Fuzzy Network Based Framework for Software Maintainability Prediction

Author:

Wang Xiaowei1ORCID,Gegov Alexander2,Farzad Arabikhan2,Chen Yuntao3,Hu Qiwei4

Affiliation:

1. Department of Computer, Army Engineering University of PLA, Wuhan, 430075, P. R. China

2. School of Computing, University of Portsmouth, Buckingham Building, Portsmouth, PO1 3HE, United Kingdom

3. Department of Radar, Army Engineering University of PLA, Wuhan, 430075, P. R. China

4. Department of Management Engineering, Army Engineering University of PLA, Shijiazhuang, 050003, P. R. China

Abstract

Software metrics based maintainability prediction is leading to development of new sophisticated techniques to construct prediction models. This paper proposes a new software maintainability prediction framework, which bases on Fuzzy Network, a novel exploratory modeling technique. The proposed framework utilizes both the metric data collected from software system and the subjective appraisals from experts. An application example of the framework is shown. In comparison to the Standard Fuzzy System based models, Fuzzy Network based models improves the transparency more than 71.3% and the accuracy more than 11.0%. It is confirmed that Fuzzy Network based framework is more appropriate for constructing SMP model.

Funder

China Scholarship Council

Publisher

World Scientific Pub Co Pte Lt

Subject

Artificial Intelligence,Information Systems,Control and Systems Engineering,Software

Cited by 15 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Introduction to Big Data Analytics;Big Data Analytics Techniques for Market Intelligence;2024-01-04

2. Moving Towards Explainable Artificial Intelligence Using Fuzzy Rule-Based Networks in Decision-Making Process;Advances in Information Systems, Artificial Intelligence and Knowledge Management;2024

3. Fuzzy Networks for Explainable Artificial Intelligence;2023 IEEE Conference on Artificial Intelligence (CAI);2023-06

4. Collaborative possibilistic fuzzy clustering based on information bottleneck;Journal of Intelligent & Fuzzy Systems;2023-05-04

5. Analysis of Hybridized Techniques with Class Imbalance Learning for Predicting Software Maintainability;International Journal of Reliability, Quality and Safety Engineering;2023-04

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3