Identifying Key Classes Based on Weighted K-Core Analysis of Software Networks

doi:10.3969/j.issn.0372-2112.2018.05.007

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Identifying Key Classes Based on Weighted K-Core Analysis of Software Networks

更新时间：2025-07-08

- Identifying Key Classes Based on Weighted K-Core Analysis of Software Networks
- Acta Electronica Sinica Vol. 46, Issue 5, Pages: 1071-1077(2018)
- 作者机构：
  
  1. 浙江工商大学计算机与信息工程学院,浙江,杭州,310018
  2. 金蝶国际软件集团金蝶研究院,广东,深圳,518057
  3. 武汉大学国际软件学院,湖北,武汉,430072
  4. 浙江工商大学计算机与信息工程学院,浙江,杭州,310018
  5. 金蝶国际软件集团金蝶研究院,广东,深圳,518057
  6. 武汉大学国际软件学院,湖北,武汉,430072
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.0372-2112.2018.05.007
  CLC： TP311.5
- Published：2018
- 稿件说明：
移动端阅览
Identifying Key Classes Based on Weighted K-Core Analysis of Software Networks[J]. Acta Electronica Sinica, 2018, 46(5): 1071-1077.
DOI：

Identifying Key Classes Based on Weighted K-Core Analysis of Software Networks[J]. Acta Electronica Sinica, 2018, 46(5): 1071-1077. DOI： 10.3969/j.issn.0372-2112.2018.05.007.

摘要

识别关键类可以帮助人们尽快理解不熟悉的软件系统.尽管目前已有一些关键类识别方面的工作，但是大部分方法构建的依赖图是无权的，未考虑类之间交互的种类及次数.有鉴于此，提出了一种基于软件网络加权

-核分析的关键类识别方法.首先，用加权类耦合网络抽象类（接口）、类（接口）间的交互及其次数；然后，引入加权

-核分解方法计算类的加权核数；最后，以加权核数作为类重要性的量度指标，降序排列所有类，并通过过滤得到候选关键类.真实软件上的数据实验验证了本文方法的有效性.

Abstract

Identifying key classes can help software engineers understand software systems that they previously were not familiar with.Though there are some methods on the identification of key classes

a majority of them use un-weighted dependency graphs

neglecting the coupling types and frequencies.In this paper

we propose a method to identify the key classes based on weighted

-core analysis of software networks.First

it uses a weighted class coupling network to represent classes (interfaces) and their couplings and coupling frequencies.Then

we introduce the weighted

-core decomposition method to compute the weighted coreness for each class (interface).Finally

we use the weighted coreness to quantify the importance of classes (interfaces) and sor

t them in a descending order with respect to their weighted corenesses.And the top-ranked classes (interfaces) will serve as the key class candidates.Empirical results show the effectiveness of our approach.

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