臺灣博碩士論文加值系統

軟體測試階段的工作攸關整體專案品質，而且軟體專案在測試階段會遭遇諸多不確定因素以及風險，因此針對軟體測試階段進行風險管理，提前辨識出測試任務之風險，組織即能提前訂定策略因應，確保軟體測試階段能在有限的資源下有效率的進行，進而得到更良好的軟體專案品質。然而，軟體測試及其風險辨識為知識密集的領域，需要仰賴專案人員的知識及經驗來辨識風險。為了將此知識在組織中分享及重用，因此本研究將建立本體模型保存專家人員知識，記錄並建立風險因子與風險關聯及風險間關聯。此外，進一步透過此關聯，運用模糊分析網路程序法量化關聯相依性。最後，將本體模型與風險關聯性整合後，設計與實作Ontology-Based Software Testing Risk Identification System，簡稱為OTRI，OTRI為Web-based系統，此系統可協助測試團隊辨識風險並掌握全面的風險關聯，並使組織知識儲存與再利用，以利測試任務順利且有效率的進行。

Software testing is one of the most important of software development tasks. Additionally, software testing often encounter uncertain and problematic risks. With the ability to identify the software testing risks, organizations could set proactive risk management strategies. However, software testing and risk identification are knowledge-intensive domain and it requires experienced domain experts and practitioner to do them efficiently. This research develops the ontology-based system to make use of organizational knowledge regarding software testing risk. In this system not only the relation between risks and risk factors but also the risks’ interaction relation are captured and saved. In addition, this research uses fuzzy analytic network process to quantify risks’ interaction relation. When a risk is identified, the proposed system is able to propagate other risks that are affected by the risk. Finally based on the model, this research is expected to assist test teams to comprehensively control the software testing risks.

摘要 i
Abstract ii
目錄 iii
圖目錄 vi
表目錄 vii
第一章 緒論 1
1.1. 研究背景 1
1.2. 問題描述與目的 2
1.3. 研究範圍與假設 4
1.4. 研究架構 5
第二章 文獻探討 6
2.1. 軟體專案風險管理 6
2.2. 軟體測試階段 8
2.3. 軟體測試風險內容 10
2.4. 風險分析方法 14
2.5. 本體論 17
第三章 系統概念與設計 22
3.1. 系統架構 22
3.2. 測試風險因子及建立本體 24
3.3. 規則設計 39
3.4. 模糊分析風險關聯程序法（FARRP） 43
第四章 系統與成果展示 50
4.1. 知識擷取與建立 54
4.2. 功能展示 57
第五章 系統驗證 69
5.1. 模式分析 69
5.2. 問卷結果與討論 71
5.3. 系統比較 77
第六章 結論與未來展望 80
6.1. 研究結果與討論 80
6.2. 研究限制與未來展望 81
參考文獻 82
附錄 96

胡小亮，「設計並建立以本體論為基礎之風險辨識資訊系統」。國立中央大學，碩士論文，民國104年。
[2] 　簡嘉成，「結合本體論與網路分析程序法於軟體專案風險之辨識與評估」。國立中央大學，碩士論文，民國105年。
[3] 　Aizen, M. A., & Harder, L. D. (2009). The global stock of domesticated honey bees is growing slower than agricultural demand for pollination. Current biology, 19(11), 915-918.
[4] Aloini, D., Dulmin, R., Mininno, V., & Ponticelli, S. (2012). Supply chain management: a review of implementation risks in the construction industry. Business Process Management Journal, 18(5), 735-761.
[5] Amland, S. (2000). Risk-based testing:: Risk analysis fundamentals and metrics for software testing including a financial application case study. Journal of Systems and Software, 53(3), 287-295.
[6] Arias, J. C. (2011). Review of risk management methods. Volume 4-Number 1-January 2011-Semiannual Publication, 4(1), 59.
[7] Ashrafi, N. (2003). The impact of software process improvement on quality: in theory and practice. Information & Management, 40(7), 677-690.
[8] Bai, X., Lee, S., Tsai, W. T., & Chen, Y. (2008, September). Ontology-based test modeling and partition testing of web services. In Web Services, 2008. ICWS'08. IEEE International Conference on (pp. 465-472). IEEE.
[9] Bannerman, P. L. (2008). Risk and risk management in software projects: A reassessment. Journal of Systems and Software, 81(12), 2118-2133.
[10] 　Bannerman, P. L. (2015). A Reassessment of Risk Management in Software Projects. In Handbook on Project Management and Scheduling Vol. 2 (pp. 1119-1134). Springer International Publishing.
[11] Bansal, R., & Chawla, S. (2015). Evaluation Metrics for Computer Science Domain Specific Ontology in Semantic Web Based IRSCSD System. International Journal of Computer (IJC), 19(1), 129-139.
[12] Barbosa, E. F., Nakagawa, E. Y., & Maldonado, J. C. (2006, July). Towards the Establishment of an Ontology of Software Testing. In SEKE (pp. 522-525).
[13] Barr, E. T., Harman, M., McMinn, P., Shahbaz, M., & Yoo, S. (2015). The oracle problem in software testing: A survey. IEEE transactions on software engineering, 41(5), 507-525.
[14] Bertolino, A. (2007, May). Software testing research: Achievements, challenges, dreams. In 2007 Future of Software Engineering (pp. 85-103). IEEE Computer Society.
[15] Bhattacharya, A., Mohapatra, P., Kumar, V., Dey, P. K., Brady, M., Tiwari, M. K., & Nudurupati, S. S. (2014). Green supply chain performance measurement using fuzzy ANP-based balanced scorecard: a collaborative decision-making approach. Production Planning & Control, 25(8), 698-714.
[16] Bland, J. M., & Altman, D. G. (1997). Statistics notes: Cronbach's alpha. Bmj, 314(7080), 572.
[17] Boehm, B. (1986). A spiral model of software development and enhancement. ACM SIGSOFT Software Engineering Notes, 11(4), 14-24.
[18] Boehm, B. W. (1988). A spiral model of software development and enhancement. Computer, 21(5), 61-72.
[19] Boehm, B. W. (1991). Software risk management: principles and practices. IEEE software, 8(1), 32-41.
[20] Bonett, D. G., & Wright, T. A. (2015). Cronbach's alpha reliability: Interval estimation, hypothesis testing, and sample size planning. Journal of Organizational Behavior, 36(1), 3-15.
[21] Borst, W. N. (1997). Construction of engineering ontologies for knowledge sharing and reuse. Universiteit Twente.
[22] Braaksma, A. J. J., Klingenberg, W., & Veldman, J. (2013). Failure mode and effect analysis in asset maintenance: a multiple case study in the process industry. International journal of production research, 51(4), 1055-1071.
[23] Braude, E. J., & Bernstein, M. E. (2016). Software engineering: modern approaches. Waveland Press.
[24] Cagliano, A. C., Grimaldi, S., & Rafele, C. (2015). Choosing project risk management techniques. A theoretical framework. Journal of Risk Research, 18(2), 232-248.
[25] Cai, L., Tong, W., Liu, Z., & Zhang, J. (2009, November). Test case reuse based on ontology. In Dependable Computing, 2009. PRDC'09. 15th IEEE Pacific Rim International Symposium on (pp. 103-108). IEEE.
[26] Carr, M. J., Konda, S. L., Monarch, I., Ulrich, F. C., & Walker, C. F. (1993). Taxonomy-based risk identification (No. CMU/SEI-93-TR-06). CARNEGIE-MELLON UNIV PITTSBURGH PA SOFTWARE ENGINEERING INST.
[27] Cervone, H. F. (2006). Project risk management. OCLC Systems & Services: International digital library perspectives, 22(4), 256-262.
[28] Chao Peng, G., & Baptista Nunes, M. (2009). Surfacing ERP exploitation risks through a risk ontology. Industrial Management & Data Systems, 109(7), 926-942.
[29] Chapman, C., & Ward, S. (2003). Project risk management: processes, techniques and insights.
[30] Charette, R. N. (2005). Why software fails. IEEE spectrum, 42(9), 36.
[31] Chemweno, P., Pintelon, L., Van Horenbeek, A., & Muchiri, P. (2015). Development of a risk assessment selection methodology for asset maintenance decision making: An analytic network process (ANP) approach. International Journal of Production Economics, 170, 663-676.
[32] Chen, Y., & Probert, R. L. (2003). A risk-based regression test selection strategy. 14th ISSRE.
[33] Chi, Y. L. (2010). Rule-based ontological knowledge base for monitoring partners across supply networks. Expert Systems with Applications, 37(2), 1400-1407.
[34] Chung, S. H., Lee, A. H., & Pearn, W. L. (2005). Analytic network process (ANP) approach for product mix planning in semiconductor fabricator. International Journal of Production Economics, 96(1), 15-36.
[35] Creswell, J. W. (2013). Research design: Qualitative, quantitative, and mixed methods approaches. Sage publications.
[36] Ebert, C., & De Man, J. (2008). Effectively utilizing project, product and process knowledge. Information and Software Technology, 50(6), 579-594.
[37] Elfriede, D. (2002). Effective Software Testing: 50 Specific Ways to Improve Your Testing.
[38] Elzamly, A., Hussin, B., & Salleh, N. M. (2016). Top Fifty Software Risk Factors and the Best Thirty Risk Management Techniques in Software Development Lifecycle for Successful Software Projects. International Journal of Hybrid Information Technology, 9(6), 11-32.
[39] Ergu, D., Kou, G., Shi, Y., & Shi, Y. (2014). Analytic network process in risk assessment and decision analysis. Computers & Operations Research, 42, 58-74.
[40] Fairley, R. E., & Willshire, M. J. (2005). Iterative rework: the good, the bad, and the ugly. Computer, 38(9), 34-41.
[41] Fan, C. F., & Yu, Y. C. (2004). BBN-based software project risk management. Journal of Systems and Software, 73(2), 193-203.
[42] Fang, C., & Marle, F. (2012). A simulation-based risk network model for decision support in project risk management. Decision Support Systems, 52(3), 635-644.
[43] Felderer, M., & Schieferdecker, I. (2014). A taxonomy of risk-based testing.
[44] Felderer, M., Haisjackl, C., Breu, R., & Motz, J. (2012, January). Integrating manual and automatic risk assessment for risk-based testing. In International Conference on Software Quality (pp. 159-180). Springer Berlin Heidelberg.
[45] Fowler Jr, F. J. (2013). Survey research methods. Sage publications.
[46] Fuggetta, A., & Di Nitto, E. (2014, May). Software process. In Proceedings of the on Future of Software Engineering (pp. 1-12). ACM.
[47] Gelperin, D., & Hetzel, B. (1988). The growth of software testing. Communications of the ACM, 31(6), 687-695.
[48] Graham, D., Van Veenendaal, E., & Evans, I. (2008). Foundations of software testing: ISTQB certification. Cengage Learning EMEA.
[49] Gruber, T. R. (1993). A translation approach to portable ontology specifications. Knowledge acquisition, 5(2), 199-220.
[50] Guarino, N. (1998, June). Formal ontology and information systems. In Proceedings of FOIS (Vol. 98, No. 1998, pp. 81-97).
[51] H.C. (2008). A web-based prototype for live capture and reuse of construction
[52] Hall, E. M. (1998). Managing risk: Methods for software systems development. Pearson Education.
[53] Han, W. M., & Huang, S. J. (2007). An empirical analysis of risk components and performance on software projects. Journal of Systems and Software, 80(1), 42-50.
[54] Harman, M., Jia, Y., & Zhang, Y. (2015, April). Achievements, open problems and challenges for search based software testing. In Software Testing, Verification and Validation (ICST), 2015 IEEE 8th International Conference on (pp. 1-12). IEEE.
[55] Hazen, B. T., Boone, C. A., Ezell, J. D., & Jones-Farmer, L. A. (2014). Data quality for data science, predictive analytics, and big data in supply chain management: An introduction to the problem and suggestions for research and applications. International Journal of Production Economics, 154, 72-80.
[56] Higuera, R. P., & Haimes, Y. Y. (1996). Software Risk Management (No. CMU/SEI-96-TR-012). CARNEGIE-MELLON UNIV PITTSBURGH PA SOFTWARE ENGINEERING INST.
[57] Hillson, D., & Simon, P. (2012). Practical project risk management: The ATOM methodology. Management Concepts Inc.
[58] Hu, Y., Zhang, X., Ngai, E. W. T., Cai, R., & Liu, M. (2013). Software project risk analysis using Bayesian networks with causality constraints. Decision Support Systems, 56, 439-449.
[59] Huang, Q. (2015, April). Research on Risk Analysis and Management in the Software Development Process. In 2015 5th International Conference on Education, Management, Information and Medicine (EMIM 2015).
[60] Huo, Q., Zhu, H., & Greenwood, S. (2003, November). A multi-agent software engineering environment for testing Web-based applications. In Computer Software and Applications Conference, 2003. COMPSAC 2003. Proceedings. 27th Annual International (pp. 210-215). IEEE.
[61] Hwang, W., Hsiao, B., Chen, H. G., & Chern, C. C. (2016). Multiphase Assessment of Project Risk Interdependencies: Evidence from a University ISD Project in Taiwan. Project Management Journal, 47(1), 59-75
[62] Hwang, W., Hsiao, B., Chen, H. G., & Chern, C. C. (2016). Multiphase Assessment of Project Risk Interdependencies: Evidence from a University ISD Project in Taiwan. Project Management Journal, 47(1), 59-75.
[63] IEEE (2012) IEEE Std 1012-2012 IEEE Standard for System and Software Verification and Validation. IEEE Standards Association.
[64] Islam, S., Mouratidis, H., & Weippl, E. R. (2014). An empirical study on the implementation and evaluation of a goal-driven software development risk management model. Information and Software Technology, 56(2), 117-133.
[65] Jaafar, J., Janjua, U. I., & Lai, F. W. (2015). Software effective risk management: An evaluation of risk management process models and standards. In Information Science and Applications (pp. 837-844). Springer Berlin Heidelberg.
[66] Jones, C. (2012). Software Quality Metrics: Three Harmful Metrics and Two Helpful Metrics. Tech. Rep., Project Performance International (PPI).
[67] Khomh, F., Adams, B., Dhaliwal, T., & Zou, Y. (2015). Understanding the impact of rapid releases on software quality. Empir Software Eng
[68] Klatt, B. K., Holzschuh, A., Westphal, C., Clough, Y., Smit, I., Pawelzik, E., & Tscharntke, T. (2014, January). Bee pollination improves crop quality, shelf life and commercial value. In Proc. R. Soc. B (Vol. 281, No. 1775, p. 20132440). The Royal Society.
[69] Krutz, D. E., Malachowsky, S. A., & Reichlmayr, T. (2014, March). Using a real world project in a software testing course. In Proceedings of the 45th ACM technical symposium on Computer science education (pp. 49-54). ACM.
[70] Lee, J. W., & Kim, S. H. (2000). Using analytic network process and goal programming for interdependent information system project selection. Computers & Operations Research, 27(4), 367-382.
[71] Lee, Y. W., Strong, D. M., Kahn, B. K., & Wang, R. Y. (2002). AIMQ: a methodology for information quality assessment. Information & management, 40(2), 133-146.
[72] Leung, N. K., Lau, S. K., & Tsang, N. (2013). An ontology-based collaborative inter-organisational knowledge management network (CIK-NET). Journal of Information & Knowledge Management, 12(01), 1350005.
[73] Li, X., & Zhang, W. (2012, April). Ontology-based testing platform for reusing. In 2012 Sixth International Conference on Internet Computing for Science and Engineering (pp. 86-89). IEEE.
[74] Lin, Y. C., & Lee, H. Y. (2012). Developing project communities of practice-based knowledge management system in construction. Automation in Construction, 22, 422-432.
[75] Marcelino-Sádaba, S., Pérez-Ezcurdia, A., Lazcano, A. M. E., & Villanueva, P. (2014). Project risk management methodology for small firms. International Journal of Project Management, 32(2), 327-340.
[76] McFarlan, F. W. (1981). Portfolio approach to information-systems. Harvard business review, 59(5), 142-150.
[77] Meenakshi, D., Naik, J. S., & Reddy, M. R. (2014). Software testing techniques in software development life cycle. International Journal of computer science and information Technologies (IJCSIT), 5, 3729-3731.
[78] Mikhailov, L., & Singh, M. G. (2003). Fuzzy analytic network process and its application to the development of decision support systems. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 33(1), 33-41.
[79] Muccini, H., Di Francesco, A., & Esposito, P. (2012, June). Software testing of mobile applications: Challenges and future research directions. In Proceedings of the 7th International Workshop on Automation of Software Test (pp. 29-35). IEEE Press.
[80] Myers, G. J., Sandler, C., & Badgett, T. (2011). The art of software testing. John Wiley & Sons.
[81] Nakatsu, R. T., & Iacovou, C. L. (2009). A comparative study of important risk factors involved in offshore and domestic outsourcing of software development projects: A two-panel Delphi study. Information & Management, 46(1), 57-68.
[82] Neves, S. M., da Silva, C. E. S., Salomon, V. A. P., da Silva, A. F., & Sotomonte, B. E. P. (2014). Risk management in software projects through knowledge management techniques: cases in Brazilian incubated technology-based firms. International Journal of Project Management, 32(1), 125-138.
[83] Niemira, M. P., & Saaty, T. L. (2004). An analytic network process model for financial-crisis forecasting. International Journal of Forecasting, 20(4), 573-587.
[84] Noy, N. F., & McGuinness, D. L. (2001). Ontology development 101: A guide to creating your first ontology.
[85] Orso, A., & Rothermel, G. (2014, May). Software testing: a research travelogue (2000–2014). In Proceedings of the on Future of Software Engineering (pp. 117-132). ACM.
[86] Perry, J. G., & Hayes, R. W. (1985). Risk and its management in construction projects. Proceedings of the Institution of Civil Engineers, 78(3), 499-521.
[87] Persson, J. S., Mathiassen, L., Boeg, J., Madsen, T. S., & Steinson, F. (2009). Managing risks in distributed software projects: an integrative framework. IEEE Transactions on engineering management, 56(3), 508-532.
[88] Plans, V. (1994). IEEE Guide for Software Verification and Validation Plans.
[89] Porter, C. E. (1981). Risk allowance in construction contracts. Unpublished MSc. project report.
[90] project knowledge. Automation in Construction, 17, 839–851.
[91] Project Management Institute. 2008. A Guide to the Project Management Body of Knowledge (PMBOK® Guide). 4th ed. Newtown Square, PA: PMI.
[92] Punch, K. F., & Oancea, A. (2014). Introduction to research methods in education. Sage.
[93] Ragin, C. C. (2014). The comparative method: Moving beyond qualitative and quantitative strategies. Univ of California Press.
[94] Redmill, F. (2004). Exploring risk‐based testing and its implications. Software Testing, Verification and Reliability, 14(1), 3-15.
[95] Roy, B., Dasgupta, R., & Chaki, N. (2016). A Study on Software Risk Management Strategies and Mapping with SDLC. In Advanced Computing and Systems for Security (pp. 121-138). Springer India.
[96] Royce, W. W. (1970, August). Managing the development of large software systems. In proceedings of IEEE WESCON (Vol. 26, No. 8, pp. 1-9).
[97] Ryu, Y. S., & Smith-Jackson, T. L. (2006). Reliability and validity of the mobile phone usability questionnaire (MPUQ). Journal of Usability Studies, 2(1), 39-53.
[98] Saaty, T. L. (1980).The analytic hierarchy process. New York: McGraw-Hill.
[99] Sapna, P. G., & Mohanty, H. (2011, March). An Ontology Based Approach for Test Scenario Management. In International Conference on Information Intelligence, Systems, Technology and Management (pp. 91-100). Springer Berlin Heidelberg.
[100] Sarigiannidis, L., & Chatzoglou, P. D. (2014). Quality vs risk: An investigation of their relationship in software development projects. International Journal of Project Management, 32(6), 1073-1082.
[101] Satty, T. L. (1996). Decision making with dependence and feedback: The analytic network process. RWS Publication.
[102] Sheffield, J., & Lemétayer, J. (2013). Factors associated with the software development agility of successful projects. International Journal of Project Management, 31(3), 459-472.
[103] Souza, E. F., Falbo, R. A., & Vijaykumar, N. L. (2013, September). Using Ontology Patterns for Building a Reference Software Testing Ontology. In 2013 17th IEEE International Enterprise Distributed Object Computing Conference Workshops (pp. 21-30). IEEE.
[104] Souza, E., Gusmão, C., & Venâncio, J. (2010, April). Risk-based testing: A case study. In information technology: new generations (ITNG), 2010 seventh international conference on (pp. 1032-1037). IEEE.
[105] Studer, R., Benjamins, V. R., & Fensel, D. (1998). Knowledge engineering: principles and methods. Data & knowledge engineering, 25(1-2), 161-197.
[106] Taroun, A. (2014). Towards a better modelling and assessment of construction risk: Insights from a literature review. International Journal of Project Management, 32(1), 101-115.
[107] Tchankova, L. (2002). Risk identification-basic stage in risk management. Environmental Management and Health, 13(3), 290-297.
[108] Udeaja, C. E., Kamara, J. M., Carrillo, P. M., Anumba, C. J., Bouchlaghem, N. D., & Tan, H. C. (2008). A web-based prototype for live capture and reuse of construction project knowledge. Automation in Construction, 17(7), 839-851.,
[109] Uzzafer, M. (2013). A contingency estimation model for software projects. International Journal of Project Management, 31(7), 981-993.
[110] Van Horenbeek, A., & Pintelon, L. (2014). Development of a maintenance performance measurement framework—using the analytic network process (ANP) for maintenance performance indicator selection. Omega, 42(1), 33-46.
[111] Venkatesh, V., Brown, S. A., & Bala, H. (2013). Bridging the qualitative-quantitative divide: Guidelines for conducting mixed methods research in information systems. MIS quarterly, 37(1), 21-54.
[112] Vinodh, S., Ramiya, R. A., & Gautham, S. G. (2011). Application of fuzzy analytic network process for supplier selection in a manufacturing organisation. Expert Systems with Applications, 38(1), 272-280.
[113] Weber, P., Medina-Oliva, G., Simon, C., & Iung, B. (2012). Overview on Bayesian networks applications for dependability, risk analysis and maintenance areas. Engineering Applications of Artificial Intelligence, 25(4), 671-682.
[114] Whittaker, J. A. (2000). What is software testing? And why is it so hard?. IEEE software, 17(1), 70-79.
[115] Williams, R. C., Pandelios, G. J., & Behrens, S. G. (1999). Software Risk Evaluation (SRE) Method Description: Version 2.0. Carnegie Mellon University, Software Engineering Institute.
[116] Wongthongtham, P., Chang, E., Dillon, T., & Sommerville, I. (2009). Development of a software engineering ontology for multisite software development. IEEE Transactions on Knowledge and Data Engineering, 21(8), 1205-1217.
[117] Yu, L., Zhang, L., Xiang, H., Su, Y., Zhao, W., & Zhu, J. (2009, September). A Framework of Testing as a Service. In Management and Service Science, 2009. MASS'09. International Conference on (pp. 1-4). IEEE.
[118] Zaveri, A., Rula, A., Maurino, A., Pietrobon, R., Lehmann, J., & Auer, S. (2016). Quality assessment for linked data: A survey. Semantic Web, 7(1), 63-93.