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One of the main challenges faced by today’s developers is keeping up with the staggering amount of source code that needs to be read and understood. In order to help developers with this problem and reduce the costs associated with it, one solution is to use simple textual descriptions of source code entities that developers can grasp easily, while capturing the code semantics precisely. We propose an approach to automatically determine such descriptions, based on automated text summarization technology and structural information.
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