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Learning the Relation between Code Features and Code Transforms with Structured Prediction

Published in arXiv (Cornell University) • Jul 22, 2019
NobleIDNI3P60W05R41S77
Authors:
Yu, Zhongxing
,
Martinez, Matias
,
Chen, Zimin

Abstract

To effectively guide the exploration of the code transform space for automated code evolution techniques, we present in this paper the first approach for structurally predicting code transforms at the level of AST nodes using conditional random fields (CRFs). Our approach first learns offline a prob...

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