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

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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Results from the Paper


Task Dataset Model Metric Name Metric Value Global Rank Benchmark
Code Translation NLC2CMD Magnum Accuracy 0.532 # 1

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