Mar 25, 2024 · A collaborative model that detects and manages code smells by learning from diverse and distributed data sources while respecting privacy.
May 31, 2023 · Abstract:This paper proposes a Federated Learning Code Smell Detection (FedCSD) approach that allows organizations to collaboratively train ...
This paper addresses the previous challenges by proposing a. Federated Learning Code Smell Detection (FedCSD) approach, specifically targeting ''God Class,'' to ...
Sep 4, 2024 · This paper proposes a Federated Learning Code Smell Detection (FedCSD) approach that allows organizations to collaboratively train federated ...
Mar 22, 2024 · The application of federated ML techniques demonstrates promising performance improvements in code-smell detection, benefiting both software ...
The foundational elements include mathematical algorithms equipped with auto-generators for improvement systems, complemented by novel artificial intelligence ...
Jun 1, 2023 · FedCSD: A Federated Learning Based Approach for Code-Smell Detection. View PDF. By Sadi Alawadi, Khalid Alkharabsheh, Fahed Alkhabbas, Victor ...
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This paper proposes a Federated Learning Code Smell Detection (FedCSD) approach that allows organizations to collaboratively train federated ML models while ...
FedCSD: A Federated Learning Based Approach for Code-Smell Detection ... This was followed by experiment 2, which was concerned with cross-evaluation, where each ...
FedCSD: A Federated Learning Based Approach for Code-Smell Detection · Beyond Random Noise: Insights on Anonymization Strategies from a Latent Bandit Study.