AxialGen: A Research Prototype for Automatically Generating the Axial Map

Abstract: AxialGen is a research prototype for automatically generating the axial map, which consists of the least number of the longest visibility lines (or axial lines) for representing individual linearly stretched parts of open space of an urban environment. Open space is the space between closed spaces such as buildings and street blocks. This paper aims to provide an accessible guide to software AxialGen, and the underlying concepts and ideas. We concentrate on the explanation and illustration of the key concept of bucket: its definition, formation and how it is used in generating the axial map. Keywords: Bucket, visibility, medial axes, axial lines, isovists, axial map


Formalization of malware through process calculi

Abstract: Since the seminal work from F. Cohen in the eighties, abstract virology has seen the apparition of successive viral models, all based on Turing-equivalent formalisms. But considering recent malware such as rootkits or k-ary codes, these viral models only partially cover these evolved threats. The problem is that Turing-equivalent models do not support interactive computations. New models have thus appeared, offering support for these evolved malware, but loosing the unified approach in the way. This article provides a basis for a unified malware model founded on process algebras and in particular the Join-Calculus. In terms of expressiveness, the new model supports the fundamental definitions based on self-replication and adds support for interactions, concurrency and non-termination allows the definition of more complex behaviors. Evolved malware such as rootkits can now be thoroughly modeled. In terms of detection and prevention, the fundamental results of undecidability and isolation still hold. However the process-based model has permitted to establish new results: identification of fragments from the Join-Calculus where malware detection becomes decidable, formal definition of the non-infection property, approximate solutions to restrict malware propagation.


Graphical Reasoning in Compact Closed Categories for Quantum Computation

Abstract: Compact closed categories provide a foundational formalism for a variety of important domains, including quantum computation. These categories have a natural visualisation as a form of graphs. We present a formalism for equational reasoning about such graphs and develop this into a generic proof system with a fixed logical kernel for equational reasoning about compact closed categories. Automating this reasoning process is motivated by the slow and error prone nature of manual graph manipulation. A salient feature of our system is that it provides a formal and declarative account of derived results that can include `ellipses'-style notation. We illustrate the framework by instantiating it for a graphical language of quantum computation and show how this can be used to perform symbolic computation.


An Optimal Multi-Unit Combinatorial Procurement Auction with Single Minded Bidders

Abstract: The current art in optimal combinatorial auctions is limited to handling the case of single units of multiple items, with each bidder bidding on exactly one bundle (single minded bidders). This paper extends the current art by proposing an optimal auction for procuring multiple units of multiple items when the bidders are single minded. The auction minimizes the cost of procurement while satisfying Bayesian incentive compatibility and interim individual rationality. Under appropriate regularity conditions, this optimal auction also satisfies dominant strategy incentive compatibility.


Analysis of bandwidth measurement methodologies over WLAN systems

Abstract: WLAN devices have become a fundamental component of nowadays network deployments. However, even though traditional networking applications run mostly unchanged over wireless links, the actual interaction between these applications and the dynamics of wireless transmissions is not yet fully understood. An important example of such applications are bandwidth estimation tools. This area has become a mature research topic with well-developed results. Unfortunately recent studies have shown that the application of these results to WLAN links is not straightforward. The main reasons for this is that the assumptions taken to develop bandwidth measurements tools do not hold any longer in the presence of wireless links (e.g. non-FIFO scheduling). This paper builds from these observations and its main goal is to analyze the interaction between probe packets and WLAN transmissions in bandwidth estimation processes. The paper proposes an analytical model that better accounts for the particularities of WLAN links. The model is validated through extensive experimentation and simulation and reveals that (1) the distribution of the delay to transmit probing packets is not the same for the whole probing sequence, this biases the measurements process and (2) existing tools and techniques point at the achievable throughput rather than the available bandwidth or the capacity, as previously assumed.


Degrees of Guaranteed Envy-Freeness in Finite Bounded Cake-Cutting Protocols

Abstract: Cake-cutting protocols aim at dividing a ``cake'' (i.e., a divisible resource) and assigning the resulting portions to several players in a way that each of the players feels to have received a ``fair'' amount of the cake. An important notion of fairness is envy-freeness: No player wishes to switch the portion of the cake received with another player's portion. Despite intense efforts in the past, it is still an open question whether there is a \emph{finite bounded} envy-free cake-cutting protocol for an arbitrary number of players, and even for four players. We introduce the notion of degree of guaranteed envy-freeness (DGEF) as a measure of how good a cake-cutting protocol can approximate the ideal of envy-freeness while keeping the protocol finite bounded (trading being disregarded). We propose a new finite bounded proportional protocol for any number n \geq 3 of players, and show that this protocol has a DGEF of 1 + \lceil (n^2)/2 \rceil. This is the currently best DGEF among known finite bounded cake-cutting protocols for an arbitrary number of players. We will make the case that improving the DGEF even further is a tough challenge, and determine, for comparison, the DGEF of selected known finite bounded cake-cutting protocols.


Embedding Data within Knowledge Spaces

Abstract: The promise of e-Science will only be realized when data is discoverable, accessible, and comprehensible within distributed teams, across disciplines, and over the long-term--without reliance on out-of-band (non-digital) means. We have developed the open-source Tupelo semantic content management framework and are employing it to manage a wide range of e-Science entities (including data, documents, workflows, people, and projects) and a broad range of metadata (including provenance, social networks, geospatial relationships, temporal relations, and domain descriptions). Tupelo couples the use of global identifiers and resource description framework (RDF) statements with an aggregatable content repository model to provide a unified space for securely managing distributed heterogeneous content and relationships.


Interference and Congestion Aware Gradient Broadcasting Routing for Wireless Sensor Networks

Abstract: This paper addresses the problem of reliable transmission of data through a sensor network. We focus on networks rapidly deployed in harsh environments. For these networks, important design requirements are fast data transmission and rapid network setup, as well as minimized energy consumption for increased network lifetime. We propose a novel broadcasting solution that accounts for the interference impact and the congestion level of the channel, in order to improve robustness, energy consumption and delay performance, compared to a benchmark routing protocol, the GRAB algorithm. Three solutions are proposed: P-GRAB, a probabilistic routing algorithm for interference mitigation, U-GRAB, a utility-based algorithm that adjusts to real-time congestion and UP-GRAB, a combination of P-GRAB and U-GRAB. It is shown that P-GRAB provides the best performance for geometry-aware networks while the U-GRAB approach is the best option for unreliable and unstable networks.


A Simple Extraction Procedure for Bibliographical Author Field

Abstract: A procedure for bibliographic author metadata extraction from scholarly texts is presented. The author segments are identified based on capitalization and line break patterns. Two main author layout templates, which can retrieve from a varied set of title pages, are provided. Additionally, several disambiguating rules are described.


Genetic algorithm based optimization and post optimality analysis of multi-pass face milling

Abstract: This paper presents an optimization technique for the multi-pass face milling process. Genetic algorithm (GA) is used to obtain the optimum cutting parameters by minimizing the unit production cost for a given amount of material removal. Cutting speed, feed and depth of cut for the finish and rough passes are the cutting parameters. An equal depth of cut for roughing passes has been considered. A lookup table containing the feasible combinations of depth of cut in finish and rough passes is generated so as to reduce the number of variables by one. The resulting mixed integer nonlinear optimization problem is solved in a single step using GA. The entire technique is demonstrated in a case study. Post optimality analysis of the example problem is done to develop a strategy for optimizing without running GA again for different values of total depth of cut.


A Multiobjective Optimization Framework for Routing in Wireless Ad Hoc Networks

Abstract: Wireless ad hoc networks are seldom characterized by one single performance metric, yet the current literature lacks a flexible framework to assist in characterizing the design tradeoffs in such networks. In this work, we address this problem by proposing a new modeling framework for routing in ad hoc networks, which used in conjunction with metaheuristic multiobjective search algorithms, will result in a better understanding of network behavior and performance when multiple criteria are relevant. Our approach is to take a holistic view of the network that captures the cross-interactions among interference management techniques implemented at various layers of the protocol stack. The resulting framework is a complex multiobjective optimization problem that can be efficiently solved through existing multiobjective search techniques. In this contribution, we present the Pareto optimal sets for an example sensor network when delay, robustness and energy are considered. The aim of this paper is to present the framework and hence for conciseness purposes, the multiobjective optimization search is not developed herein.


Alleviating Media Bias Through Intelligent Agent Blogging

Abstract: Consumers of mass media must have a comprehensive, balanced and plural selection of news to get an unbiased perspective; but achieving this goal can be very challenging, laborious and time consuming. News stories development over time, its (in)consistency, and different level of coverage across the media outlets are challenges that a conscientious reader has to overcome in order to alleviate bias. In this paper we present an intelligent agent framework currently facilitating analysis of the main sources of on-line news in El Salvador. We show how prior tools of text analysis and Web 2.0 technologies can be combined with minimal manual intervention to help individuals on their rational decision process, while holding media outlets accountable for their work.


Finding Exact Minimal Polynomial by Approximations

Abstract: We present a new algorithm for reconstructing an exact algebraic number from its approximate value using an improved parameterized integer relation construction method. Our result is consistent with the existence of error controlling on obtaining an exact rational number from its approximation. The algorithm is applicable for finding exact minimal polynomial by its approximate root. This also enables us to provide an efficient method of converting the rational approximation representation to the minimal polynomial representation, and devise a simple algorithm to factor multivariate polynomials with rational coefficients. Compared with other methods, this method has the numerical computation advantage of high efficiency. The experimental results show that the method is more efficient than \emph{identify} in \emph{Maple} 11 for obtaining an exact algebraic number from its approximation. In this paper, we completely implement how to obtain exact results by numerical approximate computations.


Matrix Graph Grammars and Monotone Complex Logics

Abstract: Graph transformation is concerned with the manipulation of graphs by means of rules. Graph grammars have been traditionally studied using techniques from category theory. In previous works, we introduced Matrix Graph Grammars (MGGs) as a purely algebraic approach for the study of graph grammars and graph dynamics, based on the representation of graphs by means of their adjacency matrices. MGGs have been succesfully applied to problems such as applicability of rule sequences, sequentialization and reachability, providing new analysis techniques and generalizing and improving previous results. Our next objective is to generalize MGGs in order to approach computational complexity theory and "static" properties of graphs out of the "dynamics" of certain grammars. In the present work, we start building bridges between MGGs and complexity by introducing what we call "Monotone Complex Logic", which allows establishing a (bijective) link between MGGs and complex analysis. We use this logic to recast the formulation and basic building blocks of MGGs as more proper geometric and analytic concepts (scalar products, norms, distances). MGG rules can also be interpreted - via operators - as complex numbers. Interestingly, the subset they define can be characterized as the Sierpinski gasket.


Comparative concept similarity over Minspaces: Axiomatisation and Tableaux Calculus

Abstract: We study the logic of comparative concept similarity $\CSL$ introduced by Sheremet, Tishkovsky, Wolter and Zakharyaschev to capture a form of qualitative similarity comparison. In this logic we can formulate assertions of the form " objects A are more similar to B than to C". The semantics of this logic is defined by structures equipped by distance functions evaluating the similarity degree of objects. We consider here the particular case of the semantics induced by \emph{minspaces}, the latter being distance spaces where the minimum of a set of distances always exists. It turns out that the semantics over arbitrary minspaces can be equivalently specified in terms of preferential structures, typical of conditional logics. We first give a direct axiomatisation of this logic over Minspaces. We next define a decision procedure in the form of a tableaux calculus. Both the calculus and the axiomatisation take advantage of the reformulation of the semantics in terms of preferential structures.


MicroSim: Modeling the Swedish Population

Abstract: This article presents a unique, large-scale and spatially explicit microsimulation model that uses official anonymized register data collected from all individuals living in Sweden. Individuals are connected to households and workplaces and represent crucial links in the Swedish social contact network. This enables significant policy experiments in the domain of epidemic outbreaks. Development of the model started in 2004 at the Swedish Institute for Infectious Disease Control (SMI) in Solna, Sweden with the goal of creating a tool for testing the effects of intervention policies. These interventions include mass vaccination, targeted vaccination, isolation and social distancing. The model was initially designed for simulating smallpox outbreaks. In 2006, it was modified to support simulations of pandemic influenza. All nine millions members of the Swedish population are represented in the model. This article is a technical description of the simulation model; the input data, the simulation engine and the basic object types.


Multiple time-delays system modeling and control for router management

Abstract: This paper investigates the overload problem of a single congested router in TCP (Transmission Control Protocol) networks. To cope with the congestion phenomenon, we design a feedback control based on a multiple time-delays model of the set TCP/AQM (Active Queue Management). Indeed, using robust control tools, especially in the quadratic separation framework, the TCP/AQM model is rewritten as an intercon- nected system and a structured state feedback is constructed to stabilize the network variables. Finally, we illustrate the proposed methodology with a numerical example and simulations using NS-2 simulator.


Design and performance evaluation of a state-space based AQM

Abstract: Recent research has shown the link between congestion control in communication networks and feedback control system. In this paper, the design of an active queue management (AQM) which can be viewed as a controller, is considered. Based on a state space representation of a linearized fluid flow model of TCP, the AQM design is converted to a state feedback synthesis problem for time delay systems. Finally, an example extracted from the literature and simulations via a network simulator NS (under cross traffic conditions) support our study.


On Designing Lyapunov-Krasovskii Based AQM for Routers Supporting TCP Flows

Abstract: For the last few years, we assist to a growing interest of designing AQM (Active Queue Management) using control theory. In this paper, we focus on the synthesis of an AQM based on the Lyapunov theory for time delay systems. With the help of a recently developed Lyapunov-Krasovskii functional and using a state space representation of a linearized fluid model of TCP, two robust AQMs stabilizing the TCP model are constructed. Notice that our results are constructive and the synthesis problem is reduced to a convex optimization scheme expressed in terms of linear matrix inequalities (LMIs). Finally, an example extracted from the literature and simulations via {\it NS simulator} support our study.


Towards a Theory of Requirements Elicitation: Acceptability Condition for the Relative Validity of Requirements

Abstract: A requirements engineering artifact is valid relative to the stakeholders of the system-to-be if they agree on the content of that artifact. Checking relative validity involves a discussion between the stakeholders and the requirements engineer. This paper proposes (i) a language for the representation of information exchanged in a discussion about the relative validity of an artifact; (ii) the acceptability condition, which, when it verifies in a discussion captured in the proposed language, signals that the relative validity holds for the discussed artifact and for the participants in the discussion; and (iii) reasoning procedures to automatically check the acceptability condition in a discussions captured by the proposed language.


Robust control tools for traffic monitoring in TCP/AQM networks

Abstract: Several studies have considered control theory tools for traffic control in communication networks, as for example the congestion control issue in IP (Internet Protocol) routers. In this paper, we propose to design a linear observer for time-delay systems to address the traffic monitoring issue in TCP/AQM (Transmission Control Protocol/Active Queue Management) networks. Due to several propagation delays and the queueing delay, the set TCP/AQM is modeled as a multiple delayed system of a particular form. Hence, appropriate robust control tools as quadratic separation are adopted to construct a delay dependent observer for TCP flows estimation. Note that, the developed mechanism enables also the anomaly detection issue for a class of DoS (Denial of Service) attacks. At last, simulations via the network simulator NS-2 and an emulation experiment validate the proposed methodology.


New Confidence Measures for Statistical Machine Translation

Abstract: A confidence measure is able to estimate the reliability of an hypothesis provided by a machine translation system. The problem of confidence measure can be seen as a process of testing : we want to decide whether the most probable sequence of words provided by the machine translation system is correct or not. In the following we describe several original word-level confidence measures for machine translation, based on mutual information, n-gram language model and lexical features language model. We evaluate how well they perform individually or together, and show that using a combination of confidence measures based on mutual information yields a classification error rate as low as 25.1% with an F-measure of 0.708.


Towards a Statistical Methodology to Evaluate Program Speedups and their Optimisation Techniques

Abstract: The community of program optimisation and analysis, code performance evaluation, parallelisation and optimising compilation has published since many decades hundreds of research and engineering articles in major conferences and journals. These articles study efficient algorithms, strategies and techniques to accelerate programs execution times, or optimise other performance metrics (MIPS, code size, energy/power, MFLOPS, etc.). Many speedups are published, but nobody is able to reproduce them exactly. The non-reproducibility of our research results is a dark point of the art, and we cannot be qualified as {\it computer scientists} if we do not provide rigorous experimental methodology. This article provides a first effort towards a correct statistical protocol for analysing and measuring speedups. As we will see, some common mistakes are done by the community inside published articles, explaining part of the non-reproducibility of the results. Our current article is not sufficient by its own to deliver a complete experimental methodology, further efforts must be done by the community to decide about a common protocol for our future experiences. Anyway, our community should take care about the aspect of reproducibility of the results in the future.


Optimal design and optimal control of structures undergoing finite rotations and elastic deformations

Abstract: In this work we deal with the optimal design and optimal control of structures undergoing large rotations. In other words, we show how to find the corresponding initial configuration and the corresponding set of multiple load parameters in order to recover a desired deformed configuration or some desirable features of the deformed configuration as specified more precisely by the objective or cost function. The model problem chosen to illustrate the proposed optimal design and optimal control methodologies is the one of geometrically exact beam. First, we present a non-standard formulation of the optimal design and optimal control problems, relying on the method of Lagrange multipliers in order to make the mechanics state variables independent from either design or control variables and thus provide the most general basis for developing the best possible solution procedure. Two different solution procedures are then explored, one based on the diffuse approximation of response function and gradient method and the other one based on genetic algorithm. A number of numerical examples are given in order to illustrate both the advantages and potential drawbacks of each of the presented procedures.


Compressed Representations of Permutations, and Applications

Abstract: We explore various techniques to compress a permutation $\pi$ over n integers, taking advantage of ordered subsequences in $\pi$, while supporting its application $\pi$(i) and the application of its inverse $\pi^{-1}(i)$ in small time. Our compression schemes yield several interesting byproducts, in many cases matching, improving or extending the best existing results on applications such as the encoding of a permutation in order to support iterated applications $\pi^k(i)$ of it, of integer functions, and of inverted lists and suffix arrays.


Fast solving of Weighted Pairing Least-Squares systems

Abstract: This paper presents a generalization of the "weighted least-squares" (WLS), named "weighted pairing least-squares" (WPLS), which uses a rectangular weight matrix and is suitable for data alignment problems. Two fast solving methods, suitable for solving full rank systems as well as rank deficient systems, are studied. Computational experiments clearly show that the best method, in terms of speed, accuracy, and numerical stability, is based on a special {1, 2, 3}-inverse, whose computation reduces to a very simple generalization of the usual "Cholesky factorization-backward substitution" method for solving linear systems.


Weak Mso with the Unbounding Quantifier

Abstract: A new class of languages of infinite words is introduced, called the max-regular languages, extending the class of $\omega$-regular languages. The class has two equivalent descriptions: in terms of automata (a type of deterministic counter automaton), and in terms of logic (weak monadic second-order logic with a bounding quantifier). Effective translations between the logic and automata are given.


Polynomial-Time Approximation Schemes for Subset-Connectivity Problems in Bounded-Genus Graphs

Abstract: We present the first polynomial-time approximation schemes (PTASes) for the following subset-connectivity problems in edge-weighted graphs of bounded genus: Steiner tree, low-connectivity survivable-network design, and subset TSP. The schemes run in O(n log n) time for graphs embedded on both orientable and non-orientable surfaces. This work generalizes the PTAS frameworks of Borradaile, Klein, and Mathieu from planar graphs to bounded-genus graphs: any future problems shown to admit the required structure theorem for planar graphs will similarly extend to bounded-genus graphs.


On finding a particular class of combinatorial identities

Abstract: In this paper, a class of combinatorial identities is proved. A method is used which is based on the following rule: counting elements of a given set in two ways and making equal the obtained results. This rule is known as "counting in two ways". The principle of inclusion and exclusion is used for obtaining a class of (0,1)-matrices.


A Polynomial Kernel For Multicut In Trees

Abstract: The MULTICUT IN TREES problem consists in deciding, given a tree, a set of requests (i.e. paths in the tree) and an integer k, whether there exists a set of k edges cutting all the requests. This problem was shown to be FPT by Guo and Niedermeyer. They also provided an exponential kernel. They asked whether this problem has a polynomial kernel. This question was also raised by Fellows. We show that MULTICUT IN TREES has a polynomial kernel.


On the Average Complexity of Moore's State Minimization Algorithm

Abstract: We prove that, for any arbitrary finite alphabet and for the uniform distribution over deterministic and accessible automata with n states, the average complexity of Moore's state minimization algorithm is in O(n log n). Moreover this bound is tight in the case of unary utomata.


A Model for Managing Collections of Patterns

Abstract: Data mining algorithms are now able to efficiently deal with huge amount of data. Various kinds of patterns may be discovered and may have some great impact on the general development of knowledge. In many domains, end users may want to have their data mined by data mining tools in order to extract patterns that could impact their business. Nevertheless, those users are often overwhelmed by the large quantity of patterns extracted in such a situation. Moreover, some privacy issues, or some commercial one may lead the users not to be able to mine the data by themselves. Thus, the users may not have the possibility to perform many experiments integrating various constraints in order to focus on specific patterns they would like to extract. Post processing of patterns may be an answer to that drawback. Thus, in this paper we present a framework that could allow end users to manage collections of patterns. We propose to use an efficient data structure on which some algebraic operators may be used in order to retrieve or access patterns in pattern bases.


How happy is your web browsing? A model to quantify satisfaction of an Internet user, searching for desired information

Abstract: We feel happy when web-browsing operations provide us with necessary information; otherwise, we feel bitter. How to measure this happiness (or bitterness)? How does the profile of happiness grow and decay during the course of web-browsing? We propose a probabilistic framework that models evolution of user satisfaction, on top of his/her continuous frustration at not finding the required information. It is found that the cumulative satisfaction profile of a web-searching individual can be modeled effectively as the sum of random number of random terms, where each term is mutually independent random variable, originating from 'memoryless' Poisson flow. Evolution of satisfaction over the entire time interval of user's browsing was modeled with auto-correlation analysis. A utilitarian marker, magnitude of greater than unity of which describe happy web-searching operations; and an empirical limit that connects user's satisfaction with his frustration level - are proposed too. Presence of pertinent information in the very first page of a web-site and magnitude of the decay parameter of user satisfaction (frustration, irritation etc.), are found to be two key aspects that dominate web-browser's psychology. The proposed model employed different combination of decay parameter, searching time and number of helpful web-sites. Obtained results are found to match the results from three real-life case-studies.


Node Weighted Scheduling

Abstract: This paper proposes a new class of online policies for scheduling in input-buffered crossbar switches. Our policies are throughput optimal for a large class of arrival processes which satisfy strong-law of large numbers. Given an initial configuration and no further arrivals, our policies drain all packets in the system in the minimal amount of time (providing an online alternative to the batch approach based on Birkhoff-VonNeumann decompositions). We show that it is possible for policies in our class to be throughput optimal even if they are not constrained to be maximal in every time slot. Most algorithms for switch scheduling take an edge based approach; in contrast, we focus on scheduling (a large enough set of) the most congested ports. This alternate approach allows for lower-complexity algorithms, and also requires a non-standard technique to prove throughput-optimality. One algorithm in our class, Maximum Vertex-weighted Matching (MVM) has worst-case complexity similar to Max-size Matching, and in simulations shows slightly better delay performance than Max-(edge)weighted-Matching (MWM).


The Complexity of Datalog on Linear Orders

Abstract: We study the program complexity of datalog on both finite and infinite linear orders. Our main result states that on all linear orders with at least two elements, the nonemptiness problem for datalog is EXPTIME-complete. While containment of the nonemptiness problem in EXPTIME is known for finite linear orders and actually for arbitrary finite structures, it is not obvious for infinite linear orders. It sharply contrasts the situation on other infinite structures; for example, the datalog nonemptiness problem on an infinite successor structure is undecidable. We extend our upper bound results to infinite linear orders with constants. As an application, we show that the datalog nonemptiness problem on Allen's interval algebra is EXPTIME-complete.


Directed paths on a tree: coloring, multicut and kernel

Abstract: In the present paper, we study algorithmic questions for the arc-intersection graph of directed paths on a tree. Such graphs are known to be perfect (proved by Monma and Wei in 1986). We present faster algorithms than all previously known algorithms for solving the minimum coloring and the minimum clique cover problems. They both run in $O(np)$ time, where $n$ is the number of vertices of the tree and $p$ the number of paths. Another result is a polynomial algorithm computing a kernel in the intersection graph, when its edges are oriented in a clique-acyclic way. Indeed, such a kernel exists for any perfect graph by a theorem of Boros and Gurvich. Such algorithms computing kernels are known only for few classes of perfect graphs.


Discovering general partial orders in event streams

Abstract: Frequent episode discovery is a popular framework for pattern discovery in event streams. An episode is a partially ordered set of nodes with each node associated with an event type. Efficient (and separate) algorithms exist for episode discovery when the associated partial order is total (serial episode) and trivial (parallel episode). In this paper, we propose efficient algorithms for discovering frequent episodes with general partial orders. These algorithms can be easily specialized to discover serial or parallel episodes. Also, the algorithms are flexible enough to be specialized for mining in the space of certain interesting subclasses of partial orders. We point out that there is an inherent combinatorial explosion in frequent partial order mining and most importantly, frequency alone is not a sufficient measure of interestingness. We propose a new interestingness measure for general partial order episodes and a discovery method based on this measure, for filtering out uninteresting partial orders. Simulations demonstrate the effectiveness of our algorithms.


On Why and What of Randomness

Abstract: This paper has several objectives. First, it separates randomness from lawlessness and shows why even genuine randomness does not imply lawlessness. Second, it separates the question -why should I call a phenomenon random? (and answers it in part one) from the patent question -What is a random sequence? -for which the answer lies in Kolmogorov complexity (which is explained in part two). While answering the first question the note argues why there should be four motivating factors for calling a phenomenon random: ontic, epistemic, pseudo and telescopic, the first two depicting genuine randomness and the last two false. Third, ontic and epistemic randomness have been distinguished from ontic and epistemic probability. Fourth, it encourages students to be applied statisticians and advises against becoming armchair theorists but this is interestingly achieved by a straight application of telescopic randomness. Overall, it tells (the teacher) not to jump to probability without explaining randomness properly first and similarly advises the students to read (and understand) randomness minutely before taking on probability.


Almost-Uniform Sampling of Points on High-Dimensional Algebraic Varieties

Abstract: We consider the problem of uniform sampling of points on an algebraic variety. Specifically, we develop a randomized algorithm that, given a small set of multivariate polynomials over a sufficiently large finite field, produces a common zero of the polynomials almost uniformly at random. The statistical distance between the output distribution of the algorithm and the uniform distribution on the set of common zeros is polynomially small in the field size, and the running time of the algorithm is polynomial in the description of the polynomials and their degrees provided that the number of the polynomials is a constant.


Hardness and Algorithms for Rainbow Connectivity

Abstract: An edge-colored graph G is rainbow connected if any two vertices are connected by a path whose edges have distinct colors. The rainbow connectivity of a connected graph G, denoted rc(G), is the smallest number of colors that are needed in order to make G rainbow connected. In addition to being a natural combinatorial problem, the rainbow connectivity problem is motivated by applications in cellular networks. In this paper we give the first proof that computing rc(G) is NP-Hard. In fact, we prove that it is already NP-Complete to decide if rc(G) = 2, and also that it is NP-Complete to decide whether a given edge-colored (with an unbounded number of colors) graph is rainbow connected. On the positive side, we prove that for every $\epsilon$ > 0, a connected graph with minimum degree at least $\epsilon n$ has bounded rainbow connectivity, where the bound depends only on $\epsilon$, and the corresponding coloring can be constructed in polynomial time. Additional non-trivial upper bounds, as well as open problems and conjectures are also pre sented.


Enumerating Homomorphisms

Abstract: The homomorphism problem for relational structures is an abstract way of formulating constraint satisfaction problems (CSP) and various problems in database theory. The decision version of the homomorphism problem received a lot of attention in literature; in particular, the way the graph-theoretical structure of the variables and constraints influences the complexity of the problem is intensively studied. Here we study the problem of enumerating all the solutions with polynomial delay from a similar point of view. It turns out that the enumeration problem behaves very differently from the decision version. We give evidence that it is unlikely that a characterization result similar to the decision version can be obtained. Nevertheless, we show nontrivial cases where enumeration can be done with polynomial delay.


Compilation of extended recursion in call-by-value functional languages

Abstract: This paper formalizes and proves correct a compilation scheme for mutually-recursive definitions in call-by-value functional languages. This scheme supports a wider range of recursive definitions than previous methods. We formalize our technique as a translation scheme to a lambda-calculus featuring in-place update of memory blocks, and prove the translation to be correct.


Extraction de concepts sous contraintes dans des donn\'ees d'expression de g\`enes

Abstract: In this paper, we propose a technique to extract constrained formal concepts.


Database Transposition for Constrained (Closed) Pattern Mining

Abstract: Recently, different works proposed a new way to mine patterns in databases with pathological size. For example, experiments in genome biology usually provide databases with thousands of attributes (genes) but only tens of objects (experiments). In this case, mining the "transposed" database runs through a smaller search space, and the Galois connection allows to infer the closed patterns of the original database. We focus here on constrained pattern mining for those unusual databases and give a theoretical framework for database and constraint transposition. We discuss the properties of constraint transposition and look into classical constraints. We then address the problem of generating the closed patterns of the original database satisfying the constraint, starting from those mined in the "transposed" database. Finally, we show how to generate all the patterns satisfying the constraint from the closed ones.


Nonclairvoyant Speed Scaling for Flow and Energy

Abstract: We study online nonclairvoyant speed scaling to minimize total flow time plus energy. We first consider the traditional model where the power function is P (s) = s\^\propto. We give a nonclairvoyant algorithm that is shown to be O(\propto\^3)-competitive. We then show an \Omega(\propto\^(1/3-\epsilon)) lower bound on the competitive ratio of any nonclairvoyant algorithm. We also show that there are power functions for which no nonclairvoyant algorithm can be O(1)-competitive.


An Approximation Algorithm for l\infty-Fitting Robinson Structures to Distances

Abstract: In this paper, we present a factor 16 approximation algorithm for the following NP-hard distance fitting problem: given a finite set X and a distance d on X, find a Robinsonian distance dR on X minimizing the l\infty-error ||d - dR||\infty = maxx,y\epsilonX {|d(x, y) - dR(x, y)|}. A distance dR on a finite set X is Robinsonian if its matrix can be symmetrically permuted so that its elements do not decrease when moving away from the main diagonal along any row or column. Robinsonian distances generalize ultrametrics, line distances and occur in the seriation problems and in classification.


Multi-Label Prediction via Compressed Sensing

Abstract: We consider multi-label prediction problems with large output spaces under the assumption of output sparsity -- that the target (label) vectors have small support. We develop a general theory for a variant of the popular error correcting output code scheme, using ideas from compressed sensing for exploiting this sparsity. The method can be regarded as a simple reduction from multi-label regression problems to binary regression problems. We show that the number of subproblems need only be logarithmic in the total number of possible labels, making this approach radically more efficient than others. We also state and prove robustness guarantees for this method in the form of regret transform bounds (in general), and also provide a more detailed analysis for the linear prediction setting.


A Note on Contractible Edges in Chordal Graphs

Abstract: Contraction of an edge merges its end points into a new vertex which is adjacent to each neighbor of the end points of the edge. An edge in a $k$-connected graph is {\em contractible} if its contraction does not result in a graph of lower connectivity. We characterize contractible edges in chordal graphs using properties of tree decompositions with respect to minimal vertex separators.


On the Additive Constant of the k-server Work Function Algorithm

Abstract: We consider the Work Function Algorithm for the k-server problem. We show that if the Work Function Algorithm is c-competitive, then it is also strictly (2c)-competitive. As a consequence of [Koutsoupias and Papadimitriou, JACM 1995] this also shows that the Work Function Algorithm is strictly (4k-2)-competitive.


Fundamental delay bounds in peer-to-peer chunk-based real-time streaming systems

Abstract: This paper addresses the following foundational question: what is the maximum theoretical delay performance achievable by an overlay peer-to-peer streaming system where the streamed content is subdivided into chunks? As shown in this paper, when posed for chunk-based systems, and as a consequence of the store-and-forward way in which chunks are delivered across the network, this question has a fundamentally different answer with respect to the case of systems where the streamed content is distributed through one or more flows (sub-streams). To circumvent the complexity emerging when directly dealing with delay, we express performance in term of a convenient metric, called "stream diffusion metric". We show that it is directly related to the end-to-end minimum delay achievable in a P2P streaming network. In a homogeneous scenario, we derive a performance bound for such metric, and we show how this bound relates to two fundamental parameters: the upload bandwidth available at each node, and the number of neighbors a node may deliver chunks to. In this bound, k-step Fibonacci sequences do emerge, and appear to set the fundamental laws that characterize the optimal operation of chunk-based systems.


The Price of Anarchy in Cooperative Network Creation Games

Abstract: In general, the games are played on a host graph, where each node is a selfish independent agent (player) and each edge has a fixed link creation cost \alpha. Together the agents create a network (a subgraph of the host graph) while selfishly minimizing the link creation costs plus the sum of the distances to all other players (usage cost). In this paper, we pursue two important facets of the network creation game. First, we study extensively a natural version of the game, called the cooperative model, where nodes can collaborate and share the cost of creating any edge in the host graph. We prove the first nontrivial bounds in this model, establishing that the price of anarchy is polylogarithmic in n for all values of α in complete host graphs. This bound is the first result of this type for any version of the network creation game; most previous general upper bounds are polynomial in n. Interestingly, we also show that equilibrium graphs have polylogarithmic diameter for the most natural range of \alpha (at most n polylg n). Second, we study the impact of the natural assumption that the host graph is a general graph, not necessarily complete. This model is a simple example of nonuniform creation costs among the edges (effectively allowing weights of \alpha and \infty). We prove the first assemblage of upper and lower bounds for this context, stablishing nontrivial tight bounds for many ranges of \alpha, for both the unilateral and cooperative versions of network creation. In particular, we establish polynomial lower bounds for both versions and many ranges of \alpha, even for this simple nonuniform cost model, which sharply contrasts the conjectured constant bounds for these games in complete (uniform) graphs.


Forward analysis for WSTS, Part I: Completions

Abstract: Well-structured transition systems provide the right foundation to compute a finite basis of the set of predecessors of the upward closure of a state. The dual problem, to compute a finite representation of the set of successors of the downward closure of a state, is harder: Until now, the theoretical framework for manipulating downward-closed sets was missing. We answer this problem, using insights from domain theory (dcpos and ideal completions), from topology (sobrifications), and shed new light on the notion of adequate domains of limits.


An Order on Sets of Tilings Corresponding to an Order on Languages

Abstract: Traditionally a tiling is defined with a finite number of finite forbidden patterns. We can generalize this notion considering any set of patterns. Generalized tilings defined in this way can be studied with a dynamical point of view, leading to the notion of subshift. In this article we establish a correspondence between an order on subshifts based on dynamical transformations on them and an order on languages of forbidden patterns based on computability properties.


A Comparison of Techniques for Sampling Web Pages

Abstract: As the World Wide Web is growing rapidly, it is getting increasingly challenging to gather representative information about it. Instead of crawling the web exhaustively one has to resort to other techniques like sampling to determine the properties of the web. A uniform random sample of the web would be useful to determine the percentage of web pages in a specific language, on a topic or in a top level domain. Unfortunately, no approach has been shown to sample the web pages in an unbiased way. Three promising web sampling algorithms are based on random walks. They each have been evaluated individually, but making a comparison on different data sets is not possible. We directly compare these algorithms in this paper. We performed three random walks on the web under the same conditions and analyzed their outcomes in detail. We discuss the strengths and the weaknesses of each algorithm and propose improvements based on experimental results.


Lower Bounds for Multi-Pass Processing of Multiple Data Streams

Abstract: This paper gives a brief overview of computation models for data stream processing, and it introduces a new model for multi-pass processing of multiple streams, the so-called mp2s-automata. Two algorithms for solving the set disjointness problem wi th these automata are presented. The main technical contribution of this paper is the proof of a lower bound on the size of memory and the number of heads that are required for solvin g the set disjointness problem with mp2s-automata.


Asymptotically Optimal Lower Bounds on the NIH-Multi-Party Information

Abstract: Here we prove an asymptotically optimal lower bound on the information complexity of the k-party disjointness function with the unique intersection promise, an important special case of the well known disjointness problem, and the ANDk-function in the number in the hand model. Our (n/k) bound for disjointness improves on an earlier (n/(k log k)) bound by Chakrabarti et al. (2003), who obtained an asymptotically tight lower bound for one-way protocols, but failed to do so for the general case. Our result eliminates both the gap between the upper and the lower bound for unrestricted protocols and the gap between the lower bounds for one-way protocols and unrestricted protocols.


Package upgrades in FOSS distributions: details and challenges

Abstract: The upgrade problems faced by Free and Open Source Software distributions have characteristics not easily found elsewhere. We describe the structure of packages and their role in the upgrade process. We show that state of the art package managers have shortcomings inhibiting their ability to cope with frequent upgrade failures. We survey current countermeasures to such failures, argue that they are not satisfactory, and sketch alternative solutions.


A baby steps/giant steps Monte Carlo algorithm for computing roadmaps in smooth compact real hypersurfaces

Abstract: We consider the problem of constructing roadmaps of real algebraic sets. The problem was introduced by Canny to answer connectivity questions and solve motion planning problems. Given $s$ polynomial equations with rational coefficients, of degree $D$ in $n$ variables, Canny's algorithm has a Monte Carlo cost of $s^n\log(s) D^{O(n^2)}$ operations in $\mathbb{Q}$; a deterministic version runs in time $s^n \log(s) D^{O(n^4)}$. The next improvement was due to Basu, Pollack and Roy, with an algorithm of deterministic cost $s^{d+1} D^{O(n^2)}$ for the more general problem of computing roadmaps of semi-algebraic sets ($d \le n$ is the dimension of an associated object). We give a Monte Carlo algorithm of complexity $(nD)^{O(n^{1.5})}$ for the problem of computing a roadmap of a compact hypersurface $V$ of degree $D$ in $n$ variables; we also have to assume that $V$ has a finite number of singular points. Even under these extra assumptions, no previous algorithm featured a cost better than $D^{O(n^2)}$.


Perfect Matchings in \~O(n^{1.5}) Time in Regular Bipartite Graphs

Abstract: We consider the well-studied problem of finding a perfect matching in $d$-regular bipartite graphs with $2n$ vertices and $m = nd$ edges. While the best-known algorithm for general bipartite graphs (due to Hopcroft and Karp) takes $O(m \sqrt{n})$ time, in regular bipartite graphs, a perfect matching is known to be computable in $O(m)$ time. Very recently, the $O(m)$ bound was improved to $O(\min\{m, \frac{n^{2.5}\ln n}{d}\})$ expected time, an expression that is bounded by $\tilde{O}(n^{1.75})$. In this paper, we further improve this result by giving an $O(\min\{m, \frac{n^2\ln^3 n}{d}\})$ expected time algorithm for finding a perfect matching in regular bipartite graphs; as a function of $n$ alone, the algorithm takes expected time $O((n\ln n)^{1.5})$. To obtain this result, we design and analyze a two-stage sampling scheme that reduces the problem of finding a perfect matching in a regular bipartite graph to the same problem on a subsampled bipartite graph with $O(n\ln n)$ edges that has a perfect matching with high probability. The matching is then recovered using the Hopcroft-Karp algorithm. While the standard analysis of Hopcroft-Karp gives us an $\tilde{O}(n^{1.5})$ running time, we present a tighter analysis for our special case that results in the stronger $\tilde{O}(\min\{m, \frac{n^2}{d} \})$ time mentioned earlier. Our proof of correctness of this sampling scheme uses a new correspondence theorem between cuts and Hall's theorem ``witnesses'' for a perfect matching in a bipartite graph that we prove. We believe this theorem may be of independent interest; as another example application, we show that a perfect matching in the support of an $n \times n$ doubly stochastic matrix with $m$ non-zero entries can be found in expected time $\tilde{O}(m + n^{1.5})$.


Improvements of real coded genetic algorithms based on differential operators preventing premature convergence

Abstract: This paper presents several types of evolutionary algorithms (EAs) used for global optimization on real domains. The interest has been focused on multimodal problems, where the difficulties of a premature convergence usually occurs. First the standard genetic algorithm (SGA) using binary encoding of real values and its unsatisfactory behavior with multimodal problems is briefly reviewed together with some improvements of fighting premature convergence. Two types of real encoded methods based on differential operators are examined in detail: the differential evolution (DE), a very modern and effective method firstly published by R. Storn and K. Price, and the simplified real-coded differential genetic algorithm SADE proposed by the authors. In addition, an improvement of the SADE method, called CERAF technology, enabling the population of solutions to escape from local extremes, is examined. All methods are tested on an identical set of objective functions and a systematic comparison based on a reliable methodology is presented. It is confirmed that real coded methods generally exhibit better behavior on real domains than the binary algorithms, even when extended by several improvements. Furthermore, the positive influence of the differential operators due to their possibility of self-adaptation is demonstrated. From the reliability point of view, it seems that the real encoded differential algorithm, improved by the technology described in this paper, is a universal and reliable method capable of solving all proposed test problems.


A competitive comparison of different types of evolutionary algorithms

Abstract: This paper presents comparison of several stochastic optimization algorithms developed by authors in their previous works for the solution of some problems arising in Civil Engineering. The introduced optimization methods are: the integer augmented simulated annealing (IASA), the real-coded augmented simulated annealing (RASA), the differential evolution (DE) in its original fashion developed by R. Storn and K. Price and simplified real-coded differential genetic algorithm (SADE). Each of these methods was developed for some specific optimization problem; namely the Chebychev trial polynomial problem, the so called type 0 function and two engineering problems - the reinforced concrete beam layout and the periodic unit cell problem respectively. Detailed and extensive numerical tests were performed to examine the stability and efficiency of proposed algorithms. The results of our experiments suggest that the performance and robustness of RASA, IASA and SADE methods are comparable, while the DE algorithm performs slightly worse. This fact together with a small number of internal parameters promotes the SADE method as the most robust for practical use.


Even Faster Exact Bandwidth

Abstract: We deal with exact algorithms for Bandwidth, a long studied NP-hard problem. For a long time nothing better than the trivial O*(n!) exhaustive search was known. In 2000, Feige an Kilian came up with a O*(10^n)-time algorithm. Recently we presented algorithm that runs in O*(5^n) time and O*(2^n) space.. In this paper we present a major modification to our algorithm which makes it run in O(4.83^n) time with the cost of O*(4^n) space complexity. This modification allowed us to perform Measure & Conquer analysis for the time complexity which was not used for such types of problems before.


Novel anisotropic continuum-discrete damage model capable of representing localized failure of massive structures. Part II: identification from tests under heterogeneous stress field

Abstract: In Part I of this paper we have presented a simple model capable of describing the localized failure of a massive structure. In this part, we discuss the identification of the model parameters from two kinds of experiments: a uniaxial tensile test and a three-point bending test. The former is used only for illustration of material parameter response dependence, and we focus mostly upon the latter, discussing the inverse optimization problem for which the specimen is subjected to a heterogeneous stress field.


Back analysis of microplane model parameters using soft computing methods

Abstract: A new procedure based on layered feed-forward neural networks for the microplane material model parameters identification is proposed in the present paper. Novelties are usage of the Latin Hypercube Sampling method for the generation of training sets, a systematic employment of stochastic sensitivity analysis and a genetic algorithm-based training of a neural network by an evolutionary algorithm. Advantages and disadvantages of this approach together with possible extensions are thoroughly discussed and analyzed.


Fast Evaluation of Interlace Polynomials on Graphs of Bounded Treewidth

Abstract: We consider the multivariate interlace polynomial introduced by Courcelle (2008), which generalizes several interlace polynomials defined by Arratia, Bollobas, and Sorkin (2004) and by Aigner and van der Holst (2004). We present an algorithm to evaluate the multivariate interlace polynomial of a graph with n vertices given a tree decomposition of the graph of width k. The best previously known result (Courcelle 2008) employs a general logical framework and leads to an algorithm with running time f(k)*n, where f(k) is doubly exponential in k. Analyzing the GF(2)-rank of adjacency matrices in the context of tree decompositions, we give a faster and more direct algorithm. Our algorithm uses 2^{3k^2+O(k)}*n arithmetic operations and can be efficiently implemented in parallel.


Linear Time Split Decomposition Revisited

Abstract: Given a family F of subsets of a ground set V, its orthogonal is defined to be the family of subsets that do not overlap any element of F. Using this tool we revisit the problem of designing a simple linear time algorithm for undirected graph split (also known as 1-join) decomposition.


On the Statistical Characterization of Flows in Internet Traffic with Application to Sampling

Abstract: A new method of estimating some statistical characteristics of TCP flows in the Internet is developed in this paper. For this purpose, a new set of random variables (referred to as observables) is defined. When dealing with sampled traffic, these observables can easily be computed from sampled data. By adopting a convenient mouse/elephant dichotomy also dependent on traffic, it is shown how these variables give a reliable statistical representation of the number of packets transmitted by large flows during successive time intervals with an appropriate duration. A mathematical framework is developed to estimate the accuracy of the method. As an application, it is shown how one can estimate the number of large TCP flows when only sampled traffic is available. The algorithm proposed is tested against experimental data collected from different types of IP networks.


Optimal cache-aware suffix selection

Abstract: Given string $S[1..N]$ and integer $k$, the {\em suffix selection} problem is to determine the $k$th lexicographically smallest amongst the suffixes $S[i... N]$, $1 \leq i \leq N$. We study the suffix selection problem in the cache-aware model that captures two-level memory inherent in computing systems, for a \emph{cache} of limited size $M$ and block size $B$. The complexity of interest is the number of block transfers. We present an optimal suffix selection algorithm in the cache-aware model, requiring $\Thetah{N/B}$ block transfers, for any string $S$ over an unbounded alphabet (where characters can only be compared), under the common tall-cache assumption (i.e. $M=\Omegah{B^{1+\epsilon}}$, where $\epsilon<1$). Our algorithm beats the bottleneck bound for permuting an input array to the desired output array, which holds for nearly any nontrivial problem in hierarchical memory models.


Correlation Robust Stochastic Optimization

Abstract: We consider a robust model proposed by Scarf, 1958, for stochastic optimization when only the marginal probabilities of (binary) random variables are given, and the correlation between the random variables is unknown. In the robust model, the objective is to minimize expected cost against worst possible joint distribution with those marginals. We introduce the concept of correlation gap to compare this model to the stochastic optimization model that ignores correlations and minimizes expected cost under independent Bernoulli distribution. We identify a class of functions, using concepts of summable cost sharing schemes from game theory, for which the correlation gap is well-bounded and the robust model can be approximated closely by the independent distribution model. As a result, we derive efficient approximation factors for many popular cost functions, like submodular functions, facility location, and Steiner tree. As a byproduct, our analysis also yields some new results in the areas of social welfare maximization and existence of Walrasian equilibria, which may be of independent interest.


Matrix Graph Grammars with Application Conditions

Abstract: In the Matrix approach to graph transformation we represent simple digraphs and rules with Boolean matrices and vectors, and the rewriting is expressed using Boolean operators only. In previous works, we developed analysis techniques enabling the study of the applicability of rule sequences, their independence, state reachability and the minimal graph able to fire a sequence. In the present paper we improve our framework in two ways. First, we make explicit (in the form of a Boolean matrix) some negative implicit information in rules. This matrix (called nihilation matrix) contains the elements that, if present, forbid the application of the rule (i.e. potential dangling edges, or newly added edges, which cannot be already present in the simple digraph). Second, we introduce a novel notion of application condition, which combines graph diagrams together with monadic second order logic. This allows for more flexibility and expressivity than previous approaches, as well as more concise conditions in certain cases. We demonstrate that these application conditions can be embedded into rules (i.e. in the left hand side and the nihilation matrix), and show that the applicability of a rule with arbitrary application conditions is equivalent to the applicability of a sequence of plain rules without application conditions. Therefore, the analysis of the former is equivalent to the analysis of the latter, showing that in our framework no additional results are needed for the study of application conditions. Moreover, all analysis techniques of [21, 22] for the study of sequences can be applied to application conditions.


Optimal Probabilistic Ring Exploration by Asynchronous Oblivious Robots

Abstract: We consider a team of $k$ identical, oblivious, asynchronous mobile robots that are able to sense (\emph{i.e.}, view) their environment, yet are unable to communicate, and evolve on a constrained path. Previous results in this weak scenario show that initial symmetry yields high lower bounds when problems are to be solved by \emph{deterministic} robots. In this paper, we initiate research on probabilistic bounds and solutions in this context, and focus on the \emph{exploration} problem of anonymous unoriented rings of any size. It is known that $\Theta(\log n)$ robots are necessary and sufficient to solve the problem with $k$ deterministic robots, provided that $k$ and $n$ are coprime. By contrast, we show that \emph{four} identical probabilistic robots are necessary and sufficient to solve the same problem, also removing the coprime constraint. Our positive results are constructive.


Polynomial Kernelizations for MIN F^+Pi_1 and MAX NP

Abstract: It has been observed in many places that constant-factor approximable problems often admit polynomial or even linear problem kernels for their decision versions, e.g., Vertex Cover, Feedback Vertex Set, and Triangle Packing. While there exist examples like Bin Packing, which does not admit any kernel unless P = NP, there apparently is a strong relation between these two polynomial-time techniques. We add to this picture by showing that the natural decision versions of all problems in two prominent classes of constant-factor approximable problems, namely MIN F^+\Pi_1 and MAX NP, admit polynomial problem kernels. Problems in MAX SNP, a subclass of MAX NP, are shown to admit kernels with a linear base set, e.g., the set of vertices of a graph. This extends results of Cai and Chen (JCSS 1997), stating that the standard parameterizations of problems in MAX SNP and MIN F^+\Pi_1 are fixed-parameter tractable, and complements recent research on problems that do not admit polynomial kernelizations (Bodlaender et al. JCSS 2009).


A Superpolynomial Lower Bound on the Size of Uniform Non-constant-depth Threshold Circuits for the Permanent

Abstract: We show that the permanent cannot be computed by DLOGTIME-uniform threshold or arithmetic circuits of depth o(log log n) and polynomial size.


Local Multicoloring Algorithms: Computing a Nearly-Optimal TDMA Schedule in Constant Time

Abstract: The described multicoloring problem has direct applications in the context of wireless ad hoc and sensor networks. In order to coordinate the access to the shared wireless medium, the nodes of such a network need to employ some medium access control (MAC) protocol. Typical MAC protocols control the access to the shared channel by time (TDMA), frequency (FDMA), or code division multiple access (CDMA) schemes. Many channel access schemes assign a fixed set of time slots, frequencies, or (orthogonal) codes to the nodes of a network such that nodes that interfere with each other receive disjoint sets of time slots, frequencies, or code sets. Finding a valid assignment of time slots, frequencies, or codes hence directly corresponds to computing a multicoloring of a graph $G$. The scarcity of bandwidth, energy, and computing resources in ad hoc and sensor networks, as well as the often highly dynamic nature of these networks require that the multicoloring can be computed based on as little and as local information as possible.


Abstraction and Refinement in Static Model-Checking

Abstract: interpretation is a general methodology for building static analyses of programs. It was introduced by P. and R. Cousot in \cite{cc}. We present, in this paper, an application of a generic abstract interpretation to domain of model-checking. Dynamic checking are usually easier to use, because the concept are establishe d and wide well know. But they are usually limited to systems whose states space is finite. In an other part, certain faults cannot be detected dynamically, even by keeping track of the history of the states space.Indeed, the classical problem of finding the right test cases is far from trivial and limit the abilities of dynamic checkers further. Static checking have the advantage that they work on a more abstract level than dynamic checker and can verify system properties for all inputs. Problem, it is hard to guarantee that a violation of a modeled property corresponds to a fault in the concrete system. We propose an approach, in which we generate counter-examples dynamically using the abstract interpretation techniques.


A Proof of Concept for Optimizing Task Parallelism by Locality Queues

Abstract: Task parallelism as employed by the OpenMP task construct, although ideal for tackling irregular problems or typical producer/consumer schemes, bears some potential for performance bottlenecks if locality of data access is important, which is typically the case for memory-bound code on ccNUMA systems. We present a programming technique which ameliorates adverse effects of dynamic task distribution by sorting tasks into locality queues, each of which is preferably processed by threads that belong to the same locality domain. Dynamic scheduling is fully preserved inside each domain, and is preferred over possible load imbalance even if non-local access is required. The effectiveness of the approach is demonstrated using a blocked six-point stencil solver as a toy model.


NNRU, a noncommutative analogue of NTRU

Abstract: NTRU public key cryptosystem is well studied lattice-based Cryptosystem along with Ajtai-Dwork and GGH systems. Underlying NTRU is a hard mathematical problem of finding short vectors in a certain lattice. (Shamir 1997) presented a lattice-based attack by which he could find the original secret key or alternate key. Shamir concluded if one designs a variant of NTRU where the calculations involved during encryption and decryption are non-commutative then the system will be secure against Lattice based attack.This paper presents a new cryptosystem with above property and we have proved that it is completely secure against Lattice based attack. It operates in the non-commutative ring M=M_k Z[X]/(X^n - I_{k*k}, where M is a matrix ring of k*k matrices of polynomials in R={Z}[X]/(X^n-1). Moreover We have got speed improvement by a factor of O(k^{1.624) over NTRU for the same bit of information.


Topological Centrality and Its Applications

Abstract: Recent development of network structure analysis shows that it plays an important role in characterizing complex system of many branches of sciences. Different from previous network centrality measures, this paper proposes the notion of topological centrality (TC) reflecting the topological positions of nodes and edges in general networks, and proposes an approach to calculating the topological centrality. The proposed topological centrality is then used to discover communities and build the backbone network. Experiments and applications on research network show the significance of the proposed approach.


Strong Completeness of Coalgebraic Modal Logics

Abstract: Canonical models are of central importance in modal logic, in particular as they witness strong completeness and hence compactness. While the canonical model construction is well understood for Kripke semantics, non-normal modal logics often present subtle difficulties - up to the point that canonical models may fail to exist, as is the case e.g. in most probabilistic logics. Here, we present a generic canonical model construction in the semantic framework of coalgebraic modal logic, which pinpoints coherence conditions between syntax and semantics of modal logics that guarantee strong completeness. We apply this method to reconstruct canonical model theorems that are either known or folklore, and moreover instantiate our method to obtain new strong completeness results. In particular, we prove strong completeness of graded modal logic with finite multiplicities, and of the modal logic of exact probabilities.


Polynomial Size Analysis of First-Order Shapely Functions

Abstract: We present a size-aware type system for first-order shapely function definitions. Here, a function definition is called shapely when the size of the result is determined exactly by a polynomial in the sizes of the arguments. Examples of shapely function definitions may be implementations of matrix multiplication and the Cartesian product of two lists. The type system is proved to be sound w.r.t. the operational semantics of the language. The type checking problem is shown to be undecidable in general. We define a natural syntactic restriction such that the type checking becomes decidable, even though size polynomials are not necessarily linear or monotonic. Furthermore, we have shown that the type-inference problem is at least semi-decidable (under this restriction). We have implemented a procedure that combines run-time testing and type-checking to automatically obtain size dependencies. It terminates on total typable function definitions.


Languages recognized by nondeterministic quantum finite automata

Abstract: The nondeterministic quantum finite automaton (NQFA) is the only known case where a one-way quantum finite automaton (QFA) model has been shown to be strictly superior in terms of language recognition power to its probabilistic counterpart. We give a characterization of the class of languages recognized by NQFA's, demonstrating that it is equal to the class of exclusive stochastic languages. We also characterize the class of languages that are recognized necessarily by two-sided error by QFA's. It is shown that these classes remain the same when the QFA's used in their definitions are replaced by several different model variants that have appeared in the literature. We prove several closure properties of the related classes. The ramifications of these results about classical and quantum sublogarithmic space complexity classes are examined.


Tableau-based decision procedure for full coalitional multiagent temporal-epistemic logic of linear time

Abstract: We develop a tableau-based decision procedure for the full coalitional multiagent temporal-epistemic logic of linear time CMATEL(CD+LT). It extends LTL with operators of common and distributed knowledge for all coalitions of agents. The tableau procedure runs in exponential time, matching the lower bound obtained by Halpern and Vardi for a fragment of our logic, thus providing a complexity-optimal decision procedure for CMATEL(CD+LT).


Qualitative Concurrent Stochastic Games with Imperfect Information

Abstract: We study a model of games that combines concurrency, imperfect information and stochastic aspects. Those are finite states games in which, at each round, the two players choose, simultaneously and independently, an action. Then a successor state is chosen accordingly to some fixed probability distribution depending on the previous state and on the pair of actions chosen by the players. Imperfect information is modeled as follows: both players have an equivalence relation over states and, instead of observing the exact state, they only know to which equivalence class it belongs. Therefore, if two partial plays are indistinguishable by some player, he should behave the same in both of them. We consider reachability (does the play eventually visit a final state?) and B\"uchi objective (does the play visit infinitely often a final state?). Our main contribution is to prove that the following problem is complete for 2-ExpTime: decide whether the first player has a strategy that ensures her to almost-surely win against any possible strategy of her oponent. We also characterise those strategies needed by the first player to almost-surely win.


Tableau-based procedure for deciding satisfiability in the full coalitional multiagent epistemic logic

Abstract: We study the multiagent epistemic logic CMAELCD with operators for common and distributed knowledge for all coalitions of agents. We introduce Hintikka structures for this logic and prove that satisfiability in such structures is equivalent to satisfiability in standard models. Using this result, we design an incremental tableau based decision procedure for testing satisfiability in CMAELCD.


A formally verified compiler back-end

Abstract: This article describes the development and formal verification (proof of semantic preservation) of a compiler back-end from Cminor (a simple imperative intermediate language) to PowerPC assembly code, using the Coq proof assistant both for programming the compiler and for proving its correctness. Such a verified compiler is useful in the context of formal methods applied to the certification of critical software: the verification of the compiler guarantees that the safety properties proved on the source code hold for the executable compiled code as well.


Ambiguity and Communication

Abstract: The ambiguity of a nondeterministic finite automaton (NFA) N for input size n is the maximal number of accepting computations of N for an input of size n. For all k, r 2 N we construct languages Lr,k which can be recognized by NFA's with size k poly(r) and ambiguity O(nk), but Lr,k has only NFA's with exponential size, if ambiguity o(nk) is required. In particular, a hierarchy for polynomial ambiguity is obtained, solving a long standing open problem (Ravikumar and Ibarra, 1989, Leung, 1998).


A Stronger LP Bound for Formula Size Lower Bounds via Clique Constraints

Abstract: We introduce a new technique proving formula size lower bounds based on the linear programming bound originally introduced by Karchmer, Kushilevitz and Nisan [11] and the theory of stable set polytope. We apply it to majority functions and prove their formula size lower bounds improved from the classical result of Khrapchenko [13]. Moreover, we introduce a notion of unbalanced recursive ternary majority functions motivated by a decomposition theory of monotone self-dual functions and give integrally matching upper and lower bounds of their formula size. We also show monotone formula size lower bounds of balanced recursive ternary majority functions improved from the quantum adversary bound of Laplante, Lee and Szegedy [15].


A Generalization of Nemhauser and Trotter's Local Optimization Theorem

Abstract: The Nemhauser-Trotter local optimization theorem applies to the NP-hard Vertex Cover problem and has applications in approximation as well as parameterized algorithmics. We present a framework that generalizes Nemhauser and Trotter's result to vertex deletion and graph packing problems, introducing novel algorithmic strategies based on purely combinatorial arguments (not referring to linear programming as the Nemhauser-Trotter result originally did). We exhibit our framework using a generalization of Vertex Cover, called Bounded- Degree Deletion, that has promise to become an important tool in the analysis of gene and other biological networks. For some fixed d \geq 0, Bounded-Degree Deletion asks to delete as few vertices as possible from a graph in order to transform it into a graph with maximum vertex degree at most d. Vertex Cover is the special case of d = 0. Our generalization of the Nemhauser-Trotter theorem implies that Bounded-Degree Deletion has a problem kernel with a linear number of vertices for every constant d. We also outline an application of our extremal combinatorial approach to the problem of packing stars with a bounded number of leaves. Finally, charting the border between (parameterized) tractability and intractability for Bounded-Degree Deletion, we provide a W[2]-hardness result for Bounded-Degree Deletion in case of unbounded d-values.


Computing Graph Roots Without Short Cycles

Abstract: Graph G is the square of graph H if two vertices x, y have an edge in G if and only if x, y are of distance at most two in H. Given H it is easy to compute its square H2, however Motwani and Sudan proved that it is NP-complete to determine if a given graph G is the square of some graph H (of girth 3). In this paper we consider the characterization and recognition problems of graphs that are squares of graphs of small girth, i.e. to determine if G = H2 for some graph H of small girth. The main results are the following. - There is a graph theoretical characterization for graphs that are squares of some graph of girth at least 7. A corollary is that if a graph G has a square root H of girth at least 7 then H is unique up to isomorphism. - There is a polynomial time algorithm to recognize if G = H2 for some graph H of girth at least 6. - It is NP-complete to recognize if G = H2 for some graph H of girth 4. These results almost provide a dichotomy theorem for the complexity of the recognition problem in terms of girth of the square roots. The algorithmic and graph theoretical results generalize previous results on tree square roots, and provide polynomial time algorithms to compute a graph square root of small girth if it exists. Some open questions and conjectures will also be discussed.


B\"uchi complementation made tight

Abstract: The precise complexity of complementing B\"uchi automata is an intriguing and long standing problem. While optimal complementation techniques for finite automata are simple - it suffices to determinize them using a simple subset construction and to dualize the acceptance condition of the resulting automaton - B\"uchi complementation is more involved. Indeed, the construction of an EXPTIME complementation procedure took a quarter of a century from the introduction of B\"uchi automata in the early 60s, and stepwise narrowing the gap between the upper and lower bound to a simple exponent (of (6e)n for B\"uchi automata with n states) took four decades. While the distance between the known upper (O'(0.96 n)n') and lower ('(0.76 n)n') bound on the required number of states has meanwhile been significantly reduced, an exponential factor remains between them. Also, the upper bound on the size of the complement automaton is not linear in the bound of its state space. These gaps are unsatisfactory from a theoretical point of view, but also because B\"uchi complementation is a useful tool in formal verification, in particular for the language containment problem. This paper proposes a B\"uchi complementation algorithm whose complexity meets, modulo a quadratic (O(n2)) factor, the known lower bound for B\"uchi complementation. It thus improves over previous constructions by an exponential factor and concludes the quest for optimal B\"uchi complementation algorithms.


Spanning Trees of Bounded Degree Graphs

Abstract: We consider lower bounds on the number of spanning trees of connected graphs with degree bounded by $d$. The question is of interest because such bounds may improve the analysis of the improvement produced by memorisation in the runtime of exponential algorithms. The value of interest is the constant $\beta_d$ such that all connected graphs with degree bounded by $d$ have at least $\beta_d^\mu$ spanning trees where $\mu$ is the cyclomatic number or excess of the graph, namely $m-n+1$. We conjecture that $\beta_d$ is achieved by the complete graph $K_{d+1}$ but we have not proved this for any $d$ greater than 3. We give weaker lower bounds on $\beta_d$ for $d\le 11$.


A principal component analysis of 39 scientific impact measures

Abstract: The impact of scientific publications has traditionally been expressed in terms of citation counts. However, scientific activity has moved online over the past decade. To better capture scientific impact in the digital era, a variety of new impact measures has been proposed on the basis of social network analysis and usage log data. Here we investigate how these new measures relate to each other, and how accurately and completely they express scientific impact. We performed a principal component analysis of the rankings produced by 39 existing and proposed measures of scholarly impact that were calculated on the basis of both citation and usage log data. Our results indicate that the notion of scientific impact is a multi-dimensional construct that can not be adequately measured by any single indicator, although some measures are more suitable than others. The commonly used citation Impact Factor is not positioned at the core of this construct, but at its periphery, and should thus be used with caution.


A List of Household Objects for Robotic Retrieval Prioritized by People with ALS (Version 092008)

Abstract: This technical report is designed to serve as a citable reference for the original prioritized object list that the Healthcare Robotics Lab at Georgia Tech released on its website in September of 2008. It is also expected to serve as the primary citable reference for the research associated with this list until the publication of a detailed, peer-reviewed paper. The original prioritized list of object classes resulted from a needs assessment involving 8 motor-impaired patients with amyotrophic lateral sclerosis (ALS) and targeted, in-person interviews of 15 motor-impaired ALS patients. All of these participants were drawn from the Emory ALS Center. The prioritized object list consists of 43 object classes ranked by how important the participants considered each class to be for retrieval by an assistive robot. We intend for this list to be used by researchers to inform the design and benchmarking of robotic systems, especially research related to autonomous mobile manipulation.


A Standalone Markerless 3D Tracker for Handheld Augmented Reality

Abstract: This paper presents an implementation of a markerless tracking technique targeted to the Windows Mobile Pocket PC platform. The primary aim of this work is to allow the development of standalone augmented reality applications for handheld devices based on natural feature tracking. In order to achieve this goal, a subset of two computer vision libraries was ported to the Pocket PC platform. They were also adapted to use fixed point math, with the purpose of improving the overall performance of the routines. The port of these libraries opens up the possibility of having other computer vision tasks being executed on mobile platforms. A model based tracking approach that relies on edge information was adopted. Since it does not require a high processing power, it is suitable for constrained devices such as handhelds. The OpenGL ES graphics library was used to perform computer vision tasks, taking advantage of existing graphics hardware acceleration. An augmented reality application was created using the implemented technique and evaluations were done regarding tracking performance and accuracy


Feature Hashing for Large Scale Multitask Learning

Abstract: Empirical evidence suggests that hashing is an effective strategy for dimensionality reduction and practical nonparametric estimation. In this paper we provide exponential tail bounds for feature hashing and show that the interaction between random subspaces is negligible with high probability. We demonstrate the feasibility of this approach with experimental results for a new use case -- multitask learning with hundreds of thousands of tasks.


Online Scheduling of Bounded Length Jobs to Maximize Throughput

Abstract: We consider an online scheduling problem, motivated by the issues present at the joints of networks using ATM and TCP/IP. Namely, IP packets have to broken down to small ATM cells and sent out before their deadlines, but cells corresponding to different packets can be interwoven. More formally, we consider the online scheduling problem with preemptions, where each job j is revealed at release time r_j, has processing time p_j, deadline d_j and weight w_j. A preempted job can be resumed at any time. The goal is to maximize the total weight of all jobs completed on time. Our main result are as follows: we prove that if all jobs have processing time exactly k, the deterministic competitive ratio is between 2.598 and 5, and when the processing times are at most k, the deterministic competitive ratio is Theta(k/log k).


BagPack: A general framework to represent semantic relations

Abstract: We introduce a way to represent word pairs instantiating arbitrary semantic relations that keeps track of the contexts in which the words in the pair occur both together and independently. The resulting features are of sufficient generality to allow us, with the help of a standard supervised machine learning algorithm, to tackle a variety of unrelated semantic tasks with good results and almost no task-specific tailoring.


A Dichotomy Theorem for Polynomial Evaluation

Abstract: A dichotomy theorem for counting problems due to Creignou and Hermann states that or any nite set S of logical relations, the counting problem #SAT(S) is either in FP, or #P-complete. In the present paper we show a dichotomy theorem for polynomial evaluation. That is, we show that for a given set S, either there exists a VNP-complete family of polynomials associated to S, or the associated families of polynomials are all in VP. We give a concise characterization of the sets S that give rise to "easy" and "hard" polynomials. We also prove that several problems which were known to be #P-complete under Turing reductions only are in fact #P-complete under many-one reductions.


What's in a Message?

Abstract: In this paper we present the first step in a larger series of experiments for the induction of predicate/argument structures. The structures that we are inducing are very similar to the conceptual structures that are used in Frame Semantics (such as FrameNet). Those structures are called messages and they were previously used in the context of a multi-document summarization system of evolving events. The series of experiments that we are proposing are essentially composed from two stages. In the first stage we are trying to extract a representative vocabulary of words. This vocabulary is later used in the second stage, during which we apply to it various clustering approaches in order to identify the clusters of predicates and arguments--or frames and semantic roles, to use the jargon of Frame Semantics. This paper presents in detail and evaluates the first stage.


XML Representation of Constraint Networks: Format XCSP 2.1

Abstract: We propose a new extended format to represent constraint networks using XML. This format allows us to represent constraints defined either in extension or in intension. It also allows us to reference global constraints. Any instance of the problems CSP (Constraint Satisfaction Problem), QCSP (Quantified CSP) and WCSP (Weighted CSP) can be represented using this format.


A Multi-Round Communication Lower Bound for Gap Hamming and Some Consequences

Abstract: The Gap-Hamming-Distance problem arose in the context of proving space lower bounds for a number of key problems in the data stream model. In this problem, Alice and Bob have to decide whether the Hamming distance between their $n$-bit input strings is large (i.e., at least $n/2 + \sqrt n$) or small (i.e., at most $n/2 - \sqrt n$); they do not care if it is neither large nor small. This $\Theta(\sqrt n)$ gap in the problem specification is crucial for capturing the approximation allowed to a data stream algorithm. Thus far, for randomized communication, an $\Omega(n)$ lower bound on this problem was known only in the one-way setting. We prove an $\Omega(n)$ lower bound for randomized protocols that use any constant number of rounds. As a consequence we conclude, for instance, that $\epsilon$-approximately counting the number of distinct elements in a data stream requires $\Omega(1/\epsilon^2)$ space, even with multiple (a constant number of) passes over the input stream. This extends earlier one-pass lower bounds, answering a long-standing open question. We obtain similar results for approximating the frequency moments and for approximating the empirical entropy of a data stream. In the process, we also obtain tight $n - \Theta(\sqrt{n}\log n)$ lower and upper bounds on the one-way deterministic communication complexity of the problem. Finally, we give a simple combinatorial proof of an $\Omega(n)$ lower bound on the one-way randomized communication complexity.


Group-Theoretic Partial Matrix Multiplication

Abstract: A generalization of recent group-theoretic matrix multiplication algorithms to an analogue of the theory of partial matrix multiplication is presented. We demonstrate that the added flexibility of this approach can in some cases improve upper bounds on the exponent of matrix multiplication yielded by group-theoretic full matrix multiplication. The group theory behind our partial matrix multiplication algorithms leads to the problem of maximizing a quantity representing the "fullness" of a given partial matrix pattern. This problem is shown to be NP-hard, and two algorithms, one optimal and another non-optimal but polynomial-time, are given for solving it.


Self-Assembly as Graph Grammar as Distributed System

Abstract: In 2004, Klavins et al. introduced the use of graph grammars to describe -- and to program -- systems of self-assembly. It turns out that these graph grammars are a "dual notion" of a graph rewriting characterization of distributed systems that was proposed by Degano and Montanari over twenty years ago. By applying techniques obtained from this observation, we prove a generalized version of Soloveichik and Winfree's theorem on local determinism, and we also present a canonical method to simulate asynchronous constant-size-message-passing models of distributed computing with systems of self-assembly.


A Time Lower Bound for Multiple Nucleation on a Surface

Abstract: Majumder, Reif and Sahu have presented a stochastic model of reversible, error-permitting, two-dimensional tile self-assembly, and showed that restricted classes of tile assembly systems achieved equilibrium in (expected) polynomial time. One open question they asked was how much computational power would be added if the model permitted multiple nucleation, i.e., independent groups of tiles growing before attaching to the original seed assembly. This paper provides a partial answer, by proving that if a tile assembly model uses only local binding rules, then it cannot use multiple nucleation on a surface to solve certain "simple" problems in constant time (time independent of the size of the surface). Moreover, this time bound applies to macroscale robotic systems that assemble in a three-dimensional grid, not just to tile assembly systems on a two-dimensional surface. The proof technique defines a new model of distributed computing that simulates tile (and robotic) self-assembly. Keywords: self-assembly, multiple nucleation, locally checkable labeling.


A Recursive Threshold Visual Cryptography Scheme

Abstract: This paper presents a recursive hiding scheme for 2 out of 3 secret sharing. In recursive hiding of secrets, the user encodes additional information about smaller secrets in the shares of a larger secret without an expansion in the size of the latter, thereby increasing the efficiency of secret sharing. We present applications of our proposed protocol to images as well as text.


The Forgiving Graph: A distributed data structure for low stretch under adversarial attack

Abstract: We consider the problem of self-healing in peer-to-peer networks that are under repeated attack by an omniscient adversary. We assume that, over a sequence of rounds, an adversary either inserts a node with arbitrary connections or deletes an arbitrary node from the network. The network responds to each such change by quick "repairs," which consist of adding or deleting a small number of edges. These repairs essentially preserve closeness of nodes after adversarial deletions, without increasing node degrees by too much, in the following sense. At any point in the algorithm, nodes $v$ and $w$ whose distance would have been $\ell$ in the graph formed by considering only the adversarial insertions (not the adversarial deletions), will be at distance at most $\ell \log n$ in the actual graph, where $n$ is the total number of vertices seen so far. Similarly, at any point, a node $v$ whose degree would have been $d$ in the graph with adversarial insertions only, will have degree at most 3d in the actual graph. Our algorithm is completely distributed and has low latency and bandwidth requirements.


Hyperset Approach to Semi-structured Databases and the Experimental Implementation of the Query Language Delta

Abstract: This thesis presents practical suggestions towards the implementation of the hyperset approach to semi-structured databases and the associated query language Delta. This work can be characterised as part of a top-down approach to semi-structured databases, from theory to practice. The main original part of this work consisted in implementation of the hyperset Delta query language to semi-structured databases, including worked example queries. In fact, the goal was to demonstrate the practical details of this approach and language. The required development of an extended, practical version of the language based on the existing theoretical version, and the corresponding operational semantics. Here we present detailed description of the most essential steps of the implementation. Another crucial problem for this approach was to demonstrate how to deal in reality with the concept of the equality relation between (hyper)sets, which is computationally realised by the bisimulation relation. In fact, this expensive procedure, especially in the case of distributed semi-structured data, required some additional theoretical considerations and practical suggestions for efficient implementation. To this end the 'local/global' strategy for computing the bisimulation relation over distributed semi-structured data was developed and its efficiency was experimentally confirmed.


Creating modular and reusable DSL textual syntax definitions with Grammatic/ANTLR

Abstract: In this paper we present Grammatic -- a tool for textual syntax definition. Grammatic serves as a front-end for parser generators (and other tools) and brings modularity and reuse to their development artifacts. It adapts techniques for separation of concerns from Apsect-Oriented Programming to grammars and uses templates for grammar reuse. We illustrate usage of Grammatic by describing a case study: bringing separation of concerns to ANTLR parser generator, which is achieved without a common time- and memory-consuming technique of building an AST to separate semantic actions from a grammar definition.