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研究生:蘇志玄
研究生(外文):Jyh-ShyuanSu
論文名稱:專案開發初期軟體成本估算之研究
論文名稱(外文):Software Effort Estimation at Early Stage of Project Development
指導教授:朱治平朱治平引用關係
指導教授(外文):Chih-Ping Chu
學位類別:碩士
校院名稱:國立成功大學
系所名稱:資訊工程學系碩博士班
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2012
畢業學年度:100
語文別:英文
論文頁數:56
中文關鍵詞:早期軟體成本預估功能點回歸分析指數成長線性成長
外文關鍵詞:early software cost estimatesfunction pointsregression analysisexponential growthlinear growth
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軟體成本預估的精確性對於專案的成功與失敗至關重要,精確的成本預估,可使專案管理人更有效的分配資源與人力。軟體成本的預估是連續性的,從軟體開發早期到軟體開發後期都存在著,然而早期的預估精確性較低,越到後期會越精確,主要是因為軟體的需求、設計、實作會越來越清楚。早期的軟體成本預估模型甚少,所以本論文提出改造功能點(function point)模型[3]來達到早期預估的方法,功能點模型是目前國內外常用的軟體規模評估的方法,它被使用的時機是在系統設計完成的階段[3]。本論文改造功能點模型預估方式,只使用功能點元件(function point component)的數量來預估軟體成本,藉此讓軟體成本預估在系統設計初期就可以預估。功能點元件可在系統分析完成之後,進行功能點元件分析得到,最後用國際軟體基準標準組織(ISBSG)所提供的專案資料做檢驗,在實驗之前先依專案屬性分為數個類別進行實驗。我們提出三種方法EFP 1 、EFP 2、 EFP 3來計算功能點的總和,再以回歸分析的方式建構成本預估模型。EFP 1是以線性成長來計算功能點的總和,EFP 2是EFP 1的改良,主要是尋找最佳的線性係數,EFP 3是以指數成長來計算功能點的總和。結果顯示EFP 3在五種資料類別下都預估較精確。另一方面當資料的分類更嚴謹,所預估出來的模型也更加精確。最後與另外一篇改良功能點的文章對照[7],本論文提出的方法可以在系統設計早期進行預估,平均精確度約只下降9.03%,而且有些類別的預估結果比改良功能點[7]還要好。
The accuracy of software cost estimates for project success is essential. Accurate cost estimation allows project managers allocate resources and manpower more efficiently. Software cost estimation is a continue activity from the beginning at software development to the end. However, estimation in early software development phase has lower accuracy than later, because the software requirements, design specification, and coding is more clear in later development phase.
Early software cost estimation is less frequently, so in this thesis we transform the function point model [3] to achieve the early estimate of software cost. Function Point (FP) [3] is commonly used to measure software size. It is generally used when system design is completed [7]. We transform the function point model by estimating with the number of function component, so we can use new FP model at the beginning of software design.
Finally, we validate with the project data provided by International Software Benchmarking Standards Group (ISBSG). Before the experiment, we classify the project data according to their attributes. We proposed three methods EFP 1, EFP 2, EFP 3 to obtain the sum of function points respectively. Then, we use regression analysis to construct the cost estimation model. EFP 1 is a linear growth function to calculate the sum of function points. EFP 2 improves EFP 1 by finding the best linear coefficient. EFP 3 is an exponential growth function to calculate the sum of function points.
The results show that EFP 3 are all best in five dataset. On the other hand, when the data classification is more stringent, the cost estimation model is more accurate.
We compare the results with a paper [7] which proposed a method to improve original FP model. Experimantal results showed that our method can be used at the beginning of system design, and the average accuracy only decreased by 9.03% when compared with the method of [7] estimated at the late stage. However, we get the better estimation results in some dataset when compared with [7].

摘要 iii
Abstract iv
致謝 vi
Contents vii
List of Table ix
List of Figure xi
Table of Symbols xii
Chapter 1. Introduction 1
Chapter 2. Background and related work 3
2.1 Function Point 3
2.2 Function Point extensions 9
Chapter 3.The EFP construction model process 16
3.1 The EFP 1 construction model process 22
3.2 The EFP 2 construction model process 25
3.3 The EFP 3 construction model process 27
Chapter 4. Experimental methodology 29
4.1 The dataset 29
4.2 Statistical Regression Analysis 38
Chapter 5. Experimental Result and discussion 41
5.1 Experimental Result 41
5.2 Discussion 49
Chapter 6. Conclusions and future work 50
6.1 Conclusions 50
6.2 Future work 51
References 52




[1] L.H. Putnam, W. Myers, 1992. Measures of Excellence, Prentice Hall, Upper Saddle River, NJ.

[2] COSMIC - Common Software Measurement International Consortium 2007. The COSMIC Functional Size Measurement Method – version 3.0 Measurement
Manual (The COSMIC Implementation Guide for ISO/IEC 19761: 2003), September 2007.

[3] A.J. Albrecht, 1979. Measuring application development productivity. In: Proceedings of the Joint SHARE/GUIDE/IBM Application Development Symposium, Monterey, CA, pp. 83–92,

[4] G. Costagliola, F. Ferrucci, G. Tortora, G. Vitiello, 2005. Class point: an approach for the size estimation of object-oriented systems. IEEE Transactions on Software Engineering 31 (1), 52–74.

[5] C. Jones, 1985. Programming Productivity. McGraw-Hill, New York.

[6] Dr. Stephen Nemecek and Dr. Jesse Bemley, 1993. “A Model for Estimating the Cost of AI Software Development: What to do if there are no Lines of Code? Developing and Managing Intelligent System Projects, IEEE International Conference on, pp. 2-9.
[7] W. Xia, L. F. Capretz, D. Ho, F. Ahmed. 2008. “A new calibration for Function Point complexity weights. Information and Software Technology, vol. 50, pp.670-683.

[8] R. Meli, L. Santillo, 1999. “Function Point Estimation Methods: a Comparative Overview ,FESMA 99, October 6-8, Amsterdam.

[9] O. S. Lima, P. F. M. Farias and A. D. Belchior, 2003. “Fuzzy Modeling for
Function Points Analysis, Software Quality Journal, vol. 11, pp. 149-166,.

[10] A. Abran, M. Maya, J.M. Desharnais, D. St-Pierre, 1997. Adapting function points to real-time software. American Programmer 10 (11), 32–43.

[11] S.A. Whitmire, 1996. 3D function points: applications for object-oriented software. In: Proceedings of the Applications in Software Measurements Conference, San Diego, CA.

[12] A.F. Minkiewicz, 1997. Measuring object oriented software with predictive object points. In: Proceedings of the Applications in Software Measurements Conference (ASM‘97), Atlanta, GA.

[13] G. Antoniol, C. Lokan, G. Caldiera, R. Fiutem, 1999. Function point-like measure for object-oriented software. Empirical Software Engineering 4 (3), 263–287.
[14] D. Cleary, 2000. Web-based development and functional size measurement. In: Proceedings of the IFPUG Annual Conference, San Diego, CA.

[15] Cost Xpert Group, 2002. Estimating Internet Development. Cost Xpert Group, Inc.

[16] UKSMA, 1998. MKII Function Point Analysis Counting Practices Manual, Version 1.3.1. United Kingdom Software Metrics Association, Edenbridge, Kent, United Kingdom.

[17]http://instructional1.calstatela.edu/prosent/BUS20514A/Costing-about_function_point_analysis.htm#WhatareMkII

[18] NESMA, http://www.nesma.nl/section/nesma/

[19] Total Metrics, http://www.totalmetrics.com/function-points-groups/finnish-software-measurement-association-fisma

[20] Finnish Software Measurement Association (FISMA), http://www.fisma.fi/

[21] A. Abran, J.M. Desharnais, S. Oligny, D. St-Pierre, C. Symons, 1999. COSMIC-FFP Measurement Manual, Version 2.0. Software Engineering Management Research Laboratory, University of Quebec, Montreal, Canada

[22] Ya-fang Fu, Xiao-dong Liu, Ren-nong Yang, Yi-lin Du, Yan-jie Li, 2010. A software size estimation method based on improved FPA, Second WRI World Congress on Software Engineering.

[23] ISBSG Glossary of Terms V5.10.2, ISBSG

[24] ISBSG, http://www.isbsg.org/

[25] Guidelines for use of the ISBSG data, ISBSG, 2009

[26] Field Descriptions - Data Release 11, ISBSG, 2009

[27] L.C. Briand, J. Wust, 2001. Modeling development effort in object-oriented systems using design properties . IEEE Transactions on Software Engineering 27 (11), 963–986.

[28] Z. Zia, A. Rashid, K. uz Zaman, 2011. Software cost estimation for component-based fourth-generation-language software applications, Software IET, 103-110

[29] D.R. Jeffery, G.C. Low, M. Barnes, 1993. A comparison of function point counting techniques. IEEE Transactions on Software Engineering 19 (5), 529–532.

[30] C.J. Lokan, 2000. An empirical analysis of function point adjustment factors. Information & Software Technology 42 (9), 649–659.

[31] B. Boehm, E. Horowitz, R. Madachy, D. Reifer, B. Clark, B. Steece, A. Brown, S. Chulani, C. Abts, 2000. Software Cost Estimation with COCOMO II, Prentice Hall, Upper Saddle River, NJ.

[32] L. Angelis, I. Stamelos, M. Morisio, 2001. Building A Software Cost Estimation Model Based On Categorical Data, metrics, pp.4, Seventh International Software Metrics Symposium (METRICS'01).

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