In the example above, c2: u, v belongs to the different clusters but have run time call dependency and ω2(u,v) calculates the normalized call frequency. In the example above, if two classes have frequent function call, then their representation should be close (e.g., inter-cluster call volume).
FIG. 3 illustrates a flow diagram of an example, non-limiting computer-implemented method 300 that can facilitate generation of microservices from a monolithic application based on runtime traces in accordance with one or more embodiments described herein. Repetitive description of like elements and/or processes employed in respective embodiments is omitted for sake of brevity.
At 302, computer-implemented method 300 can comprise collecting (e.g., via microservice generation system 102 and/or collection component 202) input data. For example, as described above with reference to FIG. 2, collection component 202 can collect runtime traces that can be produced by executing (e.g., via processor 106) test cases (e.g., business function test cases) using a monolithic application.
In an example, as illustrated in FIG. 3 at 302, collection component 202 can employ a monitoring application that can generate a runtime log from instrumented source code of a monolithic application. In this example, as illustrated in FIG. 3 at 302, such a monitoring application can generate the runtime log formatted as a log file and/or a text file.
