Abstract
The ever increasing number of platforms and languages available to software developers means that the software industry is reaching high levels of complexity. Model Driven Architecture (MDA) presents a solution to the problem of improving software development processes in this changing and complex environment. MDA driven development is based on models definition and transformation. Design patterns provide a means to reuse proven solutions during development. Identifying design patterns in the models of a MDA approach helps their understanding, but also the identification of good practices during analysis. However, when analyzing or maintaining code that has not been developed according to MDA principles, or that has been changed independently from the models, the need arises to reverse engineer the models from the code prior to patterns' identification. The approach presented herein consists in transforming source code into models, and infer design patterns from these models. Erich Gamma's cataloged patterns provide us a starting point for the pattern inference process. MapIt, the tool which implements these functionalities is described.

Abstract
Problem statements often resort to superlatives such as in e.g. " ... the smallest such number", " ... the best approximation", " ... the longest such list" which lead to specifications made of two parts: one defining a broad class of solutions (the easy part) and the other requesting one particular such solution, optimal in some sense (the hard part). This article introduces a binary relational combinator which mirrors this linguistic structure and exploits its potential for calculating programs by optimization. This applies in particular to specifications written in the form of Galois connections, in which one of the adjoints delivers the optimal solution. The framework encompasses re-factoring of results previously developed by Bird and de Moor for greedy and dynamic programming, in a way which makes them less technically involved and therefore easier to understand and play with.

Abstract
Music sources are most commontly shared in music scores scanned or printed on paper sheets. These artifacts are rich in information, but since they are images it is hard to re-use and share their content in todays' digital world. There are modern languages that can be used to transcribe music sheets, this is still a time consuming task, because of the complexity involved in the process and the typical huge size of the original documents. WIKI::SCORE is a collaborative environment where several people work together to transcribe music sheets to a shared medium, using the notation. This eases the process of transcribing huge documents, and stores the document in a well known notation, that can be used later on to publish the whole content in several formats, such as a PDF document, images or audio files for example.

Abstract
The algebra of programming (AoP) is a discipline for programming from specifications using relation algebra. Specification vagueness and nondeterminism are captured by relations. (Final) implementations are functions. Probabilistic functions are half way between relations and functions: they express the propensity, or likelihood of ambiguous, multiple outputs. This paper puts forward a basis for a linear algebra of programming (LAoP) extending standard AoP towards probabilistic functions. Because of the quantitative essence of these functions, the allegory of binary relations which supports the AoP has to be extended. We show that, if one restricts to discrete probability spaces, categories of matrices provide adequate support for the extension, while preserving the pointfree reasoning style typical of the AoP.

Abstract
There is a need for a language able to reconcile the recent upsurge of interest in quantitative methods in the software sciences with logic and set theory that have been used for so many years in capturing the qualitative aspects of the same body of knowledge. Such a lingua franca should be typed, polymorphic, diagrammatic, calculational and easy to blend with traditional notation. This paper puts forward typed linear algebra (LA) as a candidate notation for such a role. Typed LA emerges from regarding matrices as morphisms of suitable categories whereby traditional linear algebra is equipped with a type system. In this paper we show typed LA at work in describing weighted (probabilistic) automata. Some attention is paid to the interface between the index-free language of matrix combinators and the corresponding index-wise notation, so as to blend with traditional set theoretic notation. © 2012 Springer-Verlag.

Abstract
In a recent article [1], David Parnas questions the traditional use of formal methods in software development, which he considers an underdeveloped body of knowledge and therefore of little hope for the software industry. He confronts the reader with the following statement, at some stage: "We must learn to use mathematics in software development, but we need to question, and be prepared to discard, most of the methods that we have been discussing and promoting for all these years." At the core of Parnas objections we find the contrast between the current ad-hoc (re)invention of mathematical concepts which are cumbersome and a burden to use and elegant (and therefore useful) concepts which are neglected, often for cultural or (lack of) background reasons. © 2012 Springer-Verlag.