Program Equivalence Using Neural Networks
نویسندگان
چکیده
Program equivalence refers to the mapping between equivalent codes written in different languages – including high-level and lowlevel languages. In the present work, we propose a novel approach for correlating program codes of different languages using artificial neural networks and program characteristics derived from control flow graphs and call graphs. Our approach correlates the program codes of different languages by feeding the neural network with logical flow characteristics. Our evaluation using real code examples shows a typical correspondence rate between 62% and 100% with the very low rate of 4% false positives.
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تاریخ انتشار 2010