Mo2oM assigns classes to overlapping microservices using UniXcoder embeddings and NOCD soft clustering, claiming large gains in modularity metrics over hard-clustering baselines on four monoliths.
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Extracting Overlapping Microservices from Monolithic Code via Deep Semantic Embeddings and Graph Neural Network-Based Soft Clustering
Mo2oM assigns classes to overlapping microservices using UniXcoder embeddings and NOCD soft clustering, claiming large gains in modularity metrics over hard-clustering baselines on four monoliths.