Abstract
This paper presents a comparative analysis of Free/Libre Open Source Software (FLOSS) Learning Management System (LMS). Following a selection process we analyze the functionalities and characteristics of 8 tools commonly used in formal and informal education. More specifically we focus on the availability of different tools concerning communication and assistance, such as, forum, email, calendar, portfolios, etc. Our analysis showed that despite their similarities, the appropriateness of different FLOSS LMSs can be greatly affected by the specific needs of students, instructors and institutions. © Springer-Verlag Berlin Heidelberg 2014.

Abstract
In this paper we describe an approach to classifying heart sounds (classes Normal, Murmur and Extra-systole) that is based on the discretization of sound signals using the SAX (Symbolic Aggregate Approximation) representation. The ability of automatically classifying heart sounds or at least support human decision in this task is socially relevant to spread the reach of medical care using simple mobile devices or digital stethoscopes. In our approach, sounds are first pre-processed using signal processing techniques (decimate, low-pass filter, normalize, Shannon envelope). Then the pre-processed symbols are transformed into sequences of discrete SAX symbols. These sequences are subject to a process of motif discovery. Frequent sequences of symbols (motifs) are adopted as features. Each sound is then characterized by the frequent motifs that occur in it and their respective frequency. This is similar to the term frequency (TF) model used in text mining. In this paper we compare the TF model with the application of the TFIDF (Term frequency - Inverse Document Frequency) and the use of bi-grams (frequent size two sequences of motifs). Results show the ability of the motifs based TF approach to separate classes and the relative value of the TFIDF and the bi-grams variants. The separation of the Extra-systole class is overly difficult and much better results are obtained for separating the Murmur class. Empirical validation is conducted using real data collected in noisy environments. We have also assessed the cost-reduction potential of the proposed methods by considering a fixed cost model and using a cost sensitive meta algorithm.

Abstract
Bidirectional transformations have potential applications in a vast number of computer science domains. Spreadsheets, on the other hand, are widely used for developing business applications, but their formulas are unidirectional, in the sense that their result can not be edited and propagated back to their input cells. In this paper, we interpret such formulas as a well-known class of bidirectional transformations that go by the name of lenses. Being aimed at users that are not proficient with programming languages, we devote particular attention to the seamless embedding of the proposed bidirectional mechanism with the typical workflow of spreadsheet environments, allowing users to have a fine control and understanding of the behavior of the derived backward transformations.

Abstract
The Query/View/Transformation Relations (QVT-R) standard for bidirectional model transformation is notorious for its underspecified semantics. When restricted to transformations between pairs of models, most of the ambiguities and omissions have been addressed in recent work. Nevertheless, the application of the QVT-R language is not restricted to that scenario, and similar issues remain unexplored for the multidirectional case (maintaining consistency between more than two models), that has been overlooked so far. In this paper we first discuss ambiguities and omissions in the QVT-R standard concerning the mutidirectional transformation scenario, and then propose a simple extension and formalization of the checking and enforcement semantics that clarifies some of them. We also discuss how such proposal could be implemented in our Echo bidirectional model transformation tool. Ours is just a small step towards making QVT-R a viable language for bidirectional transformation in realistic applications, and a considerable amount of basic research is still needed to fully accomplish that goal.

Abstract
Model finders are becoming useful in many software engineering problems. Kodkod [19] is one of the most popular, due to its support for relational logic (a combination of first order logic with relational algebra operators and transitive closure), allowing a simpler specification of constraints, and support for partial instances, allowing the specification of a priori (exact, but potentially partial) knowledge about a problem's solution. However, in some software engineering problems, such as model repair or bidirectional model transformation, knowledge about the solution is not exact, but instead there is a known target that the solution should approximate. In this paper we extend Kodkod's partial instances to allow the specification of such targets, and show how its model finding procedure can be adapted to support them (using both PMax-SAT solvers or SAT solvers with cardinality constraints). Two case studies are also presented, including a careful performance evaluation to assess the effectiveness of the proposed extension. © 2014 Springer-Verlag.

Abstract
Bidirectional transformation (BX) is a very active area of research interest. There is not only a growing body of theory, but also a rich set of tools supporting BX. The problem now arises that there is no commonly agreed-upon suite of tests or benchmarks that shows either the conformance of tools to theory, or the performance of tools in particular BX scenarios. This paper sets out to improve the state of affairs in this respect, by proposing a template and a set of required criteria for benchmark descriptions, as well as guidelines for the artifacts that should be provided for each included test. As a proof of concept, the paper additionally provides a detailed description of one concrete benchmark.