Enabling Analysis and Reasoning on Software Systems through Knowledge Graph Representation

Satrio Adi Rukmono; Michel R.V. Chaudron

doi:10.1109/MSR59073.2023.00029

Enabling Analysis and Reasoning on Software Systems through Knowledge Graph Representation

Satrio Adi Rukmono, Michel R.V. Chaudron

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

4 Citations (Scopus)

13 Downloads (Pure)

Abstract

This work presents a knowledge-representation-based approach for analysing software systems. Its main components are: a generic and extensible knowledge model, and a knowledge extractor tool that generates instance-level knowledge graphs from software repositories (currently Java). Our knowledge model can be used as a shared data-model in a software analysis pipeline. We illustrate the potential uses of our knowledge representation by performing experimental architecture recovery and identifying design pattern instance. We intend to use our ontology and extraction tool as a partial foundation for automated reasoning on software systems.

Original language	English
Title of host publication	2023 IEEE/ACM 20th International Conference on Mining Software Repositories, MSR 2023
Publisher	Institute of Electrical and Electronics Engineers
Pages	120-124
Number of pages	5
ISBN (Electronic)	979-8-3503-1184-6
DOIs	https://doi.org/10.1109/MSR59073.2023.00029
Publication status	Published - 12 Jul 2023
Event	20th IEEE/ACM International Conference on Mining Software Repositories, MSR 2023 - Melbourne, Australia Duration: 15 May 2023 → 16 May 2023

Conference

Conference	20th IEEE/ACM International Conference on Mining Software Repositories, MSR 2023
Country/Territory	Australia
City	Melbourne
Period	15/05/23 → 16/05/23

Keywords

knowledge graph
object-oriented
software analysis
software knowledge
software ontology

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10.1109/MSR59073.2023.00029

pdfFinal published version, 794 KBLicence: TAVERNE

Cite this

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title = "Enabling Analysis and Reasoning on Software Systems through Knowledge Graph Representation",

abstract = "This work presents a knowledge-representation-based approach for analysing software systems. Its main components are: a generic and extensible knowledge model, and a knowledge extractor tool that generates instance-level knowledge graphs from software repositories (currently Java). Our knowledge model can be used as a shared data-model in a software analysis pipeline. We illustrate the potential uses of our knowledge representation by performing experimental architecture recovery and identifying design pattern instance. We intend to use our ontology and extraction tool as a partial foundation for automated reasoning on software systems.",

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Rukmono, SA & Chaudron, MRV 2023, Enabling Analysis and Reasoning on Software Systems through Knowledge Graph Representation. in 2023 IEEE/ACM 20th International Conference on Mining Software Repositories, MSR 2023., 10174249, Institute of Electrical and Electronics Engineers, pp. 120-124, 20th IEEE/ACM International Conference on Mining Software Repositories, MSR 2023, Melbourne, Australia, 15/05/23. https://doi.org/10.1109/MSR59073.2023.00029

Enabling Analysis and Reasoning on Software Systems through Knowledge Graph Representation. / Rukmono, Satrio Adi ; Chaudron, Michel R.V.
2023 IEEE/ACM 20th International Conference on Mining Software Repositories, MSR 2023. Institute of Electrical and Electronics Engineers, 2023. p. 120-124 10174249.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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AB - This work presents a knowledge-representation-based approach for analysing software systems. Its main components are: a generic and extensible knowledge model, and a knowledge extractor tool that generates instance-level knowledge graphs from software repositories (currently Java). Our knowledge model can be used as a shared data-model in a software analysis pipeline. We illustrate the potential uses of our knowledge representation by performing experimental architecture recovery and identifying design pattern instance. We intend to use our ontology and extraction tool as a partial foundation for automated reasoning on software systems.

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KW - object-oriented

KW - software analysis

KW - software knowledge

KW - software ontology

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BT - 2023 IEEE/ACM 20th International Conference on Mining Software Repositories, MSR 2023

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Y2 - 15 May 2023 through 16 May 2023

ER -

Enabling Analysis and Reasoning on Software Systems through Knowledge Graph Representation

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