FeatureIDE is an open-source framework for feature-oriented software development (FOSD) based on Eclipse. FOSD is a paradigm for construction, customization, and synthesis of software systems. Code artifacts are mapped to features and a customized software system can be generated given a selection of features. The set of software systems that can be generated is called a software product line (SPL). FeatureIDE supports several FOSD implementation techniques such as feature-oriented programming, aspect-oriented programming, delta-oriented programming, and preprocessors. All phases of FOSD are supported in FeatureIDE, namely domain analysis, requirements analysis, domain implementation, and software generation.

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Exhaustively testing every product of a software product line (SPL) is a di cult task due to the combinatorial explosion of the number of products. Combinatorial interaction testing is a technique to reduce the number of products under test. However, it is typically up-to the tester in which order these products are tested. We propose a similarity-based prioritization to be applied on these products before they are generated. The proposed approach does not guarantee to find more errors than sampling approaches, but it aims at increasing interaction coverage of an SPL under test as fast as possible over time. This is especially beneficial since usually the time budget for testing is limited. We implemented similarity-based prioritization in FeatureIDE and evaluated it by comparing its outcome to the default outcome of three sampling algorithms as well as to random orders. The experiment results indicate that the order with similarity-based prioritization is better than random orders and often better than the default order of existing sampling algorithms.

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