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The automated analysis of feature models is recognized as one of the key challenges for automated software development in the context of Software Product Lines (SPL). However, after years of research only a few ad-hoc proposals have been presented in such area and the tool support demanded by the SPL community is still insufficient. In previous work we(More)
Context. A Feature Model (FM) represents the valid combinations of features in a domain. The automated extraction of information from FMs is a complex task that involves numerous analysis operations, techniques and tools. Current testing methods in this context are manual and rely on the ability of the tester to decide whether the output of an analysis is(More)
Feature Models (FMs) are a key artifact for variability and common-ality management in Software Product Lines (SPLs). In this context, the merging of FMs is being recognized as an important operation to support the adoption and evolution of SPLs. However, providing automated support for merging FMs still remains an open challenge. In this paper, we propose(More)
The automated analysis of feature models is a flourishing research topic that has called the attention of both researchers and practitioners during the last two decades. During this time, the number of tools and techniques enabling the analysis of feature models has increased and also their complexity. In this scenario, the lack of specific testing(More)
A Feature Model (FM) is a compact representation of all the products of a software product line. The automated extraction of information from FMs is a thriving research topic involving a number of analysis operations, algorithms, paradigms and tools. Implementing these operations is far from trivial and easily leads to errors and defects in analysis(More)
Variability testing techniques search for effective and manageable test suites that lead to the rapid detection of faults in systems with high variability. Evaluating the effectiveness of these techniques in realistic settings is a must, but challenging due to the lack of variability-intensive systems with available code, automated tests and fault reports.(More)