LGTM! Characteristics of Auto-Merged LLM-based Agentic PRs

Ruben Branco*, Paulo Canelas*, Catarina Gamboa*, Alcides Fonseca (* equal contribution)

Mining Challenge at International Conference on Mining Software Repositories (MSR). 2026.  Just Accepted!   🎉

AI tools are generating code faster than humans can properly review it, leading repositories to skip review and auto-merge agentic Pull Requests (PR) directly. In this study, we analyze the characteristics of auto-merged agentic PRs and compare them to human-authored ones. We examine code characteristics, repository ecosystems, and agentic tools across the AIDev dataset, spanning diverse software engineering tasks. We find that auto-merged PRs are smaller and more focused, and that repositories tend to either auto-merge all or none agentic PRs, with more mature repositories favoring the latter. Compared to human-authored auto-merges, maintainers auto-merge agentic PRs more often but show caution toward PRs that delete existing code. Among agents, OpenAI Codex and Claude Code receive the highest auto-merge rates. These findings can inform agentic tool design and repository's auto-merge decisions.

ROSpec: A Domain-Specific Language for ROS-based Robot Software

Paulo Canelas, Bradley Schmerl, Alcides Fonseca, Christopher S. Timperley

Proceedings of the ACM on Programming Languages (PACMPL), OOPSLA. 2025.  

The Usability Argument for ROS-based Robot Architectural Description Languages

Paulo Canelas, Bradley Schmerl, Alcides Fonseca, Christopher S. Timperley

PLATEAU - The Annual Workshop on the Intersection of HCI and PL. 2025.  

Are Large Language Models Memorizing Bug Benchmarks?

Daniel Ramos, Claudia Mamede*, Kush Jain*, Paulo Canelas*, Catarina Gamboa*, Claire Le Goues (* equal contribution)

Large Language Models for Code (LLM4Code) Workshop. 2025.  🏆 Best Paper Award.

Understanding Misconfigurations in ROS: An Empirical Study and Current Approaches

Paulo Canelas, Bradley Schmerl, Alcides Fonseca, Christopher S. Timperley

International Symposium on Software Testing and Analysis (ISSTA). 2024.  

The Robot Operating System (ROS) is a popular framework for building robot software from reusable components, but configuring and connecting these components correctly is challenging. Developers often face issues due to unstated assumptions, leading to misconfigurations that can result in unpredictable and dangerous behavior. To improve the reliability of ROS projects, it is critical to identify the broader set of misconfigurations. To that end, we perform a study on ROS Answers, a Q&A platform, to categorize these misconfigurations and evaluate how well existing detection techniques cover them. We identified 12 high-level categories and 50 sub-categories, with 27 not covered by current techniques.

Is it a Bug? Understanding Physical Unit Mismatches in Robot Software

Paulo Canelas, Trenton Tabor, John-Paul Ore, Alcides Fonseca, Claire Le Goues, Christopher S. Timperley

International Conference in Robotics and Automation (ICRA). 2024.  

Usability-Oriented Design of Liquid Types for Java

Catarina Gamboa, Paulo Canelas, Alcides Fonseca, Christopher S. Timperley

International Conference in Software Engineering (ICSE). 2023.  

Data types as a more ergonomic frontend for Grammar-Guided Genetic Programming

Guilherme Espada, Leon Ingelse, Paulo Canelas, Pedro Barbosa, Alcides Fonseca

International Conference on Generative Programming: Concepts and Experiences. 2022.  

An Experience Report on Challenges in Learning the Robot Operating System

Paulo Canelas, Miguel Tavares, Ricardo Cordeiro, Alcides Fonseca, Christopher S. Timperley

International Workshop on Robotics Software Engineering (RoSE) at the International Conference in Software Engineering (ICSE). 2022.  

Grammatical Evolution Mapping for Semantically-Constrained Genetic Programming

Alcides Fonseca, Paulo Santos, Guilherme Espada, Sara Silva

Genetic Programming Theory and Practice XVIII. 2022.  

Augmenting Search-based Techniques with Static Synthesis-based Input Generation

Paulo Santos, José Campos, Christopher S. Timperley, Alcides Fonseca

International Workshop on Search-Based Software Testing (SBST) at the International Conference in Software Engineering (ICSE). 2021.  

The Usability Argument for Refinement Typed Genetic Programming

Alcides Fonseca, Paulo Santos, Sara Silva

International Conference on Parallel Problem Solving From Nature. 2020.  

Towards the Conceptualization of Refinement Typed Genetic Programming

Paulo Santos

Masters Thesis. Faculty of Sciences of University of Lisbon. 2020.  

Advised by Alcides Fonseca

Refined Typed Genetic Programming as a user interface for Genetic Programming

Paulo Santos, Alcides Fonseca, Sara Silva

Short Paper. Genetic and Evolutionary Computation Conference Companion (GECCO). 2020.