论文标题
部分可观测时空混沌系统的无模型预测
A Survey on Natural Language Processing for Programming
论文作者
论文摘要
编程的自然语言处理旨在使用NLP技术来协助编程。它在提高生产率方面的有效性越来越普遍。与自然语言不同的是，一种编程语言具有高度结构化和功能性。构建基于结构的表示和面向功能的算法是程序理解和生成的核心。在本文中，我们从基于结构和面向功能的属性的角度进行了系统的审查，涵盖了任务，数据集，评估方法，技术和模型，旨在了解每个组件中两个属性的作用。根据分析，我们说明了未开发的领域，并提出了未来工作的潜在方向。
Natural language processing for programming aims to use NLP techniques to assist programming. It is increasingly prevalent for its effectiveness in improving productivity. Distinct from natural language, a programming language is highly structured and functional. Constructing a structure-based representation and a functionality-oriented algorithm is at the heart of program understanding and generation. In this paper, we conduct a systematic review covering tasks, datasets, evaluation methods, techniques, and models from the perspective of the structure-based and functionality-oriented property, aiming to understand the role of the two properties in each component. Based on the analysis, we illustrate unexplored areas and suggest potential directions for future work.
