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Scientists use computational experiments to study natural phenomena through the lens of software tools and computer programs. A computational experiment consists of a description of how selected datasets are to be processed by a series of software components, in what order, and with what parameter configurations. Designing computational experiments is a challenging task for scientists because of the many interacting constraints to configure the software and to process datasets appropriately. The authors present a novel approach to explore the space of possible experiments efficiently starting from varying degrees of detail and varying amounts of constraints provided by the user.
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