一种结构信息增强的代码修改自动转换方法

在开发过程中,开发人员在进行缺陷修复、版本更新时,常常需要修改多处相似的代码.如何进行自动代码修改已成为软件工程领域的热点研究问题.一种行之有效的方式是:给定一组代码修改示例,通过抽取其中的代码修改模式,辅助相似代码进行自动转换.在现有工作中,基于深度学习的方法取得了一定进展,但在捕获代码间的长程信息依赖关系时,效果不...

Structurally-enhanced Approach for Automatic Code Change Transformation

In software development, developers often need to change or update lots of similar codes. How to perform code transformation automatically has become a research hotspot in software engineering. An effective way is:extracting the change pattern from a set of similar code changes and apply it to automatic code change transformation. In the related work, deep-learning-based approaches have achived much progress, but they suffer from the problem of significant long-dependency among code. To address this challenge, we propose an automatic code change transformation method, ExpTrans, enhanced by code structure information. Based on graph-based representations of code changes, we enhance ExpTrans with structural information of code. ExpTrans labels the dependency among variables in code parsing, adopts the graph-convolution network and Transformer structure, so as to capture the long-dependency among code. To evaluate ExpTrans''s effectiveness, we compare it with existing learning-based approaches first, the results show that ExpTrans gains11.8%~30.8% precision incresment. Then we compare ExpTrans with some rule-based approaches, the results show that ExpTrans significantly improves the correct rate of the modified instances.