|Table of Contents|

Empirical analysis and proneness metrics of class change based on feature influence network

《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

Issue:
2013年06期
Page:
839-844
Research Field:
Publishing date:

Info

Title:
Empirical analysis and proneness metrics of class change based on feature influence network
Author(s):
Han Lei1Wei Huihui2Xu Jian2
1.Research and Development Center,Huawei Technologies Co.,Ltd.,Nanjing 210008,China;
2.School of Computer Science and Engineering,NUST,Nanjing 210094,China
Keywords:
software metrics software change feature influence network object-oriented software class change
PACS:
TP393
DOI:
-
Abstract:
To improve software product quality,reduce software change maintenance costs,valid class change proneness metrics is designed for recognizing classes with change proneness from the software network view.Taking typical and various types of open source object-oriented software as research objects,a feature influence network(FIN)is constructed.Class change proneness metric considering the direct influence relationship of software change is proposed combining the characteristics of the FIN.Empirical analysis results show that the metrics has good class proneness prediction capacity with the minimum matching rate of 60% and is better than weighted method count(WMC)and coupling between objects(CBO)of C&K metrics in terms of the matching rate.

References:

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Last Update: 2013-12-31