article

Automatic identification of key classes in a software system using webmining techniques

Authors:

Serge DemeyerAuthors Info & Claims

Journal of Software Maintenance and Evolution: Research and Practice, Volume 20, Issue 6

Pages 387 - 417

Published: 01 November 2008 Publication History

Abstract

Software engineers new to a project are often stuck sorting through hundreds of classes in order to find those few classes that offer a significant insight into the inner workings of the software project. To help stimulate this process, we propose a technique that can identify the most important classes in a system or the key classes of that system. Software engineers can use these classes to focus their understanding efforts when starting to work on a new software project. Those key classes are typically characterized with having a lot of 'control' within the application. In order to find these controlling classes, we present a detection approach that is based on dynamic coupling and webmining. We demonstrate the potential of our technique using two open-source software systems that have a rich documentation set. During the case studies we use dynamically gathered coupling information that vary between a number of coupling metrics. The case studies show that we are able to retrieve 90% of the classes deemed important by the original maintainers of the systems, while maintaining a level of precision of around 50%. Copyright © 2008 John Wiley & Sons, Ltd.

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Cited By

Pan WKessentini MMing HYang Z(2023)EASE: An Effort-aware Extension of Unsupervised Key Class Identification ApproachesACM Transactions on Software Engineering and Methodology10.1145/363571433:4(1-43)Online publication date: 2-Dec-2023
https://dl.acm.org/doi/10.1145/3635714
Pan WMing HKim DYang Z(2023)Pride: Prioritizing Documentation Effort Based on a PageRank-Like Algorithm and Simple Filtering RulesIEEE Transactions on Software Engineering10.1109/TSE.2022.317146949:3(1118-1151)Online publication date: 1-Mar-2023
https://dl.acm.org/doi/10.1109/TSE.2022.3171469
Pan WDu XMing HKim DYang ZGrundy JPollock LPenta M(2023)Identifying Key Classes for Initial Software Comprehension: Can We Do it Better?Proceedings of the 45th International Conference on Software Engineering10.1109/ICSE48619.2023.00160(1878-1889)Online publication date: 14-May-2023
https://dl.acm.org/doi/10.1109/ICSE48619.2023.00160
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Index Terms

Automatic identification of key classes in a software system using webmining techniques

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cover image Journal of Software Maintenance and Evolution: Research and Practice

Journal of Software Maintenance and Evolution: Research and Practice Volume 20, Issue 6

November 2008

77 pages

ISSN:1532-060X

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John Wiley & Sons, Inc.

United States

Publication History

Published: 01 November 2008

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Cited By

Pan WKessentini MMing HYang Z(2023)EASE: An Effort-aware Extension of Unsupervised Key Class Identification ApproachesACM Transactions on Software Engineering and Methodology10.1145/363571433:4(1-43)Online publication date: 2-Dec-2023
https://dl.acm.org/doi/10.1145/3635714
Pan WMing HKim DYang Z(2023)Pride: Prioritizing Documentation Effort Based on a PageRank-Like Algorithm and Simple Filtering RulesIEEE Transactions on Software Engineering10.1109/TSE.2022.317146949:3(1118-1151)Online publication date: 1-Mar-2023
https://dl.acm.org/doi/10.1109/TSE.2022.3171469
Pan WDu XMing HKim DYang ZGrundy JPollock LPenta M(2023)Identifying Key Classes for Initial Software Comprehension: Can We Do it Better?Proceedings of the 45th International Conference on Software Engineering10.1109/ICSE48619.2023.00160(1878-1889)Online publication date: 14-May-2023
https://dl.acm.org/doi/10.1109/ICSE48619.2023.00160
Haas RNiedermayr RRoehm TApel S(2020)Is Static Analysis Able to Identify Unnecessary Source Code?ACM Transactions on Software Engineering and Methodology10.1145/336826729:1(1-23)Online publication date: 30-Jan-2020
https://dl.acm.org/doi/10.1145/3368267
Wang MLi YLuo SHu Z(2019)Discovering Important Services Based on Weighted K-Core DecompositionInternational Journal of Web Services Research10.4018/IJWSR.201901010216:1(22-36)Online publication date: 1-Jan-2019
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Zhou SWang Y(2019)Service ranking in service networks using parameters in complex networks: a comparative studyCluster Computing10.1007/s10586-017-1694-622:2(2921-2930)Online publication date: 1-Mar-2019
https://dl.acm.org/doi/10.1007/s10586-017-1694-6
Pan WSong BLi KZhang K(2018)Identifying key classes in object-oriented software using generalized k-core decompositionFuture Generation Computer Systems10.1016/j.future.2017.10.00681:C(188-202)Online publication date: 1-Apr-2018
https://dl.acm.org/doi/10.1016/j.future.2017.10.006
Pan WLi BLiu JMa YHu B(2018)Analyzing the structure of Java software systems by weighted K-core decompositionFuture Generation Computer Systems10.1016/j.future.2017.09.03983:C(431-444)Online publication date: 1-Jun-2018
https://dl.acm.org/doi/10.1016/j.future.2017.09.039
Vale LMaia MScanniello GLo DSerebrenik A(2017)On the properties of design-relevant classes for design anomaly assessmentProceedings of the 25th International Conference on Program Comprehension10.1109/ICPC.2017.17(332-335)Online publication date: 20-May-2017
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Muhammad THalim ZKhan M(2017)Visualizing trace of Java collection APIs by dynamic bytecode instrumentationJournal of Visual Languages and Computing10.1016/j.jvlc.2017.04.00643:C(14-29)Online publication date: 1-Dec-2017
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