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Not all bugs lead to program crashes, and not always is there a formal specification to check the correctness of a software test's outcome. A common scenario in software testing is therefore that test data are generated, and a tester manually adds test oracles. As this is a difficult task, it is important to produce small yet representative test sets, and this representativeness is typically measured...
Symbolic program manipulation plays a key role in program comprehension and verification. Logic formulae are used to represent the program's state and transformation rules describe the effect of statement executions on the program's state. A well-known problem arises in the case of loops, since the number of iterations is generally unknown. The effect of a loop is therefore abstracted into a loop...
Generally, impulse noise filtering schemes consider all pixels within a large neighborhood. However, the estimate from all pixels within the neighborhood may not be accurate. Moreover, large window may remove edges and fine details. In contrast to this approach, we propose iterative impulse noise removal scheme that emphasizes on few noise-free pixels within a small neighborhood. This iterative process...
Reinforcement Programming (RP) is a new approach to automatically generating algorithms, that uses reinforcement learning techniques. This paper describes the RP approach and gives results of experiments using RP to generate a generalized, in-place, iterative sort algorithm. The RP approach improves on earlier results that that use genetic programming (GP). The resulting algorithm is a novel algorithm...
Many games have a collection of boards with the difficulty of an instance of the game determined by the starting configuration of the board. Correctly rating the difficulty of the boards is somewhat haphazard and required either a remarkable level of understanding of the game or a good deal of play-testing. In this study we explore evolutionary algorithms as a tool to automatically grade the difficulty...
Genetic optimization has been used in the last years for solving different electromagnetic problems. However, this technique assumes, and binary-codes, a fixed structure from the beginning, so it has a limited use in antenna design. On the other hand, Genetic Programming is able to determine the antenna shape as an outcome of the procedure. This work describes how to use genetic programming to design...
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