research-article

ENRE: a tool framework for extensible eNtity relation extraction

Authors:

Di Cui,

Ting LiuAuthors Info & Claims

ICSE '19: Proceedings of the 41st International Conference on Software Engineering: Companion Proceedings

Pages 67 - 70

https://doi.org/10.1109/ICSE-Companion.2019.00040

Published: 25 May 2019 Publication History

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Abstract

Understanding the dependencies among code entities is fundamental to many software analysis tools and techniques. However, with the emergence of new programming languages and paradigms, the increasingly common practice of writing systems in multiple languages, and the increasing popularity of dynamic languages, no existing framework can reliably extract this information. That is, no tools exist to accurately extract dependencies from systems written in multiple and dynamic languages. To address this problem, we have designed and implemented the Extensible eNtity Relation Extraction (ENRE) framework. ENRE supports the extraction of entities and their dependencies from systems written in multiple languages, enables the customization of dependencies of interest to the user, and makes implicit dependencies explicit. To demonstrate feasibility of this framework, we developed two ENRE instances for analyzing Python and Golang programs. Our experiments on 12 Python and Golang projects demonstrated the effectiveness and flexibility of ENRE. By comparing with a commercial static analysis tool, we show that we can extract dependencies from Golang programs which are not supported by existing tools and we can reveal implicit dependencies in Python.

(Demo Video: https://youtu.be/BfXp5bb1yqc)

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Cui DWang JWang QJi PQiao MZhao YHu JWang LLi QFilkov VRay BZhou M(2024)Three Heads Are Better Than One: Suggesting Move Method Refactoring Opportunities with Inter-class Code Entity Dependency Enhanced Hybrid Hypergraph Neural NetworkProceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering10.1145/3691620.3695068(745-757)Online publication date: 27-Oct-2024
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Feng QJi HMa XLiang P(2024)Cross-Language Dependencies: An Empirical Study of Kotlin-JavaProceedings of the 18th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement10.1145/3674805.3686680(189-199)Online publication date: 24-Oct-2024
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Information & Contributors

Information

Published In

ICSE '19: Proceedings of the 41st International Conference on Software Engineering: Companion Proceedings

May 2019

369 pages

Conference Chair:
Gunter Mussbacher
McGill University, Canada
,
General Chair:
Joanne M. Atlee
University of Waterloo, Canada
,
Program Chair:
Tevfik Bultan
University of California, Santa Barbara

Publisher

IEEE Press

Publication History

Published: 25 May 2019

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ICSE '19

Sponsor:

SIGSOFT
IEEE-CS

ICSE '19: 41st International Conference on Software Engineering

May 25 - 31, 2019

Quebec, Montreal, Canada

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Overall Acceptance Rate 276 of 1,856 submissions, 15%

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April 26 - May 3, 2025

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Cui DWang JWang QJi PQiao MZhao YHu JWang LLi QFilkov VRay BZhou M(2024)Three Heads Are Better Than One: Suggesting Move Method Refactoring Opportunities with Inter-class Code Entity Dependency Enhanced Hybrid Hypergraph Neural NetworkProceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering10.1145/3691620.3695068(745-757)Online publication date: 27-Oct-2024
https://dl.acm.org/doi/10.1145/3691620.3695068
Feng QJi HMa XLiang P(2024)Cross-Language Dependencies: An Empirical Study of Kotlin-JavaProceedings of the 18th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement10.1145/3674805.3686680(189-199)Online publication date: 24-Oct-2024
https://dl.acm.org/doi/10.1145/3674805.3686680
Hou YJin WWang ZWang LChen SWang YSang LWang HLiu T(2024)ERD-CQC : Enhanced Rule and Dependency Code Quality Check for JavaProceedings of the 15th Asia-Pacific Symposium on Internetware10.1145/3671016.3674820(377-386)Online publication date: 24-Jul-2024
https://dl.acm.org/doi/10.1145/3671016.3674820
Meng FWang YChong CYu HZhu Z(2024)CLUE: Customizing clustering techniques using machine learning for software modularizationProceedings of the 15th Asia-Pacific Symposium on Internetware10.1145/3671016.3674816(189-198)Online publication date: 24-Jul-2024
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Wang LWang QWang JZhao YWei MQuan ZCui DLi QChristakis MPradel M(2024)HECS: A Hypergraph Learning-Based System for Detecting Extract Class Refactoring OpportunitiesProceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis10.1145/3650212.3685307(1851-1855)Online publication date: 11-Sep-2024
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Cui DWang QZhao YWang JWei MHu JWang LLi QChristakis MPradel M(2024)One-to-One or One-to-Many? Suggesting Extract Class Refactoring Opportunities with Intra-class Dependency Hypergraph Neural NetworkProceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis10.1145/3650212.3680379(1529-1540)Online publication date: 11-Sep-2024
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