基于神经网络的软件质量评价综述

Abstract

Abstract: Software quality is a significant factor throughout the software life cycle.With the rapid development of software industry,users have higher and higher requirements on software quality.Therefore,how to establish a more accurate software quality evaluation model has become an hot topic in the field of software quality research.The software quality evaluation model aims to find the relationship between the characteristics of various aspects of software and software quality from historical data.And neural network becomes one of the most appropriate methods to establish such a complex relationship because of its powerful learning ability and non-linear mapping ability.Using the method of systematic literature review,this paper summarized 50 domestic and foreign literatures on software quality evaluation using neural network method from 1994 to 2018 from the aspects of inputs,evaluation targets,modeling methods and the training of neural network.Some rules,unsolved problems and possible research directions of using neural network method to evaluate software quality were found.

Key words: Neural network, Quality evaluation, Software quality, Systematic literature review

CLC Number:

TP311.5

ZONG Peng-yang, WANG Yi-chen. Software Quality Evaluation Based on Neural Network:A Systematic Literature Review[J].Computer Science, 2019, 46(11A): 507-516.

References

[1]崔天意,刘庆峰,张芝龙.电子装备软件质量评估模型分析[J].计算机与数字工程,2010,38(1):44-47.
[2]马慧敏,宋雨,许正伟.广义回归神经网络在软件质量预测中的应用[J].计算机工程与应用,2004(29):217-219.
[3]MAJUMDER K.系统综述写作指引[EB/OL].https://www.editage.cn/insights/1159.html,2015
[4]BRERETON P,KITCHENHAM B A,BUDGEN D,et al.Lessons from applying the systematic literature review process within the software engineering domain[J].Journal of Systems and Software,2007,80(4):571-583.
[5]KITCHENHAM B.Procedures for Undertaking Systematic Reviews[C]∥Joint Technical Report,Computer Science Department.2004.
[6]张家海,孙枫,郝燕玲.神经网络用于组合导航系统软件质量的评估[J].哈尔滨理工大学学报,2001(3):34-37.
[7]赵一鸣.基于ISO质量模型的软件质量评价方法[J].计算机工程,2002(5):78-79,82.
[8]杨根兴,高大启,宋国新.基于神经网络的软件质量综合评价方法[J].华东理工大学学报,2004(3):292-295.
[9]廖锦舜,何锫.基于模糊神经网络的软件质量评价方法[J].计算机技术与发展,2006(2):194-196.
[10]杨健,朱继梅,袁正刚.基于BP网络软件质量度量模型[J].微计算机信息,2006(24):262-264.
[11]关帅,孙雅囡,朱清浩.一种潜艇作战软件质量评价的新方法[J].中国舰船研究,2008,3(5):54-56.
[12]楼文高,姜丽,孟祥辉.计算机软件质量综合评判的人工神经网络模型[J].上海理工大学学报,2008(5):479-482.
[13]王李进,吴保国,郑德祥.基于人工神经网络的软件质量评价[J].计算机应用与软件,2008,25(12):133-134,150.
[14]宫丽娜,马怀志.广义动态模糊神经网络对软件质量的预测[J].微型电脑应用,2012,28(6):32-35.
[15]宫丽娜,马怀志.粒子群算法优化的BP网络预测软件质量[J].计算机工程与应用,2014,50(23):65-68.
[16]窦立阳,刘建周.基于BP人工神经网络的软件质量评估[J].计算机与数字工程,2014,42(4):644-646.
[17]李克文,张郁,马竟峰,等.基于模糊三角数模糊神经网络的软件质量评价方法[J].计算机工程与科学,2014,36(7):1301-1306.
[18]郑鹏.基于LM-BP神经网络的软件质量综合评价[J].山东理工大学学报(自然科学版),2016,30(3):74-78.
[19]KHOSHGOFTAAR T M,LANNING D L,PANDYA A S.Comparative study of pattern recognition techniques for quality evaluation of telecommunications software[J].IEEE Journal on Selected Areas in Communications,1994,12(2):279-291.
[20]KHOSHGOFTAAR T M,SZABO R M.Improving neural network predictions of software quality using principal components analysis[C]∥IEEE International Conference on Neural Networks,1994.IEEE World Congress on Computational Intelligence.IEEE,1994:3295-3300.
[21]KHOSHGOFTAAR T M,SZABO R M,GUASTI P J.Exploring the behavior of neural network software quality models[J].Software Engineering Journal,1995,10(3):89-96.
[22]KHOSHGOFTAAR T M,ALLEN E B,HUDEPOHL J P,et al.Application of Neural Networks to Software Quality Mo-deling of a Very Large Telecommunications System[J].IEEE Transactions on Neural Networks,1997,8(4):902-909.
[23]LANUBILE F,VISAGGIO G.Evaluating predictive qualitymodels derived from software measures:Lessons learned[J].Journal of Systems & Software,1997,38(3):225-234.
[24]BAISCH E,EBERT C.On a Neural-Fuzzy Technique with GA-Optimization for Software Quality Models[M]∥Software Metrics,1997.
[25]KUMAR R,RAI S,TRAHAN J L.Neural-network techniques for software-quality evaluation[C]∥Reliability and Maintainability Symposium,1998.IEEE,1998:155-161.
[26]PEDRYCZ W,PETERS J F,RAMANNA S.Software qualitymeasurement:concepts and fuzzy neural relational model[C]∥IEEE International Conference on Fuzzy Systems Proceedings,1998.IEEE World Congress on Computational Intelligence.IEEE,1998:1026-1031.
[27]PEDRYCZ W,HAN L,PETERS J F,et al.Calibration of software quality:Fuzzy neural and rough neural computing approaches[J].Neurocomputing,2001,36(1):149-170.
[28]XU Z.Software Quality Prediction for High-Assurance Network Telecommunications Systems[J].Computer Journal,2001,44(6):557-568.
[29]RAMANNA S,PETERS J F,AHN T C.Software QualityKnowledge Discovery:A Rough Set Approach[C]∥International Computer Software & Applications Conference on Prolonging Software Life:Development & Redevelopment.IEEE Computer Society,2002.
[30]PIZZI N J,SUMMERS A R,PEDRYCZ W.Software quality prediction using median-adjusted class labels[C]∥Neural Networks,2002.IJCNN’02.Proceedings of the 2002 International Joint Conference.IEEE,2002.
[31]VALSA B.A Neural Network Model for Assessing SoftwareQuality for Mission Critical Applications[C]∥International Astronautical Congress of the International Astronautical Federation.2003.
[32]THWIN M M T,QUAH T S.Application of neural networks for software quality prediction using object-oriented metrics[J].The Journal of Systems & Software,2003,76(2):147-156.
[33]TAGHI K,NAEEM S.Fault Prediction Modeling for Software Quality Estimation:Comparing Commonly Used Techniques[J].Empirical Software Engineering,2003,8(3):255-283.
[34]WANG Q,YU B,ZHU J.Extract Rules from Software Quality Prediction Model Based on Neural Network[C]∥IEEE International Conference on TOOLS with Artificial Intelligence.IEEE Computer Society,2004:191-195.
[35]KANMANI S,UTHARIARAJ V R,SANKARANARAY-ANAN V,et al.Object-oriented software quality prediction using general regression neural networks[J].Acm Sigsoft Software Engineering Notes,2004,29(5):1-6.
[36]WANG Q,YU B,YU B.Combining classifiers in software quality prediction:a neural network approach[C]∥International Conference on Advances in Neural Networks.Springer-Verlag,2005:921-926.
[37]YANG B,YAO L,HUANG H Z.Early Software Quality Prediction Based on a Fuzzy Neural Network Model[C]∥International Conference on Natural Computation.IEEE,2007:760-764.
[38]PENG W,YAO L,MIAO Q.An Approach of Software Quality Prediction Based on Relationship Analysis and Prediction Model[C]∥The Proceedings of 2009,International Conference on Reliability,Maintainability and Safety.2009:713-717.
[39]JIN C,JIN S W,YE J M,et al.Quality prediction model of object-oriented software system using computational intelligence[C]∥International Conference on Power Electronics and Intelligent Transportation System.IEEE,2009:120-123.
[40]POMOROVA O,HOVORUSHCHENKO T.Research of artificial neural network's component of software quality evaluation and prediction method[C]∥IEEE International Conference on Intelligent Data Acquisition & Advanced Computing Systems.IEEE,2011.
[41]ZHONG C,HU Q,YANG F,et al.Software quality prediction method with hybrid applying principal components analysis and wavelet neural network and genetic algorithm[J].International Journal of Digital Content Technology and its Applications,2011,5(3):225-234.
[42]RATANOTHAYANON S,SRIVISAL C,VANICHAYOBO-NAND S,et al.Comparative Classifiers for Software Quality Assessment[J].International Journal of Engineering and Technology,2012,4(4):404-408.
[43]MIAO X,LU Y,DAI Y.Method of Military Software QualityEvaluation Based on Multi-Agent Fuzzy Neural Network[C]∥International Conference on Computer Science & Service System.IEEE,2012.
[44]KAUR A,SINGH A,SINGH B.Design of Hybrid Neural Network Model for Quality Evaluation of Object Oriented Software Modules[J].International Journal of Engineering Research and Development,2012,2(5):78-82.
[45]POMOROVA O,HOVORUSHCHENKO K.Artificial neuralnetwork for software quality evaluation based on the metric analysis[C]∥East-West Design & Test Symposium.IEEE,2013.
[46]KUMAR G,BHATIA P K.Neuro-Fuzzy Model to Estimate & Optimize Quality and Performance of Component Based Software Engineering[J].Acm Sigsoft Software Engineering Notes,2015,40(2):1-6.
[47]SURESH Y.Software quality assurance for object-oriented systems using meta-heuristic search techniques[C]∥International Conference on Applied & Theoretical Computing & Communication Technology.IEEE,2016.
[48]SHEORAN K,TOMAR P,MISHRA R.Software Quality Prediction Model with the Aid of Advanced Neural Network with HCS[J].Procedia Computer Science,2016,92:418-424.
[49]LIU Y,CHANG C,HAN P.A software development projectquality analysis model based on HMM-FNN[C]∥International Conference on Software Engineering and Service Science,2017.IEEE,2017.
[50]WANG A,GUO L,CHEN Y,et al.Comprehensive Evaluation of Software Quality Based on LM-BP Neural Network[C]∥International Conference on Dependable Systems and Their Applications.IEEE,2017.
[51]SAHAR S,QAMAR U,AYAZ S.Multilayer Neural Networkand Fuzzy Logic Based Software Quality Prediction[J].International Journal of Information,Control and Computer Sciences,2017,11(9):1024-1028.
[52]TOMAR P,MISHRA R,SHEORAN K.Prediction of quality using ANN based on Teaching-Learning Optimization in component-based software systems[J].Software Practice and Experience,2018,48(3):896-910.
[53]BANSAL M,AGRAWAL C P.Jaya Algorithm and ArtificialNeural Network Based Approach for Object-Oriented Software Quality Analysis[J].International Journal of Intelligent Engineering and Systems,2018,11(4):275-282.

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed

Comments

Recommended 0

No Suggested Reading articles found!

Software Quality Evaluation Based on Neural Network:A Systematic Literature Review

PDF (PC)

Abstract

Cite this article

share this article

References

Related Articles 15

Metrics

Comments

Recommended 0

[1]	ZHOU Fang-quan, CHENG Wei-qing. Sequence Recommendation Based on Global Enhanced Graph Neural Network [J]. Computer Science, 2022, 49(9): 55-63.
[2]	ZHOU Le-yuan, ZHANG Jian-hua, YUAN Tian-tian, CHEN Sheng-yong. Sequence-to-Sequence Chinese Continuous Sign Language Recognition and Translation with Multi- layer Attention Mechanism Fusion [J]. Computer Science, 2022, 49(9): 155-161.
[3]	NING Han-yang, MA Miao, YANG Bo, LIU Shi-chang. Research Progress and Analysis on Intelligent Cryptology [J]. Computer Science, 2022, 49(9): 288-296.
[4]	HAO Zhi-rong, CHEN Long, HUANG Jia-cheng. Class Discriminative Universal Adversarial Attack for Text Classification [J]. Computer Science, 2022, 49(8): 323-329.
[5]	WANG Run-an, ZOU Zhao-nian. Query Performance Prediction Based on Physical Operation-level Models [J]. Computer Science, 2022, 49(8): 49-55.
[6]	CHEN Yong-quan, JIANG Ying. Analysis Method of APP User Behavior Based on Convolutional Neural Network [J]. Computer Science, 2022, 49(8): 78-85.
[7]	ZHU Cheng-zhang, HUANG Jia-er, XIAO Ya-long, WANG Han, ZOU Bei-ji. Deep Hash Retrieval Algorithm for Medical Images Based on Attention Mechanism [J]. Computer Science, 2022, 49(8): 113-119.
[8]	YAN Jia-dan, JIA Cai-yan. Text Classification Method Based on Information Fusion of Dual-graph Neural Network [J]. Computer Science, 2022, 49(8): 230-236.
[9]	QI Xiu-xiu, WANG Jia-hao, LI Wen-xiong, ZHOU Fan. Fusion Algorithm for Matrix Completion Prediction Based on Probabilistic Meta-learning [J]. Computer Science, 2022, 49(7): 18-24.
[10]	YANG Bing-xin, GUO Yan-rong, HAO Shi-jie, Hong Ri-chang. Application of Graph Neural Network Based on Data Augmentation and Model Ensemble in Depression Recognition [J]. Computer Science, 2022, 49(7): 57-63.
[11]	ZHANG Ying-tao, ZHANG Jie, ZHANG Rui, ZHANG Wen-qiang. Photorealistic Style Transfer Guided by Global Information [J]. Computer Science, 2022, 49(7): 100-105.
[12]	DAI Zhao-xia, LI Jin-xin, ZHANG Xiang-dong, XU Xu, MEI Lin, ZHANG Liang. Super-resolution Reconstruction of MRI Based on DNGAN [J]. Computer Science, 2022, 49(7): 113-119.
[13]	LIU Yue-hong, NIU Shao-hua, SHEN Xian-hao. Virtual Reality Video Intraframe Prediction Coding Based on Convolutional Neural Network [J]. Computer Science, 2022, 49(7): 127-131.
[14]	XU Ming-ke, ZHANG Fan. Head Fusion:A Method to Improve Accuracy and Robustness of Speech Emotion Recognition [J]. Computer Science, 2022, 49(7): 132-141.
[15]	PENG Shuang, WU Jiang-jiang, CHEN Hao, DU Chun, LI Jun. Satellite Onboard Observation Task Planning Based on Attention Neural Network [J]. Computer Science, 2022, 49(7): 242-247.