Toward Code Generation: A Survey and Lessons from Semantic Parsing

Autor:	Lee, Celine, Gottschlich, Justin, Roth, Dan
Rok vydání:	2021
Předmět:	Computer Science - Software Engineering Computer Science - Computation and Language Computer Science - Machine Learning Computer Science - Programming Languages
Druh dokumentu:	Working Paper
Popis:	With the growth of natural language processing techniques and demand for improved software engineering efficiency, there is an emerging interest in translating intention from human languages to programming languages. In this survey paper, we attempt to provide an overview of the growing body of research in this space. We begin by reviewing natural language semantic parsing techniques and draw parallels with program synthesis efforts. We then consider semantic parsing works from an evolutionary perspective, with specific analyses on neuro-symbolic methods, architecture, and supervision. We then analyze advancements in frameworks for semantic parsing for code generation. In closing, we present what we believe are some of the emerging open challenges in this domain. Comment: 12 pages, 6 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2105.03317 Zobrazit plný text záznamu View this record from Arxiv