A Systematic Literature Review on Federated Machine Learning: From A Software Engineering Perspective

Understand

Federated learning is an emerging machine learning paradigm where clients train models locally and formulate a global model based on the local model updates.

• To identify the state-of-the-art in federated learning and explore how to develop federated learning systems, we perform a systematic literature review from a software engineering perspective, based on 231 primary studies.
• Our data synthesis covers the lifecycle of federated learning system development that includes background understanding, requirement analysis, architecture design, implementation, and evaluation.
• We highlight and summarise the findings from the results, and identify future trends to encourage researchers to advance their current work.