An Inductive-ROC Based Model for Determining Purchasing System Requirements

Yıl 2021, Cilt: 4 Sayı: 2, 177 - 194, 23.09.2021

Tijen Over Özçelik Orhan Torkul

https://doi.org/10.38016/jista.976919

Öz

The success of system development studies depends on the completeness and accuracy of the requirements collected from system user and stakeholders. Mistakes and deficiencies in the requirements determination process lie in the failure of many system development studies. The dynamism and complexity of today's systems make the requirements determination process even more complicated, and the requirement determination phase, which is the primary stage of system development studies, gains excellent importance. Although there are many techniques, strategies, and models in the literature to improve the requirements Determination process, there are very few studies on their multiple-use, classification of needs, and their experimental realization in a real system. In this study, a system development study was carried out using the System Requirements Model (SRM), which has a flexible structure that allows the system needs to be determined with the use of multiple techniques, at the same time classifies the identified requirements, can decide on the determination levels, and allows the work to be stopped if a sufficient level of needs is determined The developed model consists of three stages: requirement identification, rulemaking/technical/needs matrix creation and classification of needs. In the needs determination process, collection, presentation, verification, and sort of needs. In the second stage of the model, an analogy was made, and the needs and techniques were grouped with the ROC algorithm, and the rule-based RULES-3 algorithm was used to universalize the model. In the third stage of the model, needs were determined based on technical/technical combinations.

Anahtar Kelimeler

Requirements Determination, Requirements Determination Techniques, Stoping Rules, Requirements Engineering, Rank Order Cluster, Inductive Learning, RULES-3

Satın Alma İhtiyaçlarını Belirlemede Endüktif-ROC Temelli Bir Model

Öz

Sistem geliştirme çalışmalarının başarısı sistem kullanıcıları ve paylaşımcılarından toplanan ihtiyaçların tamlığı ve doğruluğuna bağlıdır. Birçok sistem geliştirme çalışmasının başarısızlığında da ihtiyaç belirleme sürecinde ki hatalar ve eksiklikler yatmaktadır. Günümüz sistemlerinin dinamikliği ve karmaşıklığı ihtiyaç belirleme sürecini daha da güçleştirmekte ve sistem geliştirme çalışmalarının öncelikli aşaması olan ihtiyaç belirleme aşaması büyük önem kazanmaktadır. İhtiyaç belirleme sürecinin iyileştirilmesi amacı ile literatürde birçok teknik, strateji ve model bulunmasına karşın bunların çoklu olarak kullanımı, ihtiyaçların sınıflandırılması ve gerçek bir sistemde deneysel olarak gerçekleştirilmesine yönelik çok az sayıda çalışma bulunmaktadır. Bu çalışmada çoklu teknik kullanımı ile sistem ihtiyaçlarının belirlenmesine olanak sağlayan, aynı zamanda belirlenen ihtiyaçları sınıflayan, belirlenme seviyelerine karar verebilen ve yeterli seviyede ihtiyaç belirlenmesi durumunda çalışmanın durdurulmasına izin veren esnek bir yapıya sahip Sistem İhtiyaçları Modeli (SİM) kullanılarak bir sistem geliştirme çalışması gerçekleştirilmiştir. Geliştirilen model ihtiyaç belirleme, kural çıkarma/teknik/ihtiyaç matrisi oluşturma ve ihtiyaçların sınıflanması şeklinde üç aşamadan oluşmaktadır. İhtiyaç belirleme sürecinde; ihtiyaçların toplanması, sunulması, doğrulanması ve sınıflanması gerçekleştirilmiştir. Modelin ikinci aşamasında bir analoji gerçekleştirilerek ROC algoritması ile ihtiyaç ve teknikler gruplanmış ve modelin evrenselleşmesi için kural tabanlı RULES-3 algoritması kullanılmıştır. Modelin üçüncü aşamasında ise teknik/teknik kombinasyonları bazında ihtiyaçlar belirlenmiştir.

Anahtar Kelimeler

İhtiyaç Belirleme, İhtiyaç Belirleme Teknikleri, Durdurma Kuralları, İhtiyaç Mühendisliği, Derece Sıralama ve Kümeleme, Endüktif Öğrenme, RULES-3

Kaynakça

• Aksoy, M. S., (2005). Dynamic System Modelling Using Rules3 Induction Algorithm. Mathematical and Computational Applications, Vol. 10, No. 1, pp. 121-132.
• Aksoy, M. S., (2005). Pruning Decision Trees Using Rules3 Inductive Learning Algorithm. Mathematical and Computational Applications. Vol. 10, No. 1, pp. 113-120
• Alvarez, R., (2002). Discourse Analysis of Requirements and Knowledge Elicitation Interviews. Proceedings of the 35th Hawaii International Conference on System Sciences, IEEE Computer Society.
• Bano, M., Zowghi, D., Ferrari, A., Spoletini & P., Donati, B. (2018). Learning from Mistakes: An Empirical Study of Elicitation Interviews performed by Novices. International Requirements Engineering Conference – Banff, Alberta Canada.
• Browne, G.J., & Pitts, M.G. (2004). Stopping Rule Use During Information Search in Design Problems. Organizational Behavior and Human Decision Processes. 95, 208–224.
• Browne, G.J., & Rogich, M.B. (2001). An empirical investigation of user requirements elicitation: comparing the effectiveness of prompting techniques. Journal of Management Information Systems. Vol. 17 No 4, pp. 223-249.
• Browne, G.J., Ramesh, V., “Improving information requirements determination: a cognitive perspective”, Information & Management, 39 (2002), pp. 625-645
• Byrd, T. A., Cossick, K. L., & Zmud, R. W. (1992). A Synthesis of Research on Requirements Analysis and Knowledge Acquisition Techniques. MIS Quarterly. 16 (1), 117-138.
• Carrizo, D., Dieste, O., & Juristo, N. Systematizing requirements elicitation technique selection. (Access date; 30.06.2021), http://oa.upm.es/37447/1/INVE_MEM_2014_195480-3.pdf
• Carrizo, D., Ortiz, C., & Aguirre, L. (2016) What do researchers mean by “the right requirements elicitation techniques”. Revista chilena de ingeniería. vol. 24 Nº 2, pp. 263-273.
• Cascio, W. F., & Montealegre, R. (2016). How technology is changing work and organizations. Annual Review of Organizational Psychology and Organizational Behavior. (3), 349-375.
• Darke, P., & Shanks, G. (1997). User viewpoint modelling: understanding and representing user viewpoints during requirements definition. Information Systems Journal. Vol. 7, pp. 213-239.
• Davidson, E.J. (2002). Technology frames and framing: a socio-cognitive investigation of requirements Determination. MIS Q. 26 (4) 329–358.
• Davis, G. B. (1982). Strategies for Information Requirements Determination. IBM Systems Journal. 21(1), 4-30.
• Duggan, E.W. (2003). Generating systems requirements with facilitated group techniques. Hum. Comput. Interact. 18 (4), 373–395.
• Freeman, L., A. (2004). The Effects Of Concept Maps on Requirements Elicitation And System Models During Information Systems Development. Concept Maps: Theory, Methodology, Technology Proc. of the First Int. Conference on Concept Mapping. Pamplona, Spain.
• Guinan, P. J, Cooprider, J. G., & Faraj, S. (1998). Enabling Software Development Team Performance During Requirements Definition: A Behavioral Versus Technical Approach. Information Systems Research. Vol. 9, No. 2.
• Hadar, I., Soffer, P., & Kenzi, K. (2012). The role of domain knowledge in requirements elicitation via interviews: an exploratory study. Springer-Verlag London Limited.
• Hanish, J., Thanasankit, T., & Corbitt, B. (2001). Exploring the cultural and social impacts on the requirements engineering processes – highlighting some problems challenging virtual team relationships with clients. Journal of Systems and Information Technology. Vol. 5, No.2, pp. 1-19.
• Hickey, A. M., & Davis, A., M. (2004). A Unified Model of Requirements Elicitation. Journal of Management Information Systems. Vol. 20, No. 4, pp. 65–84.
• Janz, B.D., Frolick, M.N., & Wetherbe, J.C. Human Perception: A Challenge to Organizational Process Optimization. (Access date; 30.06.2021) https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.563.6642&rep=rep1&type=pdf
• King, J.R., (1980). Machine Component Grouping Formation in Group Technology. International Journal of Management Science. Vol. 8(2), pp. 193-199.
• Laudon K. C., & Laudon J. P. (2014). Management Information Systems Managing the Digital Firm, Thirteenth Edition, Pearson Education Limited, https://repository.dinus.ac.id/docs/ajar/Kenneth_C.Laudon,Jane_P_.Laudon_-_Management_Information_Sysrem_13th_Edition_.pdf (Access date;; 6.06.2021)
• Lazar, J., Hanst, E., Buschwalter, J., % Preece, J. (2000). Collecting User Requirements in a Virtual Population, WebNet Journal: Internet Technologies. Applications and Issues. Vol. 2 No. 4, pp. 20-27.
• Över Özçelik, T., & Torkul, O. (2019). Bilişim Sistemi Geliştirmede İhtiyaç Belirleme. Iksad Publications – Ankara / Turkey, ISBN: 978-625-7954-15-0.
• Över, T., (2006). İhtiyaç Belirlemede Endüktif-Roc Temelli Bir Model. Doktora Tezi, Sakarya Üniversitesi Fen Bilimleri Enstitüsü.
• Pitts, M. G. & Browne, G. J. (2004). Stopping Behavior of Systems Analysts During Information Requirements Elicitation. Journal of Management Information Systems. 21:1, 203-226
• Shams, F., Ammar, H., & Bhutta, M. (2019). Selection of Software Requirements Elicitation Techniques- A Systematic Review. Journal of Multidisciplinary Approaches in Science. 1, Issue 1, 8-17.
• Sommerville, I., Sawyer, P., & Viller, S. (1998). Viewpoints for Requirements Elicitation: a practical approach. Third International Conference on Requirements Engineering. IEEE Computer Society Press, pp. 74-81.
• Sutcliffe, A. (2003). Scenario-based requirements engineering. Paper presented at: Proceedings 11th IEEE international requirements engineering conference. IEEE, pp. 320-329.
• Tiwari, S. & Rathore, S. S. (2017). A Methodology for the Selection of Requirement Elicitation Techniques. arXivPrepr. arXiv1709.08481.
• Vessey, I. & Conger, S. (1993). Learning to Specify Information Requirements: The Relationship Between Application and Methodology”. Journal of Management Information Systems, 10 (2), 177-201.
• Vessey, I. & Conger, S. (1994). Requirements specification: learning object, process, and data methodologies. Communications of the ACM. 37 (5), 102-113.
• Wahbeh, A., Sarnikar, S., & El-Gayar, O. (2019). A socio-technical-based process for questionnaire development in requirements elicitation via interviews. Requirements Engineering. 1-21, (Access date; 30.06.2021), https://scholar.dsu.edu/bispapers/136/
• Watson, H. J. & Frolick, M. N. (1993). “Determining Information Requirements for an EIS”. MIS Quarterly. 17(3), 255-269.
• Wetherbe, J.C. (1991). Executive Information Requirements: Getting It Right. MIS Quarterly. Vol. 15, pp. 51-65. Whitten, J.L. & Bentley, L.D.. (2007). Systems Analysis and Design Methods. McGraw-Hill/Irwin, 7th Edition.