research-article

JavaRelationshipGraphs (JRG): Transforming Java Projects into Graphs using Neo4j Graph Databases

Authors:

Sanjay GoelAuthors Info & Claims

ICSIM '19: Proceedings of the 2nd International Conference on Software Engineering and Information Management

Pages 80 - 84

https://doi.org/10.1145/3305160.3305173

Published: 10 January 2019 Publication History

Abstract

Understanding dependency relationship between various program elements in an object-oriented system is essential for many software engineering applications. In this paper, we propose a novel approach of transforming a Java project into a connected graph comprising of program elements (represented as graph nodes) connected to each other using ownership and dependency relationships (represented as edges). These graphs, named as JavaRelationshipGraphs (JRG) are created and stored using Neo4j Graph Database. Additionally, the proposed JavaRelationshipGraphs framework provides details about the two-staged conversion process along with the algorithms involved. The JRG framework uses compiled Java project to obtain the corresponding graph, which can be effectively visualized and queried using the Neo4j browser. JRG is capable of representing most of the important object-oriented features like inheritance, encapsulation, method overloading and overriding. Hence, they are suitable for use in software engineering applications like program dependence analysis, code mining, etc.

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Cited By

Borowski KBalis BOrzechowski T(2024)Semantic Code Graph—An Information Model to Facilitate Software ComprehensionIEEE Access10.1109/ACCESS.2024.335184512(27279-27310)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3351845
Putrama IMartinek P(2022)An Automated Graph Construction Approach from Relational Databases to Neo4j2022 IEEE 22nd International Symposium on Computational Intelligence and Informatics and 8th IEEE International Conference on Recent Achievements in Mechatronics, Automation, Computer Science and Robotics (CINTI-MACRo)10.1109/CINTI-MACRo57952.2022.10029438(000131-000136)Online publication date: 21-Nov-2022
https://doi.org/10.1109/CINTI-MACRo57952.2022.10029438
Steinhauer MPalomba FKhomh FSalza PCatolino G(2020)Speeding up the data extraction of machine learning approaches: a distributed frameworkProceedings of the 4th ACM SIGSOFT International Workshop on Machine-Learning Techniques for Software-Quality Evaluation10.1145/3416505.3423562(13-18)Online publication date: 13-Nov-2020
https://dl.acm.org/doi/10.1145/3416505.3423562

Index Terms

JavaRelationshipGraphs (JRG): Transforming Java Projects into Graphs using Neo4j Graph Databases
1. Software and its engineering
  1. Software notations and tools
    1. General programming languages
      1. Language types
        Object oriented languages

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ICSIM '19: Proceedings of the 2nd International Conference on Software Engineering and Information Management

January 2019

293 pages

ISBN:9781450366427

DOI:10.1145/3305160

Copyright © 2019 ACM.

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Published: 10 January 2019

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ICSIM 2019

ICSIM 2019: The 2nd International Conference on Software Engineering and Information Management

January 10 - 13, 2019

Bali, Indonesia

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Cited By

Borowski KBalis BOrzechowski T(2024)Semantic Code Graph—An Information Model to Facilitate Software ComprehensionIEEE Access10.1109/ACCESS.2024.335184512(27279-27310)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3351845
Putrama IMartinek P(2022)An Automated Graph Construction Approach from Relational Databases to Neo4j2022 IEEE 22nd International Symposium on Computational Intelligence and Informatics and 8th IEEE International Conference on Recent Achievements in Mechatronics, Automation, Computer Science and Robotics (CINTI-MACRo)10.1109/CINTI-MACRo57952.2022.10029438(000131-000136)Online publication date: 21-Nov-2022
https://doi.org/10.1109/CINTI-MACRo57952.2022.10029438
Steinhauer MPalomba FKhomh FSalza PCatolino G(2020)Speeding up the data extraction of machine learning approaches: a distributed frameworkProceedings of the 4th ACM SIGSOFT International Workshop on Machine-Learning Techniques for Software-Quality Evaluation10.1145/3416505.3423562(13-18)Online publication date: 13-Nov-2020
https://dl.acm.org/doi/10.1145/3416505.3423562

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