Nothing Special   »   [go: up one dir, main page]

计算机科学 ›› 2018, Vol. 45 ›› Issue (11A): 501-504.

• 软件工程与数据库技术 • 上一篇    下一篇

基于加权类比的软件成本估算方法

赵小敏, 曹光斌, 费梦钰, 朱李楠   

  1. 浙江工业大学计算机科学与技术学院 杭州310023
  • 出版日期:2019-02-26 发布日期:2019-02-26
  • 通讯作者: 朱李楠(1982-),男,博士,讲师,主要研究方向为云制造、制造业信息化等,E-mail:zln@zjut.edu.cn
  • 作者简介:赵小敏(1976-),男,博士,副教授,CCF会员,主要研究方向为无线传感器网络、信息安全和软件成本评估,E-mail:zxm@zjut.edu.cn;曹光斌(1992-),男,硕士生,主要研究方向为软件成本评估;费梦钰(1992-),女,硕士生,主要研究方向为软件成本评估
  • 基金资助:
    本文受国家自然科学基金(61701443)资助。

Software Cost Estimation Method Based on Weighted Analogy

ZHAO Xiao-min, CAO Guang-bin, FEI Meng-yu, ZHU Li-nan   

  1. College of Computer Science and Technology,Zhejiang University of Technology,Hangzhou 310023,China
  • Online:2019-02-26 Published:2019-02-26

摘要: 软件成本估算是软件项目开发周期、管理决策和软件项目质量中最重要的问题之一。针对软件研发成本估算在软件行业中普遍存在不准确、难以估算的问题,提出一种基于加权类比的软件成本估算方法,将相似度距离定义为具有相关性的马氏距离,通过优化的粒子群算法优化后得到权值,并用类比法估算软件成本。实验结果表明,该方法具有比非加权类比、神经网络等非计算模型方法更高的精确度。实际案例测试表明,该方法在软件开发初期基于需求分析的软件成本估算比专家估算有更精确的评估结果。

关键词: 加权类比, 粒子群优优化, 马氏距离, 软件成本估算

Abstract: Software cost estimation is one of the most important issues in the cycle of development,management decision,and in the quality of software project.Aiming at the common problems of software cost estimation in the software industry,such as inaccuracy of cost estimation and estimation difficulty,this paper presented a weighted analogy-based software cost estimation method.In this method,the similarity distance is defined as the Mahalanobis distance with correlation,and the weight is obtained by particle swarm optimization.The software cost is estimated by analogy method.The result shows that this method has high accuracy compared with non-computational based model methods such as non-weighted analogy and neural networks.At the same time,the actual cases show that this method is more accurate than expert estimation in software cost estimation based on demand analysis at the early stage of software development.

Key words: Mahalanobis distance, Particle swarm optimization, Software cost estimation, Weighted analogy

中图分类号: 

  • TP391
[1]DAVE V S,DUTTA K.Neural network based models for software effort estimation:a review[J].Artificial Intelligence Review,2014,42(2):295-307.
[2]SARNO R,SIDABUTAR J,SARWOSRI.Comparison of diffe-rent Neural Network architectures for software cost estimation[C]∥International Conference on Computer,Control,Informa-tics and ITS Applications.IEEE,2016:68-73.
[3]WANI Z H,QUADRI S M K.Artificial Bee Colony-Trained Functional Link Artificial Neural Network Model for Software Cost Estimation[M]∥Proceedings of Fifth International Conference on Soft Computing for Problem Solving.2016:729-741.
[4]BENALA T R,CHINNABABU K,MALL R,et al.A particle swarm optimized functional link artificial neural network (PSO-FLANN) in software cost estimation[C]∥Proceedings of the International Conference on Frontiers of Intelligent Computing:Theory and Applications (FICTA) Advances in Intelligent Systems and Computing.Springer Berlin Heidelberg,2013:59-66.
[5]BAJTA M E,IDRI A,FERNÁNDEZ-ALEMÁN J L,et al.Software cost estimation for global software development a syste-matic map and review study[C]∥International Conference on Evaluation of Novel Approaches To Software Engineering.IEEE,2015:197-206.
[6]杨抒,王业,乌尔柯西,等.基于C&S-PSO的软件成本估算类比法特征权重优化[J].计算机系统应用,2015,24(7):99-103.
[7]PAPATHEOCHAROUS E,ANDREOU A S.On the Problem of Attribute Selection for Software Cost Estimation:Input Backward Elimination Using Artificial Neural Networks[C]∥Artificial Intelligence Applications and Innovations,Ifip Wg 12.5 International Conference.Springer Berlin Heidelberg,2010:287-294.
[8]吴登生,李建平,蔡晨.软件成本估算的粒子群算法类比模型及自助法推断[J].管理科学,2010,23(3):113-120.
[9]DIZAJI Z A,KHALILPOUR K.Particle Swarm Optimization and Chaos Theory Based Approach for Software Cost Estimation[J].International Journal of Academic Research,2014,6(3):130.
[10]王振丽.基于加权MP马氏距离的GS方法研究[D].南京:南京理工大学,2016.
[11]KENNEDY J,EBERHART R.Particle swarm optimization[C]∥IEEE International Conference on Neural Networks.IEEE,1995:1942-1948.
[12]牛利勇,张帝,王晓峰,等.基于自适应变异粒子群算法的电动出租车充电引导[J].电网技术,2015,39(1):63-68.
[13]DESHARNAIS J M.Analyse statistique de la productivitie des projets informatique a partie de la technique des point des fonction[D].Quebec:University of Montreal,1989.
[14]中华人民共和国工业和信息化部.软件研发成本度量规范:SJ/T11463-2013[S].2013.
[1] 林毅, 吉鸿江, 韩佳佳, 张德平.
一种基于马氏距离的系统故障诊断方法
System Fault Diagnosis Method Based on Mahalanobis Distance Metric
计算机科学, 2020, 47(11A): 57-63. https://doi.org/10.11896/jsjkx.190900174
[2] 张谢锴,丁世飞.
基于马氏距离的孪生多分类支持向量机
Mahalanobis Distance-based Twin Multi-class Classification Support Vector Machine
计算机科学, 2016, 43(3): 49-53. https://doi.org/10.11896/j.issn.1002-137X.2016.03.009
[3] 王昱杰,赵培海,王咪咪.
基于键盘行为进行用户识别的方法与应用
Method of User Identification Based on Keystroke Behavior and its Application
计算机科学, 2015, 42(11): 203-207. https://doi.org/10.11896/j.issn.1002-137X.2015.11.042
[4] 刘解放,赵斌,周宁.
基于有效载荷的多级实时入侵检测系统框架
Multilevel Real-time Payload-based Intrusion Detection System Framework
计算机科学, 2014, 41(4): 126-133.
[5] 凡少强,王国胤,李美争.
改进的知识特征驱动的任务分解模型
Improved Knowledge Characteristic-driven Task Decomposition Model
计算机科学, 2014, 41(3): 91-95.
[6] 秦玉平,王祎,伦淑娴,王秀坤.
基于超椭球支持向量机的兼类文本分类算法
Multi-label Text Classification Algorithm Based on Hyper Ellipsoidal SVM
计算机科学, 2013, 40(Z11): 98-100.
[7] 马青,徐如志,田茂圣.
非基于软件复用的成本估算模型的复用改造模型及模型系数修正策略
Non-reuse-based Software Cost Estimate Model's Reuse Transformation and Model Coefficients Modification Strategies
计算机科学, 2012, 39(9): 155-156.
[8] 丁昕苗,郭文,徐常胜.
基于黎曼流型度量的人工鱼群算法视觉跟踪
Visual Tracking of Artificial Fish Swarm Algorithm Based on Riemannian Manifold Metric
计算机科学, 2012, 39(5): 266-270.
[9] 陈欢,黄德才.
基于广义马氏距离的缺损数据补值算法
Missing Data Imputation Based on Generalized Mahalanobis Distance
计算机科学, 2011, 38(5): 149-153.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!