EAGER: Exploiting the Naturalness of Software

University Of California-Davis, Davis CA

Investigators

Abstract

A study of software code has revealed a surprising result: that software code may be just as (if not more) "natural" as natural language itself (e.g., English) in that code is highly predictable and repetitive; statistical natural language techniques may be applied quite competently for some software engineering tasks. For example, N-grams may be quite effective at suggestion and completion tasks in code. The evidence supports further exploration of the applicability of statistical NLP techniques and tools to software development activities and processes. The project explores the feasibility of establishing a scientific basis and tools for a variety of code-level software engineering functions -- including natural language summarization, code retrieval, software question answering, automated code completion, and assistive tools for disabled developers to support software engineering, forming not only a new and important domain for further research in NLP, but also a totally new approach to software development.