Vilmar Nepomuceno

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Summary form only given. The extractive and the reactive software product line (SPL) adoption strategies involve, respectively, bootstrapping existing products into a SPL and extending an existing SPL to encompass another product. In both cases, product line refactorings are useful to guide the SPL derivation process by extracting product variations and(More)
Apart from adoption strategies, an existing Software Product Line (SPL) implemented using some variability mechanisms can be migrated to use another variability mechanism. In this paper, we present some migration strategies from one SPL implemented with conditional compilation to one using Aspect-Oriented Programming (AOP). The strategies present a(More)
With the growing academic and industrial interest in Software Product Lines (SPL), one area demanding special attention is tool support development, which is a pre-requisite for widespread SPL practices adoption. In this paper, we present FLiPEx, a code refactoring tool that can be used for extraction of product variations in the context of developing(More)
With the growing academic and industrial interest in Software Product Lines, one area demanding special attention is tool support development, which is a pre-requisite for widespread software product lines practices adoption. In this demo, we present FLiP, a suite of tools consisting of 3 modules: a refactoring tool that implements code transformations for(More)
In Software Product Line (SPL) engineering [1], while focusing on exploiting the commonality within the products, adequate support must be available for customizing the SPL core in order to derive a particular SPL instance. The more diverse the domain, the harder it is to accomplish this task. This, in some cases, may outweigh the cost of developing the SPL(More)
Context: Researchers perform experiments to check their proposals under controlled conditions. Thus, experiments are an important category of empirical studies and are the classical approach for identifying cause-effect relationships. Goal: Quantitatively characterize and analyze the controlled experiments in software engineering published in journal and(More)
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