[Artifact Respository] Quantum Program Linting with LLMs: Emerging Results from a Comparative Study

This page contains the artifacts of our paper, entitled "Quantum Program Linting with LLMs: Emerging Results from a Comparative Study". In particular, this pape provides the experiment package to increase the reproducibility of our experiments.<b>Datasets</b>In our experiments, we used real-world Qiskit source code files and the annotated dataset from the LintQ repository, which is available at https://github.com/sola-st/LintQ.<b>Files</b>LintQ-LLM.py: A Python script that generates prompts and executes them.results.txt: The results produced by LintQ-LLM in the experiments presented in our paper.<b>LintQ-LLM Usage Instruction</b>Update line 18 in LintQ-LLM.py with a valid OpenAI API key.Create a ./files_selected directory and place Qiskit source code files in it.Run "python LintQ-LLM.py", which will output results.txt<b>License</b>This software is licensed under the Apache License 2.0, which permits use, modification, and distribution under open source terms. However, please be aware of the following: Access to and use of the OpenAI API is governed by OpenAI’s Terms of Use and Usage Policies, which include but are not limited to:Requirements for account registration and a valid API key.Restrictions on prohibited use cases (e.g., illegal, harmful, or misleading content generation).Usage limits, pricing, and billing terms defined by OpenAI.By running this software with OpenAI API integration, you (the user) are responsible for complying with OpenAI’s terms and policies. This project does not provide, include, or distribute access to OpenAI’s services, nor does it accept liability for how those services are used.

本页面包含我们题为《基于大语言模型（Large Language Model）的量子程序静态代码检查：一项对比研究的初步成果》的论文配套资料。具体而言，本文提供了实验包以提升本实验的可复现性。
<b>数据集</b> 本实验所用数据包括真实场景下的Qiskit源代码文件，以及来自LintQ仓库的标注数据集，该仓库的公开地址为https://github.com/sola-st/LintQ。
<b>文件说明</b> LintQ-LLM.py：用于生成提示词（Prompt）并执行提示词的Python脚本。results.txt：本论文实验中，LintQ-LLM生成的实验结果文件。
<b>LintQ-LLM使用指南</b> 1. 将LintQ-LLM.py文件的第18行替换为有效的OpenAI API密钥。2. 创建名为./files_selected的目录，并将Qiskit源代码文件放入该目录中。3. 执行命令"python LintQ-LLM.py"，程序将生成并输出results.txt文件。
<b>许可协议</b> 本软件采用Apache许可证2.0（Apache License 2.0）进行授权，允许在开源条款范围内进行使用、修改与分发。但请注意以下事项：访问及使用OpenAI API需遵守OpenAI的服务条款与使用政策，其中包括但不限于：账户注册与有效API密钥的相关要求、禁止使用场景的限制（例如生成非法、有害或误导性内容）、OpenAI规定的使用限额、定价与计费条款。通过集成OpenAI API运行本软件，您（用户）需自行遵守OpenAI的相关条款与政策。本项目未提供、包含或分发OpenAI服务的访问权限，亦不对该服务的使用方式承担任何责任。