Evaluating Variability Modeling Techniques for Dynamic Software Product Lines: A Controlled Experiment

Dynamic Software Product Lines (DSPL) is a promising approach to enable variability management at run-time. As a particularly novel approach, variability management at runtime demands proper guidance for software engineers. Although there is a number of variability modeling techniques, understand whether they fulfill important requirements to deal with the DSPL challenges is necessary. In this work, we analyzed two variability modeling techniques with regard to their effectiveness and efficiency based on a controlled experiment conducted with 10 students. Data from performed tasks and background and feedback questionnaires were gathered and analyzed. The results showed Context-aware Feature Model technique more effective than Tropos Goal Model with Context technique considering precision. Nevertheless, both techniques were effective considering recall.