In the above example, as described in detail below, microservice generation system 102 can further facilitate via processor 106 (e.g., a classical processor, a quantum processor, etc.): refining the one or more microservices based on at least one of data dependency of the monolithic application or a static call graph of the monolithic application; generating one or more causal graphs based on the runtime traces of the executed test cases to capture at least one of first order temporal dependencies or high order temporal dependencies of at least one of the monolithic application or the cluster assignments of the classes in the monolithic application; and/or training the model to learn at least one of the cluster assignments or graph embeddings of the classes in the monolithic application using causal sequences of one or more causal graphs generated based on the runtime traces of the executed test cases. In the above example, the executed test cases can comprise business function test cases that provide business functionalities of the monolithic application in the runtime traces.