1)k-(j-2)}] cup b(K_j times K_k)| b,j,k in {{mathbb {Z}}}^+}), ( Lambda _2 = {G_{2,b} = [K_6 nabla b(K_2 times K_3)] cup (4b-2)K_9 | bin {{mathbb {Z}}}^+ }), ( Lambda _3 = {G_{3,b} = [bK_8 nabla b(K_2 times K_4)] cup (14b-4)K_{8b+6} | bin {{mathbb {Z}}}^+ }), where (nabla ) is join operator and (times ) is direct product operator on graphs. Then, in the second part of this work, we construct new infinite families of non-complete connected L-borderenergetic graphs (Omega _1= {K_2 nabla overline{aK_2^r} vert ain {{mathbb {Z}}}^+}), (Omega _2 = {overline{aK_3 cup 2(K_2times K_3)}vert ain {{mathbb {Z}}}^+ }) and (Omega _3 = {overline{aK_5 cup (K_3times K_3)}vert ain {{mathbb {Z}}}^+ }), where ({overline{G}}) is the complement operator on G.

We present a new FPTAS for the Subset Sum Ratio problem, which, given a set of integers, asks for two disjoint subsets such that the ratio of their sums is as close to 1 as possible. Our scheme makes use of exact and approximate algorithms for Partition, and clearly showcases the close relationship between the two algorithmic problems. Depending on the relationship between the size of the input set n and the error margin (varepsilon ), we improve upon the best currently known algorithm of Melissinos and Pagourtzis [COCOON 2018] of complexity (mathcal {O} (n^4 / varepsilon )). In particular, the exponent of n in our proposed scheme may decrease down to 2, depending on the Partition algorithm used.