Papers › A Transformer-based Approach for Translating Natural Language to Bash Commands

A Transformer-based Approach for Translating Natural Language to Bash Commands

14 Dec 202120th IEEE International Conference on Machine Learning and Applications - ICMLA 2021 12archive 2025-07-28

Quchen Fu, Zhongwei Teng, Jules White, Douglas C. Schmidt

This paper explores the translation of natural language into Bash Commands, which developers commonly use to accomplish command-line tasks in a terminal. In our approach a terminal takes a command as a sentence in plain English and translates it into the corresponding string of Bash Commands. The paper analyzes the performance of several architectures on this translation problem using the data from the NLC2CMD competition at the NeurIPS 2020 conference. The approach presented in this paper is the best performing architecture on this problem to date and improves the current state-of-the-art accuracy on this translation task from 13.8% to 53.2%.

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