Decision Diagrams are now widely used in model checking as extremely compact representations of state spaces. Many Decision Diagram categories have been developed over the past twenty years based on the same principles. Each one targets a specific domain with its own characteristics. Moreover, each one provides its own definition. It prevents sharing concepts and techniques between these structures. This paper aims to propose a basis for a common Framework for Decision Diagrams. It should help users of this technology to define new Decision Diagram categories thanks to a simple specification mechanism called Controller. This enables the building of efficient Decision Diagrams dedicated to a given problem.

CLoX is an ongoing attempt to provide a full Emacs Lisp implementation of the Common Lisp Object System, including its underlying meta-object protocol, for XEmacs. This paper describes the early development stages of this project. CLoX currently consists in a port of Closette to Emacs Lisp, with some additional features, most notably, a deeper integration between types and classes and a comprehensive test suite. All these aspects are described in the paper, and we also provide a feature comparison with an alternative project called Eieio.

While software design patterns are a generally useful concept, they are often (and mistakenly) seen as ready-made universal recipes for solving common problems. In a way, the danger is that programmers stop thinking about their actual problem, and start looking for pre-cooked solutions in some design pattern book instead. What people usually forget about design patterns is that the underlying programming language plays a major role in the exact shape such or such pattern will have on the surface. The purpose of this paper is twofold: we show why design pattern expression is intimately linked to the expressiveness of the programming language in use, and we also demonstrate how a blind application of them can in fact lead to very poorly designed code.

The LaTeX world is composed of thousands of software components, most notably classes and styles. Classes and styles are born, evolve or die, interact with each other, compete or cooperate, very much as living organisms do at the cellular level. This paper attempts to draw an extended analogy between the LaTeX biotope and cellular biology. By considering LaTeX documents as living organisms and styles as viruses that infect them, we are able to exhibit a set of behavioral patterns common to both worlds. We analyze infection methods, types and cures, and we show how LaTeX or cellular organisms are able to survive in a world of perpetual war.

In the automata theoretic approach to model checking, checking a state-space $S$ against a linear-time property $\varphi$ can be done in $\mathrm{O}(|S|\times 2^{\mathrm{O}(|\varphi|)})$ time. When model checking under $n$ strong fairness hypotheses expressed as a Generalized Büchi automaton, this complexity becomes $\mathrm{O}(|S|\times 2^{\mathrm{O}(|\varphi|+n)})$.Here we describe an algorithm to check the emptiness of Streett automata, which allows model checking under $n$ strong fairness hypotheses in $\mathrm{O}(|S|\times 2^{\mathrm{O}(|\varphi|)}\times n)$. We focus on transition-based Streett automata, because it allows us to express strong fairness hypotheses by injecting Streett acceptance conditions into the state-space without any blowup.

This paper presents a new speaker verification system architecture based on Joint Factor Analysis (JFA) as feature extractor. In this modeling, the JFA is used to define a new low-dimensional space named the total variability factor space, instead of both channel and speaker variability spaces for the classical JFA. The main contribution in this approach, is the use of the cosine kernel in the new total factor space to design two different systems: the first system is Support Vector Machines based, and the second one uses directly this kernel as a decision score. This last scoring method makes the process faster and less computation complex compared to others classical methods. We tested several intersession compensation methods in total factors, and we found that the combination of Linear Discriminate Analysis and Within Class Covariance Normalization achieved the best performance.