用ChatGPT自动将Python联邦学习代码转为CSP模型，提升验证效率
Translating Federated Learning Algorithms in Python into CSP Processes Using ChatGPT
- 利用ChatGPT将Python联邦学习算法自动翻译为CSP过程
- 成功验证了中心化与去中心化算法的正确性，翻译成功率100%
- 适合想快速形式化验证联邦学习系统的开发者
Python联邦学习测试平台是一个简洁易用的FL框架，适合非专业编程人员使用，也便于大语言模型处理。此前研究中，该框架提供的通用联邦学习算法需手动转换为CSP过程，并通过模型检测器PAT验证其安全性和活性性质。本文提出一种简化翻译流程，利用ChatGPT自动化实现从Python联邦学习算法到对应CSP过程的转换，并基于ChatGPT反馈评估上下文最小化程度。实验验证表明，该方法成功完成了对通用中心化与去中心化联邦学习算法的翻译，且结果经PAT模型检测器确认无误。
原文摘要 · Abstract (English)
The Python Testbed for Federated Learning Algorithms is a simple Python FL framework that is easy to use by ML&AI developers who do not need to be professional programmers and is also amenable to LLMs. In the previous research, generic federated learning algorithms provided by this framework were manually translated into the CSP processes and algorithms' safety and liveness properties were automatically verified by the model checker PAT. In this paper, a simple translation process is introduced wherein the ChatGPT is used to automate the translation of the mentioned federated learning algorithms in Python into the corresponding CSP processes. Within the process, the minimality of the used context is estimated based on the feedback from ChatGPT. The proposed translation process was experimentally validated by successful translation (verified by the model checker PAT) of both generic centralized and decentralized federated learning algorithms.
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