2017-07-212017-07-212016Galindo Duarte, J.Á., Turner, H., Benavides Cuevas, D.F. y White, J. (2016). Testing variability-intensive systems using automated analysis: an application to Android. Software Quality Journal, 24 (2), 365-405.0963-9314http://hdl.handle.net/11441/62860Software product lines are used to develop a set of software products that, while being different, share a common set of features. Feature models are used as a compact representation of all the products (e.g., possible configurations) of the product line. The number of products that a feature model encodes may grow exponentially with the number of features. This increases the cost of testing the products within a product line. Some proposals deal with this problem by reducing the testing space using different techniques. However, a daunting challenge is to explore how the cost and value of test cases can be modeled and optimized in order to have lower-cost testing processes. In this paper, we present TESting vAriAbiLity Intensive Systems (TESALIA), an approach that uses automated analysis of feature models to optimize the testing of variability-intensive systems. We model test value and cost as feature attributes, and then we use a constraint satisfaction solver to prune, prioritize and package product line tests complementing prior work in the software product line testing literature. A prototype implementation of TESALIA is used for validation in an Android example showing the benefits of maximizing the mobile market share (the value function) while meeting a budgetary constraint.application/pdfengAttribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/TestingSoftware Product Linesautomated analysisFeature modelsAndroidinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/openAccess10.1007/s11219-014-9258-y