Translating Federated Learning Algorithms in Python into CSP Processes Using ChatGPT
Fuente:
arXiv
Enregistré dans:
| Auteurs principaux: | , , , |
|---|---|
| Format: | Preprint |
| Publié: |
2025
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
| _version_ | 1866918136278679552 |
|---|---|
| author | Popovic, Miroslav Popovic, Marko Djukic, Miodrag Basicevic, Ilija |
| author_facet | Popovic, Miroslav Popovic, Marko Djukic, Miodrag Basicevic, Ilija |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_07173 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Translating Federated Learning Algorithms in Python into CSP Processes Using ChatGPT Popovic, Miroslav Popovic, Marko Djukic, Miodrag Basicevic, Ilija Artificial Intelligence 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. |
| title | Translating Federated Learning Algorithms in Python into CSP Processes Using ChatGPT |
| topic | Artificial Intelligence |
| url | https://arxiv.org/abs/2506.07173 |