TripleBound: Triplet-Guided Heterogeneous Graph Learning for Microservice Decomposition
TripleBound is proposed, a hybrid framework for automated monolith-to-microservices decomposition that augments a heterogeneous graph neural network with weakly supervised triplet constraints derived from parser-inferred service groups based on package structure, naming conventions, and code location.
M. Weerasinghe, Himindu Kularathne, Methmini Madhushika et al.
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