A Preliminary Study on Generating Well-Formed Q# Quantum Programs for Fuzz Testing

Abstract

Generative Sequence-To-Sequence models have been proposed for the task of generating well-formed programs, an important task for fuzz testing tools such as compilers. In this paper, we propose a Sequence-to-Sequence model to generate well-formed Q# Quantum programs. The ratio of syntactically valid programs among 1,000 Q# files generated by our model is 79.6%. In addition, we also contribute with a dataset of 1,723 Q# files taken from publicly available repositories on GitHub, which can be used by the growing community of Quantum Software Engineering.

Publication
In IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW), 2022