Jaime Font

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Software Product Lines (SPLs) can be established from a set of similar models. Establishing the Product Line by mechanically finding model differences may not be the best approach. The identified model fragments may not be seen as recognizable units by the application engineers. We propose to identify model patterns by human-in-the-loop and conceptualize(More)
The aim of domain engineering process is to define and realise the commonality and variability of a Software Product Line. In the context of a family of models, spotting the commonalities and differences may become cumbersome and error prone as the number of models and its complexity increases. This work presents an approach to automate the formalization of(More)
Common Variability Language (CVL) is a recent proposal for OMG's upcoming Variability Modeling standard. CVL models variability in terms of Model Fragments. Usability is a widely-recognized quality criterion essential to warranty the successful use of tools that put these ideas in practice. Facing the need of evaluating usability of CVL modeling tools, this(More)
Every day we receive lots of information through our senses that is lost forever, because it lacked the strength or the repetition needed to generate a lasting memory. Combining the emerging Internet of Things and lifelogging sensors, we believe it is possible to build up a Digital Memory (Dig-Mem) in order to complement the fallible memory of people. This(More)
Dynamic Software Product Lines (DSPLs) offer a strategy to deal with software changes that need to be handled at run-time. In response to context changes, a DSPL capitalize on knowledge about the architecture variability of the software system to shift between configurations. Similar to any other kind of software, a DSPL needs to evolve over time but(More)
—Current research efforts are focused on taking advantage of the models at run-time for run-time decision-making related to run-time system concerns associated with autonomic and adaptive systems. In addition, all systems need maintenance over time as new requirements emerge or when bug-fixing becomes necessary. Models at run-time can provide an execution(More)
In this work we propose a feature location approach that targets models as the feature realization artifacts. The approach combines Genetic Algorithms and Information Retrieval techniques. Given a model and a feature description, model fragments extracted from the model are evolved using genetic operations. Then, Formal Concept Analysis is used to cluster(More)