Graph4Code: A Machine Interpretable Knowledge Graph for Code
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Knowledge graphs have proven to be extremely useful in powering diverse applications in semantic search, natural language understanding, and even image classification. Graph4Code attempts to build well structured knowledge graphs about program code to similarly revolutionize diverse applications such as code search, code understanding, refactoring, bug detection, and code automation. We build such a graph by applying a set of generic code analysis techniques to Python code on the web. Since use of popular Python modules is ubiquitous in code, calls to functions in Python modules serve as key nodes of the knowledge graph. The edges in the graph are based on 1) function usage in the wild (e.g., which other function tends to call this one, or which function tends to precede this one, as gleaned from program analysis), 2) documentation about the function (e.g., code documentation, usage documentation, or forum discussions such as StackOverflow), and 3) program specific features such as class hierarchies. We use the Whyis knowledge graph management framework to make the graph easily extensible. We apply these techniques to 1.3M Python files drawn from GitHub, and associated documentation on the web for over 400 popular libraries, as well as StackOverflow posts about the same set of libraries. This knowledge graph will be made available soon to the larger community for use.
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