對於軟體專案開發階段而言，專案變更是無可避免的，並且在專案開發階段隨時有可能發生。這些專案變更皆有可能造成專案交付時程延宕、額外的預算花費甚至是專案品質的降低。而專案管理鐵三角之時程、成本與範疇為專案成功與否的關鍵因素，亦即專案準時交付，成本符合預算，完成需求功能，品質達到客戶要求，即可視為成功的專案。由於專案變更對於專案品質具有重大且關鍵的影響，特別是時程、成本與範疇三者間的變動關係，並非是單純的倆倆之間相互影響。因此，本研究旨在透過綜合性的分析，提出一個專案變更影響分析模型。同時透過此模型架構的品質規模，協助企業能從不同專案變更角度掌握軟體專案的品質。在實務應用上，本研究依據所提出之架構，設計一個透過web-based的方式來進行模型建置與專案變更影響之分析，協助企業與客戶評估專案變更所造成之專案影響與專案品質之變動。

Change of project is inevitable in the software development life cycle. When a project change occurs, all of the impact should be considered in order to achieve project success. It could delay the schedule of project, increase extra cost on the budget or decrease the quality of project caused by project change. The time, cost and scope are critical success factors in the project management. In order to maintain the quality of project, the change impact of time, cost and scope must be considered in the same time. Therefore, this research aims to propose a comprehensive impact analysis model to ensure quality scale against change. Through the three project object factors(time, cost and scope), it can assist organizations to analyze the quality of dynamic and comprehensive change impact from different software projects. This study design an online iron-triangle perspective through the web-based environment for software projects.

[1] 林信惠、黃明祥. (2002). 軟體專案管理研究架構及趨勢. 資訊管理研究. 第四卷第一期, 31-64.
[2] Babu, A. J. G., & Suresh, N. (1996). Project management with time, cost, and quality considerations. European Journal of Operational Research, 88(2), 320-327.
[3] Boehm, B. W. (1984). Software engineering economics. Software Engineering, IEEE Transactions on, (1), 4-21.
[4] Bozhikova, V., & Stoeva, M. (2010, June). An approach for software cost estimation. In Proceedings of the 11th International Conference on Computer Systems and Technologies and Workshop for PhD Students in Computing on International Conference on Computer Systems and Technologies (pp. 119-124). ACM.
[5] Chanas, S., & Zieliński, P. (2001). Critical path analysis in the network with fuzzy activity times. Fuzzy sets and systems, 122(2), 195-204.
[6] Cheikhi, L., Abran, A., & Desharnais, J. M. (2012, October). Analysis of the ISBSG software repository from the ISO 9126 view of software product quality. In IECON 2012-38th Annual Conference on IEEE Industrial Electronics Society (pp. 3086-3094). IEEE.
[7] Chen, C. Y., & Chen, P. C. (2009). A holistic approach to managing software change impact. Journal of Systems and Software, 82(12), 2051-2067.
[8] De, P., James Dunne, E., Ghosh, J. B., & Wells, C. E. (1995). The discrete time-cost tradeoff problem revisited. European Journal of Operational Research, 81(2), 225-238.
[9] Demeulemeester, E. L., Herroelen, W. S., & Elmaghraby, S. E. (1996). Optimal procedures for the discrete time/cost trade-off problem in project networks. European Journal of Operational Research, 88(1), 50-68.
[10] Dillibabu, R., & Krishnaiah, K. (2005). Cost estimation of a software product using COCOMO II. 2000 model–a case study. International Journal of Project Management, 23(4), 297-307.
[11] El-Rayes, K., & Kandil, A. (2005). Time-cost-quality trade-off analysis for highway construction. Journal of construction Engineering and Management, 131(4), 477-486.
[12] Elshaer, R. (2012). Impact of sensitivity information on the prediction of project's duration using earned schedule method. International Journal of Project Management.
[13] Feng, C. W., Liu, L., & Burns, S. A. (1997). Using genetic algorithms to solve construction time-cost trade-off problems. Journal of computing in civil engineering, 11(3), 184-189.
[14] Iranmanesh, H., Skandari, M. R., & Allahverdiloo, M. (2008). Finding Pareto optimal front for the multi-mode time, cost quality trade-off in project scheduling. In Proceedings of World Academy of Science, Engineering and Technology (Vol. 30, pp. 1307-6884).
[15] ISBSG The global and independent source of data and analysis for the IT industry (2013). http://www.isbsg.org
[16] Johnston, A. (2012). Hacker's guide to project management. Routledge.
[17] Jorgensen, M. (2004). Top-down and bottom-up expert estimation of software development effort. Information and Software Technology, 46(1), 3-16.
[18] Jorgensen, M. (2005). Practical guidelines for expert-judgment-based software effort estimation. Software, IEEE, 22(3), 57-63.
[19] Khang, D. B., & Myint, Y. M. (1999). Time, cost and quality trade-off in project management: a case study. International Journal of Project Management, 17(4), 249-256.
[20] Khatibi, V., & Jawawi, D. N. (2011). Software cost estimation methods: A review. Journal of emerging trends in computing and information sciences, 2(1), 21-29.
[21] Kitchenham, B., Pickard, L., & Pfleeger, S. L. (1995). Case studies for method and tool evaluation. Software, IEEE, 12(4), 52-62.
[22] Kohavi, R. (1995, August). A study of cross-validation and bootstrap for accuracy estimation and model selection. In IJCAI (Vol. 14, No. 2, pp. 1137-1145).
[23] Leu, S. S., Chen, A. T., & Yang, C. H. (2001). A GA-based fuzzy optimal model for construction time–cost trade-off. International Journal of Project Management, 19(1), 47-58.
[24] Lipke, W., Zwikael, O., Henderson, K., & Anbari, F. (2009). Prediction of project outcome: The application of statistical methods to earned value management and earned schedule performance indexes. International journal of project management, 27(4), 400-407.
[25] Lipow, M. (1982). Number of faults per line of code. Software Engineering, IEEE Transactions on, (4), 437-439.
[26] McCahon, C. S. (1993). Using PERT as an approximation of fuzzy project-network analysis. Engineering Management, IEEE Transactions on, 40(2), 146-153.
[27] Mendes, E., & Lokan, C. (2008). Replicating studies on cross-vs single-company effort models using the ISBSG Database. Empirical Software Engineering, 13(1), 3-37.
[28] Pendharkar, P. C., & Rodger, J. A. (2009). The relationship between software development team size and software development cost. Communications of the ACM, 52(1), 141-144.
[29] Ren, Y., Xing, T., Chai, X., Quan, Q., & Chen, X. (2010, November). Study of Using Critical Path Method to Formulate the Algorithm of Software Project Schedule Planning. In Information Management, Innovation Management and Industrial Engineering (ICIII), 2010 International Conference on (Vol. 4, pp. 126-129). IEEE.
[30] Runeson, P., & Höst, M. (2009). Guidelines for conducting and reporting case study research in software engineering. Empirical Software Engineering, 14(2), 131-164.
[31] Shankar, N. R., & Sireesha, V. (2010). Using modified Dijkstra’s algorithm for critical path method in a project network. International Journal of Computational and Applied Mathematics, 5(2), 217-225.
[32] Shepperd, M., & Schofield, C. (1997). Estimating software project effort using analogies. Software Engineering, IEEE Transactions on, 23(11), 736-743.
[33] Symons, C. R. (1988). Function point analysis: difficulties and improvements. Software Engineering, IEEE Transactions on, 14(1), 2-11.
[34] Tareghian, H. R., & Taheri, S. H. (2006). On the discrete time, cost and quality trade-off problem. Applied Mathematics and Computation, 181(2), 1305-1312.
[35] Vandevoorde, S., & Vanhoucke, M. (2006). A comparison of different project duration forecasting methods using earned value metrics. International journal of project management, 24(4), 289-302.
[36] Xia, W., Capretz, L. F., Ho, D., & Ahmed, F. (2008). A new calibration for Function Point complexity weights. Information and Software Technology, 50(7), 670-683.
[37] Zheng, D. X., Ng, S. T., & Kumaraswamy, M. M. (2004). Applying a genetic algorithm-based multiobjective approach for time-cost optimization. Journal of Construction Engineering and Management, 130(2), 168-176.