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Your computer is continuously executing programs, but does it reallyunderstand them? Not in any meaningful sense. That burden falls upon humanknowledge workers, who are increasingly asked to write and understand code.They deserve to have intelligent tools that reveal the connections between codeand its subject matter. Towards this prospect, we develop an AI system thatforms semantic representations of computer programs, using techniques fromknowledge representation and program analysis. To create the representations,we introduce an algorithm for enriching dataflow graphs with semanticinformation. The semantic enrichment algorithm is undergirded by a new ontologylanguage for modeling computer programs and a new ontology about data science,written in this language. Throughout the paper, we focus on code written bydata scientists and we locate our work within a larger movement towardscollaborative, open, and reproducible science.

Teaching machines to understand data science code by semantic enrichment of dataflow graphs