Symbolic execution is a powerful automated technique for generating test cases. Its goal is to achieve high coverage of software. One major obstacle in adopting the technique in practice is its inability to handle complex mathematical constraints. To address the problem, we have integrated CORAL's heuristic solvers into NASA Ames' Symbolic PathFinder symbolic execution tool. CORAL's solvers have been designed to deal with mathematical constraints and their heuristics have been improved based on examples from the aerospace domain. This integration significantly broadens the application of Symbolic PathFinder at NASA and in industry.
Computational Intelligence (CI) techniques have been used in many different knowledge areas in order to rationalize costs and potentially increase profits. Nevertheless, using this kind of technique is not straight forward, especially in the case of sectors whose practitioners do not have enough programming knowledge. In order to facilitate the teaching, learning, research and usage of CI techniques, we have developed a tool called Athena. In this paper, we report the results of an experiment that we conducted to identify to which extent Athena improves the performance of students during the learning of IC techniques. The results indicate that our tool can be very useful for educators involved in teaching IC.
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