  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 researchers experiment with input representations.
Nowadays, a popular starting point to represent code is abstract syntax trees
(ASTs). Abstract syntax trees have been used for a long time in various
software engineering domains, and in particular in IDEs. The API of modern IDEs
allows to manipulate and traverse ASTs, resolve references between code
elements, etc. Such algorithms can enrich ASTs with new data and therefore may
be useful in ML-based code analysis. In this work, we present PSIMiner - a tool
for processing PSI trees from the IntelliJ Platform. PSI trees contain code
syntax trees as well as functions to work with them, and therefore can be used
to enrich code representation using static analysis algorithms of modern IDEs.
To showcase this idea, we use our tool to infer types of identifiers in Java
ASTs and extend the code2seq model for the method name prediction problem.
