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Abstract. In this this paper, we discuss the interest and the need to evaluate the difficulty of single player video games. We first show the importance of difficulty, drawing from semiotics to explain the link between tension-resolution cycles, and challenge with the player's enjoyment. Then, we report related work on automatic gameplay analysis. We show through a simple experimentation that automatic video game analysis is both practicable and can lead to interesting results. We argue that automatic analysis tools are limited if they do not consider difficulty from the player point of view. The last section provides a player and Game Design oriented definition of the challenge and difficulty notions in games. As a consequence we derive the property that must fulfill a measurable definition of difficulty.

Recent research and bug reports have shown that work conservation, the property that a core is idle only if no other core is overloaded, is not guaranteed by Linux's CFS or FreeBSD's ULE multicore schedulers. Indeed, multicore schedulers are challenging to specify and verify: they must operate under stringent performance requirements, while handling very large numbers of concurrent operations on threads. As a consequence, the verification of correctness properties of schedulers has not yet been considered. In this paper, we propose an approach, based on a domainspecific language and theorem provers, for developing schedulers with provable properties. We introduce the notion of concurrent work conservation (CWC), a relaxed definition of work conservation that can be achieved in a concurrent system where threads can be created, unblocked and blocked concurrently with other scheduling events. We implement several scheduling policies, inspired by CFS and ULE. We show that our schedulers obtain the same level of performance as production schedulers, while concurrent work conservation is satisfied.

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Les applications auto-adaptables modifient leur comportement de façon dynamique et autonome par le biais d'opérations d'introspection, de recomposition, d'ajout et suppression de composants, dans le but de s'adapter aux changements pouvant survenir dans leur contexte d'exécution. Un des moyens de favoriser leur robustesse est de disposer d'un support formel permettant de modéliser ces applications, de spécifier les programmes d'adaptation, d'y exprimer des propriétés et de les vérifier. Nous proposons un cadre formel de spécification et de raisonnement sur des programmes avec reconfiguration dynamique inspiré du modèle à composants Fractal. Le cadre proposé, nommé FracL, est fondé sur une description axiomatique des primitives de Fractal en logique de premier ordre, et permet la spécification et la preuve des propriétés autant fonctionnelles que de contrôle dans ces systèmes. Notre modèle a été traduit dans l'atelier de spécification et de preuve Focal, ce qui permet à la fois d'en assurer la cohérence et de fournir un cadre outillé pour raisonner sur des applications concrètes. ABSTRACT. Self-adapting software adapts its behavior in an autonomic way, by dynamically adding, suppressing and recomposing components, and by the use of computational reflection. One way to enforce software robustness while adding adaptative behavior is disposing of a formal support allowing these programs to be modeled, and their properties specified and verified. We propose FracL, a formal framework for specifying and reasoning about dynamic reconfiguration programs being written in a Fractal-like programming style. FracL is founded on first order logic, and allows the specification and proof of properties concerning either functional concerns or control concerns. Its encoding using the Focal proof framework, enabled us to prove FracL coherence and to obtain a mechanized framework for reasoning on concrete architectures.