GRAPHIA uses graph neural network link prediction on whole-program graphs to rank candidate callees for unresolved JavaScript call sites, placing the correct one in the top 5 for 72% of cases.
Learning to Represent Edits
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abstract
We introduce the problem of learning distributed representations of edits. By combining a "neural editor" with an "edit encoder", our models learn to represent the salient information of an edit and can be used to apply edits to new inputs. We experiment on natural language and source code edit data. Our evaluation yields promising results that suggest that our neural network models learn to capture the structure and semantics of edits. We hope that this interesting task and data source will inspire other researchers to work further on this problem.
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Call Me Maybe: Enhancing JavaScript Call Graph Construction using Graph Neural Networks
GRAPHIA uses graph neural network link prediction on whole-program graphs to rank candidate callees for unresolved JavaScript call sites, placing the correct one in the top 5 for 72% of cases.