La construction du poète

Comment Gérald Leblanc s’est-il fait poète? La réponse peut se trouver dans son oeuvre poétique. Deux explications peuvent s’avérer utiles. Dans son enfance, le poète découvrit un accès à une sorte d’équivalence universelle, qu’il devait appeler plus tard « Acadie », c’est-à-dire sans doute poésie. Cela entraînait une vision nouvelle de la langue, clé de l’analogie plutôt que système de différences. Cette expérience s’était donnée dans une coïncidence avec l’espace et le temps. Il arrive donc que le poème soit rencontré, étant, dans sa forme idéale, éternel. Une histoire concurrente fait du poète un travailleur patient à l’écoute des bredouillements de la ville, bâtissant son autoportrait avec des choses trouvées en chemin. Il réclame un sens politique, et vit dans un monde de prose commune, mais ne peut être compris que dans une lecture poétique. Les deux tableaux sont également vrais.How did Gérald Leblanc become a poet? The answer can be found in his poetic works. Two accounts might prove helpful. During his childhood, the poet gained access to a kind of universal equivalence which he later called “Acadie” clearly another name for poetry. This led to a fresh view of language as a key to analogy rather than a system of differences. This experience was provided by an intimate encounter with time and space. Thus the poem is encountered its ideal form, as being eternal. An alternative story shows the poet as a worker, listening patiently to the mumblings of the town, constructing his self-portrait out of things found along the way. He claims a political meaning and lives in a world of ordinary prose, but can only be understood through a poetic reading. Both pictures are equally true

Les groupements d'éleveurs. I- L'organisation

Cette fiche décrit en détail l'organisation des groupements d'éleveurs : les préalables à leur création, les conditions nécessaires à leur bon fonctionement, et leur structuration en unions ou fédération

PLTL Partitioned Model Checking for Reactive Systems under Fairness Assumptions

We are interested in verifying dynamic properties of finite state reactive systems under fairness assumptions by model checking. The systems we want to verify are specified through a top-down refinement process. In order to deal with the state explosion problem, we have proposed in previous works to partition the reachability graph, and to perform the verification on each part separately. Moreover, we have defined a class, called Bmod, of dynamic properties that are verifiable by parts, whatever the partition. We decide if a property P belongs to Bmod by looking at the form of the Buchi automaton that accepts the negation of P. However, when a property P belongs to Bmod, the property f => P, where f is a fairness assumption, does not necessarily belong to Bmod. In this paper, we propose to use the refinement process in order to build the parts on which the verification has to be performed. We then show that with such a partition, if a property P is verifiable by parts and if f is the expression of the fairness assumptions on a system, then the property f => P is still verifiable by parts. This approach is illustrated by its application to the chip card protocol T=1 using the B engineering design language

Syntactic Abstraction of B Models to Generate Tests

In a model-based testing approach as well as for the verification of properties, B models provide an interesting solution. However, for industrial applications, the size of their state space often makes them hard to handle. To reduce the amount of states, an abstraction function can be used, often combining state variable elimination and domain abstractions of the remaining variables. This paper complements previous results, based on domain abstraction for test generation, by adding a preliminary syntactic abstraction phase, based on variable elimination. We define a syntactic transformation that suppresses some variables from a B event model, in addition to a method that chooses relevant variables according to a test purpose. We propose two methods to compute an abstraction A of an initial model M. The first one computes A as a simulation of M, and the second one computes A as a bisimulation of M. The abstraction process produces a finite state system. We apply this abstraction computation to a Model Based Testing process.Comment: Tests and Proofs 2010, Malaga : Spain (2010