臺灣博碩士論文加值系統

為了維持競爭力及改善軟體流程品質，軟體公司紛紛導入軟體流程管理方
法，其中CMMI 則是國內資策會推動的一項軟體流程管理方法。而CMMI 的評
鑑流程則是依據質性工具，多依主任稽核員的主觀判斷。
本研究提出一模糊量化整合模式，結合量化軟體指標集(QSMS)、語意變數
及一新模糊數排序方法。此模式以量化方法幫助公司有效率及快速地衡量及了解
本身的現況，並與標竿公司作基準比較，藉此方式與通過CMMI Level 2 公司作
優缺點的比較。此外，本研究以JAVA 開發CMMI 評鑑系統(CMMI ASS)協助軟
另一方面，一新模糊數排序的方法用來排序公司的績效表現值。為了要驗
證所提出的方法，本研究以大量例子作實驗，並與其它方法作比較。最後，並將
此模糊數排序方法應用在實際的CMMI Level 2 的公司績效作排序。

In Capability Maturity Model Integrated (CMMI), Lead Appraiser (LA) evaluates the processes of one company according to qualitative sources such as Instrument, Interview and Document through direct Artifacts, indirect artifacts and Affirmation. Due to the subjective measurement and non-quantitative expression of LAs, this paper proposes a Fuzzy Quantitative Integrated Metric Model (FQIMM) that combines Quantitative Software Metrics Set (QSMS), linguistic variables, interval of confidence and a new fuzzy number ranking method. It can help companies to evaluate on quantitative approach and then know itself status more quickly and effectively. Moreover, CMMI Appraisal Support System (CMMI-ASS) is developed to help self-assessment companies to accomplish the appraisal process. In the other hand, a new fuzzy number ranking method is proposed to rank the companies. In order to verify the proposed method, it is compared with other ranking methods. Furthermore, it is applied to the ranking order of the performance of CMMI level 2 in practical.

摘要..........................................................................i
ABSTRACT ....................................................................ii
誌謝........................................................................iii
Contents.................................................................... iv
Table.........................................................................v
Figur........................................................................vi
1.Introduction ...............................................................1
2. Preliminaries..............................................................3
2.1 Capability Maturity Model Integrated (CMMI) ............................. 3
2.1.1 The evolution of CMMI ................................................. 3
2.1.2 The comparison of CMMI and ISO standards .............................. 4
2.2 Fuzzy Set Theory......................................................... 6
2.2.1 Arithmetic operations of fuzzy numbers ................................ 6
2.2.2 Linguistic Variable.................................................... 7
3. A new fuzzy number ranking method based on adaptive 2-dimensions dominance.7
4. A new CMMI appraisal model, FQIMM ........................................12
5. FQIMM applied in CMMI Level 2 appraisal ..................................14
5.1 Practical example..................................................................... 14
5.2 Comparisons with other methods ......................................... 27
5.2.1 Simple Additive Weighting method (SAW) ............................... 27
5.2.2 Lee and Li’s approach................................................ 28
6. CMMI Appraisal Support System ............................................29
7. Future work ..............................................................34
8. Conclusions ..............................................................35
Reference....................................................................37
Appendix A Comparison examples...............................................39
Appendix B Expert and DM Questionnaire ......................................43

[1] APQC (American Productivity & Quality Center), 1993, "The benchmarking
management guide", Portland, Oregon: Productivity Press.
[2] Baas, S.M., and Kwakernaak, H., 1977, “Rating and ranking of multiple-aspect alternatives using fuzzy sets”, Automatica, vol. 13, p.p.47-58.
[3] Baldwin, J.F., and Guild, N.C., 1979, “Comparison of fuzzy sets on the same
decision space”, Fuzzy Sets and Systems , vol. 2, p.p. 213-233.
[4] Bortolan G., Degani R., 1985, “A review of some methods for ranking fuzzy
subsets”, Fuzzy Sets and Systems, vol.15, pp. 1-19.
[5] Cheng, C. H. 1998, “A new approach for ranking fuzzy numbers by distance
method,” Fuzzy Sets and Systems, Vol. 95, No. 3, pp. 307-317.
[6] Carnegie Mellon Software Engineering Institute, 2001, “Appraisal Requirements for CMMI, Version 1.1”.
[7] Carnegie Mellon Software Engineering Institute, 2001, “Standard CMMISM
Appraisal Method for Process Improvement (SCAMPISM), Version 1.1: Method
Definition Document”.
[8] Carnegie Mellon Software Engineering Institute, 2002, “Capability Maturity
Model Integration v1.1”, CMMI–SW/SE, Continuous representation.
[9] Chen, C.Y. and Huang, S. J., 2003, Using Quantitative Software Metrics to Support CMMI Deployment and Appraisal, Software Industry Service Newsletter, Vol.54,pp.46-57.
[10] Chen, L. H. and Lu, H. W., 2001, “An Approximate Approach for Ranking Fuzzy Numbers Based on Left and Right Dominance” Computers and Mathematics with
Applications, vol. 41, p.p. 1589-1602.
[11] Chen, S. J. and Hwang, C. L., 1992, “Fuzzy multiple attribute decision making methods and applications”, Lecture Notes in Economics and Mathematical
Systems, Springer, New York.
[12] Grady, R. B., 1987, “Measuring and Managing Software Maintenance”. IEEE
Software, Vol. 4 (5), pp. 35-45.
[13] Grady, R. B., 1990, “Work-Product Analysis: The Philosopher''s Stone of Software”. IEEE Software, pp. 26-34.
[14] Hung, C. K., 2003, “Why Need? Capability Maturity Model Integration (CMMI)”, SPIN-Taiwan Conference, Kaohsiung, August 1.
[15] Hwang, C. L. and Yoon, K., 1981, Multiple Attribute Decision Making- Methodsand Appliacations, A State-of-the-Art Survey, Springer-Verlag, New York.
[16] Kaufmann A. and Gupta M.M., 1991, Introduction to Fuzzy Arithmetic Theory and Applications, Van Norstrand Reinhold, New York,.
[17] Keen, P.G.W. and Scott Morton, M. S., 1978, Decision Support Systems, An
Organizational Perspective.Reading, Addison –Wesley, MA.
[18] Kerre E., 1982, “The use of fuzzy set theory in electrocardiological diagnostics”, Approximate Reasoning in Decision Analysis, pp. 277-282, North-Holland, Amsterdam.
[19] Lee, E.S. and Li, R.J., 1988, “Comparison of fuzzy numbers based on the probability measure of fuzzy events”, Computers Math. Applic. , Vol.15 (10),
p.p.887-896.
[20] Li, E. Y., Chen, H.G. and Lee, T.S., 2003, “Software process management of top companies in Taiwan: a comparative study”, Total Quality Management, vol. 13, pp. 701- 713.
[21] Li, S., Davies, B., Edwards, J. and et al., 2002, “Integrating group Delphi, fuzzy logic systems for marketing strategy development: hybridisation and its effectiveness”. Marketing Intelligence & Planning, vol.20, pp.273-284.
[22] Miller G.A., 1956, “The magical number seven or minus two: some limits on our capacity of processing information”, Psychol., Rev. 63 pp.81-97.
[23] Ngo, D. C. L.and Law, B. L., 2003. “An expert screen design and evaluation
assistant that uses knowledge-based backtracking”. Information and Software Technology. Vol. 45, pp.293-304.
[24] Noushin A., 2003, “The impact of software process improvement on quality: in theory and practice”, Information and Management, vol.40, pp. 677-690.
[25] Paulk, M., et al., 1991, “Capability maturity model for software, Technical Report CMU/SEI-91-TR-024”, Software Engineering Institute, Carnegie Mellon University, Pittsburgh, PA 15213.
[26] Paulk, M., et al., 1993, “The capability maturity model for software, version 1.1, Technical ReportCMU/SEI-93-TR-024”, Software Engineering Institute, Carnegie Mellon University, Pittsburgh, PA 15213.
[27] Schultz ,D. J., 2000, “A comparison of five approaches to software development ”, NASA Standards Research Paper 012100
[28] Scott Morton, M.S., 1971, Management Decision System：Computer Based
Support for Decision Making, Cambridge MA：Division of Research, Harvard University.
[29] Sprague, R.H. Jr. and Carlson, E.D., 1982, Building Effective Decision Support System, Prentice Hall, New Jersey.
[30] Tseng T. Y. and Klein, C.M., 1989, New algorithm for the ranking procedure in fuzzy decision making, IEEE Trans. Syst. Man Cyber., Vol.19, pp. 1289-1296.
[31] Turban, E., 1990, Decision Support and Expert Systems: Management Support
Systems (2nd Edition), Macmillan Publishing Company, New York, NY, U.S.A.
[32] Yoon, K. P. and Hwang, C.L., 1995. Multiple Attribute Decision Making: An
Introduction. Newbury Park, CA: Sage.
[33] Zadeh, L.A., 1975,“The concept of a linguistic variable and its application to approximate reasoning”, Parts 1 and 2, Information Sciences, vol.8, pp.199-249, 301-357
[34] Zadeh, L.A., 1988, “Fuzzy Logic”, IEEE Computer, Vol.21, pp.83-93.
[35] Zimmermann H. J., 1991, Fuzzy Set Theory and its Applications, 2nd ed., Kluwer Academic Publisher, London.