A software quality evaluation model
based on hesitant fuzzy set
#br#

Abstract

Abstract:

A software quality evaluation model based on hesitant fuzzy set is proposed. Firstly, according to the expert score, hesitant fuzzy set and intuitionistic fuzzy set are combined to obtain a comprehensive hesitant fuzzy evaluation matrix of software quality characteristics. Then, by calculating the hesitant fuzzy generalized comparison table, the scores of each quality attribute of the software are obtained. Finally, the quality order of the software is given according to the score. It better solves the he- sitant problem when experts evaluate software quality indicators. Specific case analysis proves that the proposed software quality evaluation model is feasible and effective.

Key words: software, quality evaluation, hesitant fuzzy set, multi-attribute decision

YU Jian-li,LU Jiao,CHEN Hong-gen.

A software quality evaluation model

based on hesitant fuzzy set

#br# [J]. Computer Engineering & Science.

References ［31］

［1］	Ji Qing-yun.Application of software engineering technology in system software development process［J］.Think Tank Age,2018
(44)	:167.(in Chinese)
［2］	Sarkar S, Rama G, Kak A. API-based and information-theoretic metrics for measuring the quality of software modula- rization［J］.IEEE Transactions on Software Engineering,2007,33(1):14-32.
［3］	Xu Man-yi. Study on software quality comprehensive evalu- ation method based on improved particle swarm algorithm［D］.Lanzhou:Northwest Normal University,2013.(in Chinese)
［4］	Tomas P, Escalona M J,Mejias M.Open source tools for measuring the internal quality of Java software products. A survey.［J］.Computer Standards & Interfaces,2013,36(1):244-255.
［5］	Peng Kai. Application of software engineering method in computer software development［J］.Electronic Technology & Software Engineering,2018(8):50.(in Chinese)
［6］	Yang Fu-qing.Thinking on the development of software engineering technology［J］.Journal of Software,2005,16(1):1-7.(in Chinese)
［7］	Boehm B W,Brown J R,Lipow M.Quantitative evaluation of software quality［C］∥Proc of International Conference on Software Engineering,1976:1-29.
［8］	McCall J,Richards P,Walters G.Factors in software quality:Technical Report CDRL A2003［R］.New York:US Rome Air Development Centre,1977.
［9］	ISO/IEC 9126-l: Information technology-software product quality-parl:Quality model ［S］.Geneva:ISO/IEC/JTC1/Junio,1998.
［10］	Abreu F B E, Melo W.Evaluating the impact of object- oriented design on software quality［C］∥Proc of the 3rd International Software Metrics Symposium,1996:1-10.
［11］	de Almeida M A, Matwin S.Machine learning method for software quality model building［C］∥Proc of International Symposium on Methodologies for Intelligent Systems,1999:565-573.
［12］	Hou Mi.Research and application of software quality evaluation method based on analytic hierarchy process［J］.Software Industry and Engineering,2016(4):29-34.(in Chinese)
［13］	Li Jian, Wei Ling-nan.Application of AHP and fuzzy analysis in choice of CAD software［J］. Modular Machine Tool & Automatic Manufacturing Technique,2004(4):27-28.(in Chinese)
［14］	Qin Jin,Zhi Rong-teng.Application research of BP neural network in software quality evaluation［J］.Software Guide,2016,15(9):1-3.(in Chinese)
［15］	Yue Chuan. A model for evaluating software quality based on symbol information［J］.Journal of Guangdong Ocean University,2016,36(1):85-92.(in Chinese)
［16］	Yan Qiong,Zhang Hai-jun.Quality evaluation of software development based on QFD［J］.Value Engineering,2019,38(14):179-182.(in Chinese)
［17］	Wang Xiao-xia, Wang Tao, Gu Gen-dai.Neural network based on modified particle swarm optimization and its application［J］.Journal of North China Electric Power University (Natural Science Edition),2009,36(5):99-102.(in Chinese)
［18］	Zhang Dan,Song Xiao-qiu.Research on software quality evaluation model based on genetic algorithm and BP artificial neural network［J］.China New Communications,2016,18(4):84-87.(in Chinese)
［19］	Zadeh L A.Fuzzy sets［J］.Information and Control,1965,8(3):338-353.
［20］	Cui Xiao-dan,Gong Jia-yu,Liu Xiao-qiang.Research on domain-oriented software quality evaluation method［J］.Information Technology & Standardization,2018(3):36-40.(in Chinese)
［21］	Li Shi-qun,Wang Kun-sheng,Jing Xiao-chuan, et al.Evaluation for effectiveness of software’s protection based on FAHP［J］.Computer Technology and Development,2018,28(4):133-140.(in Chinese)
［22］	Zheng Peng. FUZZY-SVM based software quality comprehensive evaluation［J］.Journal of Changchun University of Technology,2018,39(3):278-281.(in Chinese)
［23］	Atanassov K T.Intuitionistic fuzzy sets［J］.Fuzzy Sets and Systems,1986,20(1):87-96.
［24］	Atanassov K T, Gargov G.Interval valued intuitionistic fuzzy sets［J］.Fuzzy Sets and Systems,1989,31(3):343-349.
［25］	Torra V.Hesitant fuzzy sets［J］.International Journal of Intelligent Systems,2010,25(6):529-539.
［26］	Zhu Sheng, Liu Zhong-qiang.The method of pricing real option based on fuzzy set theory［J］.Mathematics in Economics,2008,25(3):242-247.(in Chinese)
［27］	Yang Mei-qi. Research on the evaluation method in constructing bidding based on interval-value hesitant fuzzy set［D］.Chengdu:Southwest Jiaotong University,2017.(in Chinese)
［28］	Zhang Li, Li Qian, Yu Jian-li. Patent quality evaluation model based on hesitant fuzzy soft set［J］.Science & Technology for Development,2018(5):440-446.(in Chinese)
［29］	Zhao Yi-ding, Li Zhi-min, Zhang Xi-guang. Model for software quality evaluation with fuzzy information［J］.Journal of Computational and Theoretical Nanoscience,
20	16,13(10):7394-7398.
［30］	Torra V,Narukawa Y.On hesitant fuzzy sets and decision［C］∥Proc of 2009 International Conference on Fuzzy Systems,2009:1378-1382.
［31］	Zhou Xiao-qiang.Soft set and hesitant fuzzy set with their application in decision making［D］.Changsha:Hunan University,2014.(in Chinese)
	附中文参考文献：
［1］	纪青云.软件工程技术在系统软件开发过程中的应用［J］.智库时代,2018(44):167.
［3］	徐满意.改进粒子群的软件质量综合评价方法研究［D］.兰州：西北师范大学,2013.
［5］	彭凯.软件工程方法在计算机软件开发中的运用［J］.电子技术与软件工程,2018(8):50.
［6］	杨芙清.软件工程技术发展思索［J］.软件学报,2005,16(1):1-7.
［12］	侯觅.基于层次分析法的软件质量评价方法的研究与应用［J］.软件产业与工程,2016(4):29-34.
［13］	李健,韦灵南.层次分析法与模糊评价在CAD软件选择中的应用［J］.组合机床与自动化加工技术,2004(4):27-28.
［14］	秦晋,智荣腾.BP神经网络在软件质量评价中的应用研究［J］.软件导刊,2016,15(9):1-3.
［15］	岳川.基于符号信息的软件质量评价模型［J］.广东海洋大学学报，2016,36(1):85-92.
［16］	闫琼,张海军.基于QFD的软件系统开发质量评价［J］.价值工程,2019,38(14):179-182.
［17］	王晓霞,王涛,谷根代.基于改进粒子群优化的神经网络及应用［J］.华北电力大学学报（自然科学版）,2009,36(5):99-102.
［18］	张丹,宋晓秋.基于遗传算法和BP人工神经网络的软件质量评价模型研究［J］.中国新通信,2016,18(4):84-87.
［20］	崔潇丹,龚家瑜,刘晓强.面向领域的软件质量评价方法研究［J］.信息技术与标准化,2018(3):36-40.
［21］	李士群,王崑声,经小川,等.基于模糊层次分析法的软件保护有效性评价［J］.计算机技术与发展,2018,28(4):133-140.
［22］	郑鹏.基于FUZZY-SVM的软件质量评价［J］.长春工业大学学报，2018,39(3):278-281.
［26］	朱盛,刘中强.基于模糊集合论的实物期权定价方法［J］.经济数学,2008,25(3):242-247.
［27］	杨美琪.基于区间值犹豫模糊集的施工评标方法研究［D］.成都：西南交通大学,2017.
［28］	张黎,李倩,禹建丽.基于犹豫模糊软集的专利质量评价模型［J］.科技促进发展,2018(5):440-446.
［31］	周小强.软集与犹豫模糊集理论及其在决策中的应用［D］.长沙：湖南大学，2014.

[1]	HUANG Xiaopeng1,HUANG Chuanhe1,NONG Huangwu1,Yang Danfeng1,YANG Jinling2. End-to-end delay in software defined networks [J]. J4, 20160101, 38(01): 67-72.
[2]	ZHANG Yufeng,LOU Fang,ZHANG Li. Security assessment of web applications based on software attack surface [J]. J4, 20160101, 38(01): 73-77.
[3]	TANG Yu, DAI Qi, YANG Zhi-wei, YANG Ai-min, CHEN Li-fang, . A software defect prediction algorithm based on optimized random forest [J]. Computer Engineering & Science, 2023, 45(05): 830-839.
[4]	BAI Jian-jing, GU Rui-chun, LIU Qing-he. A DDoS attack detection scheme based on Bi-LSTM in SDN [J]. Computer Engineering & Science, 2023, 45(02): 277-285.
[5]	WANG Yang, LONG Hai-yan, JIA Xi-ran, . Research on image quality evaluation based on color differential perception of human eye [J]. Computer Engineering & Science, 2023, 45(02): 295-303.
[6]	GOU Ping-zhang, MA Lin, GUO Bao-yong, YUAN Chen. A multi-constrained QoS dual path routing optimization algorithm based on software defined network [J]. Computer Engineering & Science, 2023, 45(01): 46-56.
[7]	SUN Zhi-chao, ZHANG Ce, JIANG Wen-qian, LIU Kai-wei, FAN Miao-miao, LI Wen-yu, WEN Ya-fei. Empirical analysis of the impact of failure detection rate on software reliability [J]. Computer Engineering & Science, 2022, 44(12): 2162-2173.
[8]	NIU Sheng-jie, LI Peng, ZHANG Yu-jie, . Survey on fuzzy testing technologies [J]. Computer Engineering & Science, 2022, 44(12): 2173-2186.
[9]	HE Hai-jiang. A lightweight software fault localization method based on statement complexity [J]. Computer Engineering & Science, 2022, 44(12): 2187-2195.
[10]	GOU Ping-zhang, YUAN Chen, ZHANG Fen. A non-uniform clustering QoS routing algorithm based on software-defined wireless sensor networks [J]. Computer Engineering & Science, 2022, 44(02): 227-236.
[11]	CAO Liang-lin, BEN Ke-rong, ZHANG Xian. A surrogate-assisted multi-objective firefly algorithm for software defect prediction [J]. Computer Engineering & Science, 2022, 44(02): 257-265.
[12]	QIN Ying. A survey on quality evaluation of machine generated texts [J]. Computer Engineering & Science, 2022, 44(01): 138-148.
[13]	ZHU Hao, ZHOU Bo-yang, LU Xue-shan, DU Yi-mo. Evaluation of OpenCL computing software stack [J]. Computer Engineering & Science, 2021, 43(12): 2105-2114.
[14]	MA Jun, ZHOU Kai, REN Yi, ZHU Hao, QIN Ying, WANG Jing. Package dependency analysis for operating system distribution building [J]. Computer Engineering & Science, 2021, 43(11): 1926-1933.
[15]	ZHANG Yu-xin, LI Yong-gang, SHI Ming-qian, GUO Li-bing, YANG Hai-min, HU Shang-cheng. A data-driven software architecture of the measured data’s real-time processing on tracking ships [J]. Computer Engineering & Science, 2021, 43(11): 1979-1985.

A software quality evaluation model

based on hesitant fuzzy set
#br#

PDF

Knowledge

Abstract

Cite this article

share this article

References ［31］

Related Articles 15

Recommended Articles

Metrics

Comments