In another example, as illustrated in FIG. 3 at 302, collection component 202 can employ a data dependency generator such as, for instance, a python-based tool to extract information from source code of a monolithic application that can be used to generate a data dependency graph, where such information can comprise class name, attributes, method names, method arguments, return types, and/or other information. In this example, as illustrated in FIG. 3 at 302, such a data dependency generator can generate a data dependency graph comprising a symbol table (denoted as symTable in FIG. 3) and/or a reference table (denoted as refTable in FIG. 3) that can be formatted as a JSON file.
In another example, as illustrated in FIG. 3 at 302, collection component 202 can employ a static call graph generator such as, for instance, an extraction application that can extract inheritance relationships, data dependency, attributes, method argument, return type, and/or other relationships to generate a static call graph. In this example, as illustrated in FIG. 3 at 302, such a static call graph generator can generate a static call graph formatted as a JSON file. In this example, as illustrated in FIG. 3 at 302, microservice generation system 102 and/or collection component 202 can filter non-application classes out of the static call graph, where such a filtered static call graph can be utilized to refine clusters of classes and/or can be provided to a user interface (UI) as described below.
