33 research outputs found

    Extensional and Intensional Strategies

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    This paper is a contribution to the theoretical foundations of strategies. We first present a general definition of abstract strategies which is extensional in the sense that a strategy is defined explicitly as a set of derivations of an abstract reduction system. We then move to a more intensional definition supporting the abstract view but more operational in the sense that it describes a means for determining such a set. We characterize the class of extensional strategies that can be defined intensionally. We also give some hints towards a logical characterization of intensional strategies and propose a few challenging perspectives

    Reducing the Cost of Grammar-Based Testing Using Pattern Coverage

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    Part 2: Test Derivation MethodsInternational audienceIn grammar-based testing, context-free grammars may be used to generate relevant test inputs for language processors, or meta programs, such as programming language compilers, refactoring tools, and implementations of software quality metrics. This technique can be used to test these meta programs, but the amount of sentences, and syntax trees thereof, which needs to be generated to obtain reasonable coverage of the input language is exponential.Pattern matching is a programming language feature used often when writing meta programs. Pattern matching helps because it automates the frequently occurring task of detecting shapes in, and extracting information from syntax trees. However, meta programs which contain many patterns are difficult to test using only randomly generated sentences from grammar rules. The reason is that statistically it is uncommon to directly generate sentences which accidentally match the patterns in the code.To solve this problem, in this paper we extract information from the patterns in the code of meta programs to guide the sentence generation process. We introduce a new coverage criterion, called Pattern Coverage, which focuses on providing a test strategy to reduce the amount of test necessary cases, while covering the relevant parts of the meta program. An initial experimental evaluation is presented and the result is compared with traditional grammar-based testing

    Labelled Graph Rewriting Meets Social Networks

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    International audienceThe intense development of computing techniques and the increasing volumes of produced data raise many modelling and analysis challenges. There is a need to represent and analyse information that is: complex –due to the presence of massive and highly heterogeneous data–, dynamic –due to interactions, time, external and internal evolutions–, connected and distributed in networks. We argue in this work that relevant concepts to address these challenges are provided by three ingredients: labelled graphs to represent networks of data or objects; rewrite rules to deal with concurrent local transformations; strategies to express control versus autonomy and to focus on points of interests. To illustrate the use of these concepts, we choose to focus our interest on social networks analysis, and more precisely in this paper on random network generation. Labelled graph strategic rewriting provides a formalism in which different models can be generated and compared. Conversely, the study of social networks, with their size and complexity, stimulates the search for structure and efficiency in graph rewriting. It also motivated the design of new or more general kinds of graphs, rules and strategies (for instance, to define positions in graphs), which are illustrated here. This opens the way to further theoretical and practical questions for the rewriting community

    Building and Combining Matching Algorithms

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    International audienceThe concept of matching is ubiquitous in declarative programming and in automated reasoning. For instance, it is a key mechanism to run rule-based programs and to simplify clauses generated by theorem provers. A matching problem can be seen as a particular conjunction of equations where each equation has a ground side. We give an overview of techniques that can be applied to build and combine matching algorithms. First, we survey mutation-based techniques as a way to build a generic matching algorithm for a large class of equational theories. Second, combination techniques are introduced to get combined matching algorithms for disjoint unions of theories. Then we show how these combination algorithms can be extended to handle non-disjoint unions of theories sharing only constructors. These extensions are possible if an appropriate notion of normal form is computable

    Toxicity of Ag, CuO and ZnO nanoparticles to selected environmentally relevant test organisms and mammalian cells in vitro: a critical review

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    Probabilistic rewrite strategies. Applications to ELAN

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    Colloque avec actes et comité de lecture. internationale.International audienceRecently rule based languages focussed on the use of rewriting as a modeling tool which results in making specifications executable. To extend the modeling capabilities of rule based languages, we explore the possibility of making the rule applications subject to probabilistic choices. We propose an extension of the Elan strategy language to deal with randomized systems. We argue through several examples that we propose indeed a natural setting to model systems with randomized choices. This leads us to interesting new problems, and we address the generalization of the usual concepts in abstract reduction systems to randomized systems
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