# How to Design a Program Repair Bot? Insights from the Repairnator Project

arXiv: https://arxiv.org/abs/1811.09852 · HTML: https://mlsanity.com/paper/1811.09852/

## Key facts

- Cited by 11 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Nov 2018.

## Built on by (most cited first, 11 of 11)

- [RAP-Gen: Retrieval-Augmented Patch Generation with CodeT5 for Automatic Program Repair](https://mlsanity.com/paper/2309.06057/) (2023)
- [Towards Human-Bot Collaborative Software Architecting with ChatGPT](https://mlsanity.com/paper/2302.14600/) (2023)
- [AIDev: Studying AI Coding Agents on GitHub](https://mlsanity.com/paper/2602.09185/) (2026)
- [SGAgent: Suggestion-Guided LLM-Based Multi-Agent Framework for Repository-Level Software Repair](https://mlsanity.com/paper/2602.23647/) (2026)
- [Motivations, Challenges, Best Practices, and Benefits for Bots and Conversational Agents in Software Engineering: A Multivocal Literature Review](https://mlsanity.com/paper/2409.11864/) (2024)
- [C4Q: A Chatbot for Quantum](https://mlsanity.com/paper/2402.01738/) (2024)
- [Accelerating Automatic Program Repair with Dual Retrieval-Augmented Fine-Tuning and Patch Generation on Large Language Models](https://mlsanity.com/paper/2507.10103/) (2025)
- [NARRepair: Non-Autoregressive Code Generation Model for Automatic Program Repair](https://mlsanity.com/paper/2406.16526/) (2024)
- [Architecture for a Trustworthy Quantum Chatbot](https://mlsanity.com/paper/2503.04875/) (2025)
- [From Assistance to Agency: Rethinking Autonomy and Control in CI/CD Pipelines](https://mlsanity.com/paper/2605.07062/) (2026)
- [Co-Modifying Application Code and Deployment Infrastructure: A Causal Study of AI Agent Pull Requests](https://mlsanity.com/paper/2610.12849/) (2026)

## Abstract (arXiv)

Program repair research has made tremendous progress over the last few years, and software development bots are now being invented to help developers gain productivity. In this paper, we investigate the concept of a " program repair bot " and present Repairnator. The Repairnator bot is an autonomous agent that constantly monitors test failures, reproduces bugs, and runs program repair tools against each reproduced bug. If a patch is found, Repairnator bot reports it to the developers. At the time of writing, Repairnator uses three different program repair systems and has been operating since February 2017. In total, it has studied 11 317 test failures over 1 609 open-source software projects hosted on GitHub, and has generated patches for 17 different bugs. Over months, we hit a number of hard technical challenges and had to make various design and engineering decisions. This gives us a unique experience in this area. In this paper, we reflect upon Repairnator in order to share this knowledge with the automatic program repair community.