1. A method comprising: receiving, via a processor, a model having a set of model elements, a test case that produces an expected response when run on the model, and one or more suspect elements, the model corresponding to an application; calculating, via the processor, a relevance score for each model element of the set of model elements based on the one or more suspect elements; setting, via the processor, a threshold reduction score governing reduction of the model; generating, via the processor, a reduced model by reducing the set of model elements based on the relevance scores and the threshold reduction score; evaluating, via the processor, the reduced model based on the test case; determining, via the processor, that the reduced model does not reproduce an expected behavior when running the test case; rolling back a model element into the reduced model to produce a revised model; responsive to the revised model not reproducing the expected behavior, performing a rollback refinement of the revised model based on a number of model elements rolled back into the reduced model; and generating, via the processor, a modified application by modifying the application associated with the model based on the revised model.