TY - GEN

T1 - PathMiner: a library for mining of path-based representations of code

AU - Kovalenko, Vladimir

AU - Bogomolov, Egor

AU - Bryksin, Timofey

AU - Bacchelli, Alberto

N1 - Publisher Copyright: © 2019 IEEE.

PY - 2019/5

Y1 - 2019/5

N2 - 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. PathMiner is fast, flexible, well-tested, and easily extensible to support input code in any common programming language.

AB - 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. PathMiner is fast, flexible, well-tested, and easily extensible to support input code in any common programming language.

KW - Ast path

KW - Code2Vec

KW - Machine learning on code

KW - Mining tool

KW - Path based representation

UR - https://2019.msrconf.org/details/msr-2019-papers/38/PathMiner-A-Library-for-Mining-of-Path-Based-Representations-of-Code

UR - http://www.scopus.com/inward/record.url?scp=85072347462&partnerID=8YFLogxK

U2 - 10.1109/MSR.2019.00013

DO - 10.1109/MSR.2019.00013

M3 - Conference contribution

SN - 9781728134123

VL - 2019

SP - 13

EP - 17

BT - Proceedings - 2019 IEEE/ACM 16th International Conference on Mining Software Repositories, MSR 2019

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 16th International Conference on Mining Software Repositories

Y2 - 26 May 2019 through 27 May 2019

ER -