---
aliases:
  - '/publication/2026-linterguidedrepairquantumcodesmells/'
title: "Linter-Guided Repair of Quantum Code Smells"
date: 2026-10-02
authors:
  - "Greta Dolcetti"
  - "Giulio Zizzo"
  - "Liubov Nedoshivina"
  - "Juan Cruz-Benito"
  - "Nicolas Dupuis"
abstract: "Quantum programs can suffer from quantum-specific code smells that cannot be captured by classical unit tests. We propose a framework that analyzes the existing programs released in two popular benchmarks using LintQ, a linter for quantum code smells, and attempts to repair them using LLMs while leaving functional correctness untouched. We test the proposed pipeline on 14 different LLMs and 2 popular Qiskit benchmarks and the results show that existing benchmarks are not free from code smells but repairing them using LLMs is feasible without breaking their functional correctness."
publication_types:
  - "paper-conference"
selected: true
publication: "To appear in *SaTQuML: Secure and Trustworthy Quantum Machine Learning Workshop, NeurIPS 2026*"
tags:
  - "Quantum Computing"
  - "Large Language Models"
  - "Code Smells"
  - "Program Repair"
  - "Qiskit"
  - "Quantum Software Engineering"
links:
- type: event
  url: "https://satquml.github.io/"
---