Big Transformers for Code Generation

G. A. Arutyunov, S. M. Avdoshin

National Research University Higher School of Economics

Abstract: IT industry has been thriving over the past decades. Numerous new programming languages have emerged, new architectural patterns and software development techniques. Tools involved in the process ought to evolve as well. One of the key principles of new generation of instruments for software development would be the ability of the tools to learn using neural networks. First of all, it is necessary for the tools to learn how to write code. In this work we study the ability of Transformers to generate competition level code. The main goal is to discover whether open-source Big Transformers are “naturally” good coders.

Keywords: neural networks, code generation, Transformers, GPT

Language: English

DOI: 10.15514/ISPRAS-2022-34(4)-6