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Identifying key classes of object-oriented software based on software complex network

  • Jiaming Wang
  • , Jun Ai
  • , Yiwen Yang
  • , Wenzhu Su
  • Beihang University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Identifying the most important classes in a software system is crucial for engineers to understand or maintain an unfamiliar system. Complex network theory provides a new way to study the characteristics of large-scale software. Unfortunately, most current studies consider only one or a limited number of factors affecting software structure, rendering inaccurate the results of mining the key classes of software. Thus, we propose an approach using various complex network metrics to automatically identify key classes from global and local aspects. From the global aspect, the location of a class and its ability to control the information flow of software are mainly considered. From local aspects, we focus on the interactions of classes with their neighbors, as well as the complexity of the class itself. Experiments are performed on two Java open-source projects. Results show that this approach can accurately identify key classes compared with existing literature.

Original languageEnglish
Title of host publication2017 2nd International Conference on System Reliability and Safety, ICSRS 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages444-449
Number of pages6
ISBN (Electronic)9781538633229
DOIs
StatePublished - 2 Jul 2017
Event2nd International Conference on System Reliability and Safety, ICSRS 2017 - Milan, Italy
Duration: 20 Dec 201722 Dec 2017

Publication series

Name2017 2nd International Conference on System Reliability and Safety, ICSRS 2017
Volume2018-January

Conference

Conference2nd International Conference on System Reliability and Safety, ICSRS 2017
Country/TerritoryItaly
CityMilan
Period20/12/1722/12/17

Keywords

  • complex network metrics
  • key classes
  • software complex network

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