# Simulink Mutation Testing using CodeBERT

arXiv: https://arxiv.org/abs/2501.07553 · HTML: https://mlsanity.com/paper/2501.07553/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Jan 2025.

## Built on by (most cited first, 1 of 1)

- [SimuAgent: An LLM-Based Simulink Modeling Assistant Enhanced with Reinforcement Learning](https://mlsanity.com/paper/2601.05187/) (2026)

## Abstract (arXiv)

We present BERTiMuS, an approach that uses CodeBERT to generate mutants for Simulink models. BERTiMuS converts Simulink models into textual representations, masks tokens from the derived text, and uses CodeBERT to predict the masked tokens. Simulink mutants are obtained by replacing the masked tokens with predictions from CodeBERT. We evaluate BERTiMuS using Simulink models from an industrial benchmark, and compare it with FIM -- a state-of-the-art mutation tool for Simulink. We show that, relying exclusively on CodeBERT, BERTiMuS can generate the block-based Simulink mutation patterns documented in the literature. Further, our results indicate that: (a) BERTiMuS is complementary to FIM, and (b) when one considers a requirements-aware notion of mutation testing, BERTiMuS outperforms FIM.