At 308, computer-implemented method 300 can comprise refining (e.g., via microservice generation system 102 and/or refinement component 206) clustering A, B, and/or C as depicted in FIG. 3 based on the data dependency graph generated at 302 as described above and using input from an entity (e.g., a human, a client, a user, a computing device, a software application, an agent, a machine learning (ML) model, an artificial intelligence (AI) model, etc.). For example, as illustrated in FIG. 3 at 308, refinement component 206 and/or the entity defined above can add classes (e.g., to clustering A, B, and/or C) that are missing in the runtime traces, where such classes have data dependency (e.g., data dependency with one or more classes in clustering A, B, and/or C as determined using the data dependency graph). In this example, as illustrated in FIG. 3 at 308, refinement component 206 and/or the entity defined above can further merge clusters (e.g., clustering A, B, and/or C) with cross-cluster data dependency (e.g., cross-cluster data dependency between classes of clustering A, B, and/or C). In this example, as illustrated in FIG. 3 at 308, such refinement operations described above can be implemented to generate natural seam.
