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MSR 2019
Sun 26 - Mon 27 May 2019 Montreal, QC, Canada
co-located with ICSE 2019

One recent, significant advance in modeling source code for machine learning algorithms has been the introduction of path-based representation – an approach consisting in representing a snippet of code as a collection of paths from its syntax tree. Such representation efficiently captures the structure of code, which, in turn, carries its semantics and other information. Building the path-based representation involves parsing the code and extracting the paths from its syntax tree; these steps build up to a substantial technical job. With no common reusable toolkit existing for this task, the burden of mining diverts the focus of researchers from the essential work and hinders newcomers in the field of machine learning on code.

In this paper, we present PathMiner – an open-source library for mining path-based representations of code. Path- Miner is fast, flexible, well-tested, and easily extensible to support input code in any common programming language.

Sun 26 May

msr-2019-Paper-Presentations
11:00 - 11:45: MSR 2019 Paper Presentations - Session I: Representations for Mining (Part 1) at Place du Canada
Chair(s): Chanchal K. RoyUniversity of Saskatchewan
msr-2019-papers11:00 - 11:15
Full-paper
Pre-print Media Attached
msr-2019-papers11:16 - 11:22
Short-paper
Vladimir KovalenkoTU Delft, Egor BogomolovHigher School of Economics, JetBrains Research, Timofey Bryksin, Alberto BacchelliUniversity of Zurich
DOI Pre-print Media Attached
msr-2019-papers11:23 - 11:38
Full-paper
Bart TheetenNokia Bell Labs, Belgium, Frederik Vandeputte, Tom Van CutsemNokia Bell Labs
Pre-print
msr-2019-Data-Showcase11:39 - 11:45
Talk
Vasiliki EfstathiouAthens University of Economics and Business, Diomidis SpinellisAthens University of Economics and Business
Pre-print