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A Rough Number-Based Copula-Dombi Aggregation Framework for Selection of Agile Methods for Software Development Projects
Abhijit Saha   Bibhas Chandra Giri   Prasenjit Chatterjee ORCID icon link to view author Prasenjit Chatterjee details   Jurate Sliogeriene   Seifedine Kadry  

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https://doi.org/10.15388/26-INFOR630
Pub. online: 14 May 2026      Type: Research Article      Open accessOpen Access

Received
1 December 2025
Accepted
1 April 2026
Published
14 May 2026

Abstract

Agile methodology follows the Agile Manifesto, encompassing principles, frameworks, and tools for implementation. Selecting an appropriate agile method is a complex multi-criteria decision problem. To address uncertainty objectively, this study employs rough number theory, while Copula-Dombi aggregation operators preserve information and capture interrelationships. A group decision-making framework is developed, with criteria weights derived using cross-entropy and dispersion measures. A case study is conducted to demonstrate the applicability of the proposed framework. The results indicate Dynamic System Development Model as the most suitable method, while project vision and customer involvement emerged as the most influential criteria, demonstrating robustness and practical relevance.

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References

 
Ahmad, A., Ahmad, S., Ehsan, N., Mirza, E., Sarwar, S.Z. (2010). Agile software development: impact on productivity and quality. In: 2010 IEEE International Conference on Management of Innovation and Technology, pp. 287–291.
 
Alahyari, H., Svensson, R., Gorschek, T. (2017). A study of value in agile software development organizations. Journal of Systems and Software, 125, 271–288.
 
Alami, A., Krancher, O., Paasivaara, M. (2022). The journey to technical excellence in agile software development. Information and Software Technology, 150, 106959.
 
Al-Saqqa, S., Sawalha, S., Abdel-Nabi, H. (2020). Agile software development: methodologies and trends. International Journal of Interactive Mobile Technology, 14(11), 246–270.
 
Alshamrani, A.M., Hezam, I.M. (2023). Integrating rough-entropy and rough-TOPSIS methods for evaluating the legatum prosperity pillars of weakest performing countries. Measurement and Control, 56(5–10). https://doi.org/10.1177/00202940231174427.
 
Asif, Q., Henderson-Sellers, B. (2008). An evaluation of the degree of agility in six agile methods and its applicability for method engineering. Information and Software Technology, 50, 280–295.
 
Bacigal, T., Mesiar, R., Najjari, V. (2015). Generators of copulas and aggregation. Information Sciences, 306, 81–87.
 
Barros, L., Tam, C., Varajao, J. (2024). Agile software development projects—unveiling the human-related critical success factors. Information and Software Technology, 170, 107432.
 
Baham, C., Hirschheim, R. (2022). Issues, challenges, and a proposed theoretical core of agile software development research. Information Systems Journal, 32(1), 103–129.
 
Braude, E.J., Bernstein, M.E. (2016). Software Engineering: Modern Approaches. Waveland Press.
 
Bomstrom, H., Kelanti, M., Annanpera, E., Liukkunen, K., Kilamo, T., Sievi-Korte, O., Systa, K. (2023). Information needs and presentation in agile software development. Information and Software Technology, 162, 107265.
 
Bowen, S., Maurer, F. (2002). Process support and knowledge management for virtual teams doing agile software development. In: Proceedings of the 26th Annual International Computer Software and Applications Conference. IEEE, pp. 1118–1120.
 
Casper, L., Dingsøyr, T., Paasivaara, M. (2015). Agile processes in software engineering and extreme programming. In: Proceedings of the 16th International Conference, XP. Springer, pp. 16.
 
Chugh, M., Chugh, N. (2023). A deep drive into software development agile methodologies for software quality assurance. In: Agile Software Development: Trends, Challenges and Applications, pp. 235–255. https://doi.org/10.1002/9781119896838.ch12.
 
Devedzic, V. (2010). Teaching agile software development: a case study. IEEE Transactions on Education, 54(2), 273–278.
 
Deveci, M., Pamucar, D., Oguz, E. (2022). Floating photovoltaic site selection using fuzzy rough numbers-based LAAW and RAFSI model. Applied Energy, 324, 119597. https://doi.org/10.1016/j.apenergy.2022.119597.
 
Dikert, K., Paasivaara, M., Lassenius, C. (2016). Challenges and success factors for large-scale agile transformations: a systematic literature review. Journal of Systems and Software, 119, 87–108.
 
Dingsoyr, T., Nerur, S., Balijepally, V.G., Moe, N.B. (2012). A decade of agile methodologies: towards explaining agile software development. Journal of Systems and Software, 85(6), 1213–1221.
 
Dombi, J. (1982). A general class of fuzzy operators, the De Morgan class of fuzzy operators and fuzziness measures induced by fuzzy operators. Fuzzy Sets and Systems, 8, 149–163.
 
Dyba, T., Dingsoyr, T. (2008). Empirical studies of agile software development: a systematic review. Information and Software Technology, 50, 833–859.
 
Dyba, T., Dingsoyr, T. (2009). What do we know about agile software development? IEEE Software, 26(5), 6–9.
 
Edison, H., Wang, X., Conboy, K. (2021). Comparing methods for large scale agile software development: a systematic literature review. IEEE Transactions on Software, 48(8), 2709–2731.
 
Elbanna, A., Sarker, S. (2016). The risks of agile software development: learning from adopters. IEEE Software, 33(5), 72–79.
 
Erol, I., Oztel, A., Searcy, C., Medeni, T. (2023). Selecting the most suitable blockchain platform: a case study on the healthcare industry using a novel rough MCDM framework. Technological Forecasting & Social Change, 186, 122132. https://doi.org/10.1016/j.techfore.2022.122132.
 
Geambaşu, C.V., Jianu, I., Jianu, I., Gavrila, A. (2011). Influence factors for the choice of a software development methodology. Accounting and Management Information Systems, 10, 479–494.
 
Gheorghe, A.-M., Gheorghe, I.D., Iatan, I.L. (2020). Agile software development. Informatica Economica, 24(2), 90–100.
 
Ghimire, D., Charters, S. (2022). The impact of agile development practices on project outcomes. Software, 1(3), 265–275.
 
Giuffrida, R., Dittrich, Y. (2015). A conceptual framework to study the role of communication through social software for coordination in globally-distributed software teams. Information and Software Technology, 63, 11–30.
 
Gokasar, I., Pamucar, D., Deveci, M., Ding, W. (2023). A novel rough numbers-based extended MACBETH method for the prioritization of the connected autonomous vehicles in real-time traffic management. Expert Systems with Applications, 211, 118445. https://doi.org/10.1016/j.eswa.2022.118445.
 
Görçün, O.F., Saha, A., Kumar, P.V.R., Debnath, B.K. (2025). A hybrid rough aggregation approach for the selection of artificial intelligence-based industrial cleaning robots used in public spaces from the perspective of urban waste management. Engineering Applications of Artificial Intelligence, 150, 109566. https://doi.org/10.1016/j.engappai.2024.109566.
 
Greer, D., Haman, Y. (2011). Agile software development. Software: Practice and Experience, 41(9), 943–944.
 
Habib, B., Romli, R., Zulkifli, M. (2023). Identifying components existing in agile software development for achieving light but sufficient documentation. Journal of Engineering and Applied Science, 70(1), 75.
 
Hamed, A.M.M., Abushama, H. (2013). Popular agile approaches in software development: Review and analysis. In: 2013 International Conference on Computing, Electrical and Electronic Engineering (ICCEEE). IEEE, pp. 160–166.
 
Hinderks, A., Mayo, F.J., Thomaschewski, J., Escalona, M.J. (2022). Approaches to manage the user experience process in agile software development: a systematic literature review. Information and Software Technology, 150, 106957.
 
Itzik, D., Roy, G. (2023). Does agile methodology fit all characteristics of software projects? Review and analysis. Empirical Software Engineering, 28(4), 105.
 
Jain, R., Usman, U. (2016). Effectiveness of agile practices in global software development. International Journal of Grid and Distributed Computing, 9(10), 231–248.
 
Kautz, K. (2011). Investigating the design process: participatory design in agile software development. Information Technology & People, 24(3), 217–235.
 
Khatib, M., Alajjal, N., Alshehhi, A. (2025). Technology selection in agile project management: balancing flexibility, integration, and team capabilities. International Journal of Theory of Organization and Practice, 5(1), 187–203. https://doi.org/10.54489/699gcx22.
 
Kruchten, P. (2013). Contextualizing agile software development. Journal of Software: Evolution and Process, 25(4), 351–361.
 
Mall, R. (2018). Fundamentals of Software Engineering. PHI Learning Pvt. Ltd.
 
Mishra, A., Alzoubi, Y.I. (2023). Structured software development versus agile software development: a comparative analysis. International Journal of System Assurance Engineering and Management, 14(4), 1504–1522.
 
Mishra, S., Kumar, V., Kumar, U., Fantazy, K., Akther, M. (2012). Agile software development practices: evolution, principles, and criticisms. International Journal of Quality and Reliability Management, 29(9), 972–980.
 
Mishra, S., Omorodion, F.M., Damasevicius, R. (2020). Metrics for measuring progress and productivity in agile software development. In: Innovations in Bio-Inspired Computing and Applications, IBICA 2020, Advances in Intelligent Systems and Computing, Vol. 1372. Springer, Cham, pp. 469–478. https://doi.org/10.1007/978-3-030-73603-3_44.
 
Moosavi, S.H.S., Bardsiri, V.K. (2017). Satin bowerbird optimizer: a new optimization algorithm to optimize ANFIS for software development effort estimation. Engineering Applications of Artificial Intelligence, 60, 1–15. https://doi.org/10.1016/j.engappai.2017.01.006.
 
Nelsen, R.B. (2013). An Introduction to Copulas. Springer Science & Business Media.
 
Ouriques, R., Wnuk, K., Gorschek, T., Svensson, R.B. (2023). The role of knowledge-based resources in agile software development contexts. Journal of Systems and Software, 197, 111572.
 
Oyetunji, T.S., Erinjogunola, F.L., Ajirotutu, R.O., Adeyemi, A.B., Ohakawa, T.C., Adio, S.A. (2025). Application of agile methodologies in managing smart affordable housing infrastructure projects. Engineering Science & Technology Journal, 6(2), 73–85.
 
Papadopoulos, G. (2015). Moving from traditional to agile software development methodologies also on large distributed projects. Procedia-Social and Behavioral Sciences, 175, 455–463.
 
Pereira, J.C., Russo, R.F.S.M. (2018). Design thinking integrated in agile software development: a systematic literature review. Procedia Computer Science, 138, 775–782.
 
Perkusich, M., Silva, L.C., Costa, A., Ramos, F., Saraiva, R., Freire, A., Dilorenzo, E., Dantas, E., Santos, D., Gorgonio, K., Almeida, H., Perkusich, A. (2020). Information and Software Technology, 119, 106241.
 
Qi, J., Hu, J., Peng, Y.H. (2020). Integrated rough VIKOR for customer-involved design concept evaluation combining with customers’ preferences and designers’ perceptions. Advanced Engineering Informatics, 46, 101138. https://doi.org/10.1016/j.aei.2020.101138.
 
Rindell, K., Ruohonen, J., Holvitie, J., Hyrynsalmi, S., Leppanen, V. (2021). Security in agile software development: a practitioner survey. Information and Software Technology, 131, 106488.
 
Saha, A., Kolandasamy, R., Chatterjee, P., Antucheviciene, J. (2024). A consensus-based single valued neutrosophic model for selection of educational vendors under metaverse with extended reality. Applied Soft Computing, 155, 111476.
 
Sayed, B., Shamsi, Z., Sadiq, M. (2017). A method for the selection of agile methods using AHP. In: Proceedings of the 5th International Conference on Frontiers in Intelligent Computing: Theory and Applications: FICTA 2016, Vol. 2. Springer, Singapore, pp. 297–303.
 
Schramm, V.B., Damasceno, A.C., Schramm, F. (2023). Supporting the choice of the best-fit agile model using fitradeoff. Pesquisa Operacional, 43, e264750.
 
Shameem, M., Kumar, R.R., Kumar, C., Chandra, B., Khan, A.A. (2018). Prioritizing challenges of agile process in distributed software development environment using analytic hierarchy process. Journal of Software: Evolution and Process, 30(11), e1979.
 
Shameem, M., Nadeem, M., Zamani, A.T. (2023). Genetic algorithm-based probabilistic model for agile project success in global software development. Applied Soft Computing, 135, 109998.
 
Shastri, Y., Hoda, R., Amar, R. (2021). The role of the project manager in agile software development projects. Journal of Systems and Software, 173, 110871.
 
Silva, V.B., Schramm, F., Damasceno, A.C. (2016). A multi-criteria approach for selection of agile methodologies in software development projects. In: 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC). IEEE, pp. 002056–002060.
 
Simhadri, R.S., Shameem, M. (2023). Challenges in requirements gathering for agile software development. In: Proceedings of the 27th International Conference on Evaluation and Assessment in Software Engineering, pp. 406–413.
 
Sinani, F., Erceg, Z., Vasiljević, M. (2020). An evaluation of a third-party logistics provider: the application of the rough Dombi-Hamy mean operator. Decision Making: Applications in Management and Engineering, 3(1), 92–107. https://doi.org/10.31181/dmame2003080f.
 
Stojić, G., Stević, Z., Antuchevičiene, J., Pamučar, D., Vasiljević, M. (2018). A novel rough WASPAS approach for supplier selection in a company manufacturing PVC carpentry products. Information, 9(5), 121. https://doi.org/10.3390/info9050121.
 
Strode, D.E. (2016). A dependency taxonomy for agile software development projects. Information Systems Frontiers, 18(1), 23–46.
 
Strode, D.E., Huff, S.L., Hope, B., Link, S. (2012). Coordination in co-located agile software development projects. Journal of Systems and Software, 85(6), 1222–1238.
 
Strode, D., Dingsoyr, T., Lindsjorn, Y. (2022). A teamwork effectiveness model for agile software development. Empirical Software Engineering, 27(2), 56.
 
Tam, C., Moura, E.J.C., Oliveira, T., Varajao, J. (2020). The factors influencing the success of ongoing agile software development projects. International Journal of Project Management, 38(3), 165–176.
 
Tasneem, N., Zulzalil, H.B., Hassan, S. (2025). Enhancing agile software development: a systematic literature review of requirement prioritization and reprioritization techniques. IEEE Access, 13, 32993–33034. https://doi.org/10.1109/ACCESS.2025.3539357.
 
Tavares, B.G., Keil, M., D’silva, C.E., D’souza, A.D. (2021). A risk management tool for agile software development. Journal of Computer Information Systems, 61(6), 561–570.
 
Terzioglu, T., Polat, G. (2022). Formwork system selection in building construction projects using an integrated rough AHP-EDAS approach: a case study. Buildings, 12(8), 1084. https://doi.org/10.3390/buildings12081084.
 
Usman, M., Mendes, E., Weidt, F., Britto, R. (2014). Effort estimation in agile software development: a systematic literature review. In: Proceeding of the 10th International Conference on Predictive Models in Software Engineering, pp. 82–91.
 
Vojinović, N., Sremac, S., Zlatanović, D. (2021). A novel integrated fuzzy-rough MCDM model for evaluation of companies for transport of dangerous goods. Complexity, 2021, 5141611. https://doi.org/10.1155/2021/5141611.
 
Wang, X., Triantaphyllou, E. (2008). Ranking irregularities when evaluating alternatives by using some ELECTRE methods. Omega, 36(1), 45–63.
 
Williams, L. (2010). Agile software development methodologies and practices. Advances in Computers, 80, 1–44.
 
Yazdani, M., Chatterjee, P., Pamucar, D., Chakraborty, S. (2020). Development of an integrated decision-making model for location selection of logistics centers in the Spanish autonomous communities. Computers and Industrial Engineering, 148, 113208.
 
Yel, İ., Baysal, M.E., Sarucan, A. (2023). A new approach to developing software projects by assigning teams to projects with interval-valued neutrosophic Z numbers. Engineering Applications of Artificial Intelligence, 126, 106984. https://doi.org/10.1016/j.engappai.2023.106984.
 
Zhao, P., Ji, S., Xue, Y. (2023). An integrated approach based on the decision-theoretic rough set for resilient supplier selection and order allocation. Kybernetes, 52(3), 774–808.
 
Zavadskas, E.K., Stevic, Z., Tanackov, I., Prentkovskis, O. (2018). A novel multi-criteria approach-Rough step-wise weight assessment ratio analysis method (R-SWARA) and its application in logistics. Studies in Informatics and Control, 27(1), 97–106. https://doi.org/10.24846/v27i1y201810.

Biographies

Saha Abhijit
abhijit84.math@gmail.com

A. Saha is an assistant professor (research) in the Department of Computing Technologies at SRMIST, Tamil Nadu, India. Dr. Saha has published 40 research articles in various journals of international repute. His areas of research interest are fuzzy set theory, soft set theory, optimization and decision-making. He is serving as an editorial board member of various Scopus indexed journals including International Journal of Neutrosophic Sciences and Decision Making: Applications in Engineering and Management.

Chandra Giri Bibhas
bcgiri.jumath@gmail.com

B.C Giri is a professor of mathematics at Jadavpur University, Kolkata, with over two decades of teaching and research experience. His research focuses on operations research, sustainable supply chain management, inventory theory, and multi-criteria decision-making, with applications of emerging technologies like AI and Industry 4.0. He has published more than 250 research papers and supervised numerous PhD scholars.

Chatterjee Prasenjit
https://orcid.org/0000-0002-7994-4252
p.chatterjee@mckvie.edu.in

P. Chatterjee is currently a professor of mechanical engineering and dean (research and consultancy) at MCKV Institute of Engineering, West Bengal, India. He has over 180 research papers in various international journals and peer reviewed conferences. He has authored and edited more than 57 books on intelligent decision-making, supply chain management, optimization techniques, risk and sustainability modelling. He is the lead series editor of Disruptive Technologies and Digital Transformations for Society 5.0, Springer. He is also the lead series editor of Smart and Intelligent Computing in Engineering, Chapman and Hall/CRC Press, founder and lead series editor of Concise Introductions to AI and Data Science, Scrivener – Wiley; AAP Research Notes on Optimization and Decision Making Theories; Frontiers of Mechanical and Industrial Engineering, Apple Academic Press, co-published with CRC Press, Taylor and Francis Group and River Publishers Series in Industrial Manufacturing and Systems Engineering. Dr. Chatterjee is one of the developers of two multiple-criteria decision-making methods called Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) and Ranking of Alternatives through Functional mapping of criterion sub-intervals into a Single Interval (RAFSI).

Sliogeriene Jurate
jurate.sliogeriene@vilniustech.lt

J. Sliogeriene is an associate professor and research fellow at the Laboratory of Smart Building Systems, Institute of Sustainable Construction, Vilnius Gediminas Technical University, Lithuania. Her main research areas include decision analytics, renewable energy, sustainable development, and energy systems. She has an extensive record of publications indexed in the Science Citation Index Expanded (SCIE) and Social Science Citation Index (SSCI). Her research contributions have made a significant impact on the fields of energy and sustainability.

Kadry Seifedine
seifedine.kadry@lau.edu.lb

S. Kadry is a professor of Department of Computer Science and Mathematics, Lebanese American University, Beirut, Lebanon. He has extensive teaching experience across data science, AI, machine learning, statistics, and computing. He is actively involved in accreditation and quality assurance and serves as a European project reviewer, IEEE senior member, Fellow of IET, IETE, and IASCIT, editor-in-chief of IJEECS and IJQCSSE, and associate editor of IEEE Access. His research focuses on stochastic modelling and machine learning applications, particularly in medical imaging.


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Keywords
software development projects agile methods rough numbers hybrid aggregation group decision-making

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