Advances in Code Summarization

Utkarsh Desai, G. Sridhara, Srikanth G. Tamilselvam
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引用次数: 2

Abstract

Several studies have suggested that comments describing source code can help mitigate the burden of program understanding. However, software systems usually lack adequate comments and even when present, the comments may be obsolete or unhelpful. Researchers have addressed this issue by automatically generating comments from source code, a task referred to as Code Summarization. In this technical presentation, we take a deeper look at some of the significant, recent works in the area of code summarization and how each of them attempts to take a new perspective of this task including methods leveraging RNNs, Transformers, Graph neural networks and Reinforcement learning.
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代码摘要的进展
一些研究表明,描述源代码的注释可以帮助减轻程序理解的负担。然而,软件系统通常缺乏足够的注释,即使有,注释也可能是过时的或无用的。研究人员通过从源代码自动生成注释来解决这个问题,这个任务被称为代码汇总。在这个技术演示中,我们将深入研究一些重要的,最近在代码总结领域的工作,以及他们如何尝试从一个新的角度来看待这个任务,包括利用rnn,变形,图神经网络和强化学习的方法。
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