115 citations · 195 across the 32 of their papers we have counts for
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cs.SE2021
Unsupervised Learning of General-Purpose Embeddings for Code Changes
Mikhail Pravilov, Egor Bogomolov, Yaroslav Golubev +1
Applying machine learning to tasks that operate with code changes requires their numerical representation. In this work, we propose an approach for obtaining such representations d…
cs.SE2021
PSIMiner: A Tool for Mining Rich Abstract Syntax Trees from Code
Egor Spirin, Egor Bogomolov, Vladimir Kovalenko +1
The application of machine learning algorithms to source code has grown in the past years. Since these algorithms are quite sensitive to input data, it is not surprising that resea…