Design Smell Detection and Analysis for Open Source Java Software

Asif Imran

doi:10.1109/ICSME.2019.00104

Design Smell Detection and Analysis for Open Source Java Software

Asif Imran

Department of Computer Science and Engineering

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

15 Scopus citations

Abstract

Software design smells have gained significant importance in recent years since those directly lead to the increase of design debts and drastically affect software quality. Although the impact of design smells is manifold, techniques to detect design smells using both rule based and data mining approaches have been explored to a limited extent. This research aims to provide a tool which uses software metrics as a guide to detect smells and also deploys Spectral Clustering to mine the software repositories and group similar smells. The tool has been partially implemented till now and initial experiments on 2,59,509 Lines of Code (LoC) covering 3,306 classes of real life open source Java software show 2,220 occurrences of four types of design smells.

Original language	English
Title of host publication	Proceedings - 2019 IEEE International Conference on Software Maintenance and Evolution, ICSME 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	644-648
Number of pages	5
ISBN (Electronic)	9781728130941
DOIs	https://doi.org/10.1109/ICSME.2019.00104
State	Published - Sep 2019
Event	2019 IEEE International Conference on Software Maintenance and Evolution, ICSME 2019 - Cleveland, United States Duration: Sep 30 2019 → Oct 4 2019

Publication series

Name	Proceedings - 2019 IEEE International Conference on Software Maintenance and Evolution, ICSME 2019

Conference

Conference	2019 IEEE International Conference on Software Maintenance and Evolution, ICSME 2019
Country/Territory	United States
City	Cleveland
Period	09/30/19 → 10/4/19

Keywords

Design Smell Analysis
Design Smell Detection
Software Engineering

Access to Document

10.1109/ICSME.2019.00104

Cite this

Imran, A. (2019). Design Smell Detection and Analysis for Open Source Java Software. In Proceedings - 2019 IEEE International Conference on Software Maintenance and Evolution, ICSME 2019 (pp. 644-648). Article 8919054 (Proceedings - 2019 IEEE International Conference on Software Maintenance and Evolution, ICSME 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICSME.2019.00104

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title = "Design Smell Detection and Analysis for Open Source Java Software",

abstract = "Software design smells have gained significant importance in recent years since those directly lead to the increase of design debts and drastically affect software quality. Although the impact of design smells is manifold, techniques to detect design smells using both rule based and data mining approaches have been explored to a limited extent. This research aims to provide a tool which uses software metrics as a guide to detect smells and also deploys Spectral Clustering to mine the software repositories and group similar smells. The tool has been partially implemented till now and initial experiments on 2,59,509 Lines of Code (LoC) covering 3,306 classes of real life open source Java software show 2,220 occurrences of four types of design smells.",

keywords = "Design Smell Analysis, Design Smell Detection, Software Engineering",

author = "Asif Imran",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE International Conference on Software Maintenance and Evolution, ICSME 2019 ; Conference date: 30-09-2019 Through 04-10-2019",

year = "2019",

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language = "English",

series = "Proceedings - 2019 IEEE International Conference on Software Maintenance and Evolution, ICSME 2019",

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Imran, A 2019, Design Smell Detection and Analysis for Open Source Java Software. in Proceedings - 2019 IEEE International Conference on Software Maintenance and Evolution, ICSME 2019., 8919054, Proceedings - 2019 IEEE International Conference on Software Maintenance and Evolution, ICSME 2019, Institute of Electrical and Electronics Engineers Inc., pp. 644-648, 2019 IEEE International Conference on Software Maintenance and Evolution, ICSME 2019, Cleveland, United States, 09/30/19. https://doi.org/10.1109/ICSME.2019.00104

Design Smell Detection and Analysis for Open Source Java Software. / Imran, Asif.
Proceedings - 2019 IEEE International Conference on Software Maintenance and Evolution, ICSME 2019. Institute of Electrical and Electronics Engineers Inc., 2019. p. 644-648 8919054 (Proceedings - 2019 IEEE International Conference on Software Maintenance and Evolution, ICSME 2019).

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

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AB - Software design smells have gained significant importance in recent years since those directly lead to the increase of design debts and drastically affect software quality. Although the impact of design smells is manifold, techniques to detect design smells using both rule based and data mining approaches have been explored to a limited extent. This research aims to provide a tool which uses software metrics as a guide to detect smells and also deploys Spectral Clustering to mine the software repositories and group similar smells. The tool has been partially implemented till now and initial experiments on 2,59,509 Lines of Code (LoC) covering 3,306 classes of real life open source Java software show 2,220 occurrences of four types of design smells.

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KW - Design Smell Detection

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M3 - Conference contribution

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BT - Proceedings - 2019 IEEE International Conference on Software Maintenance and Evolution, ICSME 2019

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ER -

Imran A. Design Smell Detection and Analysis for Open Source Java Software. In Proceedings - 2019 IEEE International Conference on Software Maintenance and Evolution, ICSME 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 644-648. 8919054. (Proceedings - 2019 IEEE International Conference on Software Maintenance and Evolution, ICSME 2019). doi: 10.1109/ICSME.2019.00104

Design Smell Detection and Analysis for Open Source Java Software

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Keywords

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