The Impact of Human Factors on Software Development Processes Applying the Agile and Waterfall Methodologies: A Case Study Using Real Data

Authors

  • Šarun˙e Sielskait˙e Department of Information Systems, Faculty of Fundamental Sciences, Vilnius Gediminas Technical University, Lithuania
  • Diana Kalibatienė Department of Information Systems, Faculty of Fundamental Sciences Vilnius, Gediminas Technical University, Lithuania

DOI:

https://doi.org/10.15837/ijccc.2025.4.6807

Keywords:

software development process, human factors, Agile, Waterfall, fuzzy logic

Abstract

The software development process (SDP) contains many variables depending on the methodology chosen. Software development methodologies such as Agile or Waterfall can specify how and in what sequence software is developed. However, the SDP remains a hot topic among practitioners and academics, who seek to clarify the key aspects that influence the successful implementation of the SDP. As the SDP is a dynamic and knowledge-intensive business process (BP), one of its most impact components is the human factor (HF). It is difficult to predict how the HF impacts the sequence and results of SDP implementation. This paper proposes a new approach to investigate the impact of the HF on the SDP through the perspectives of different software development methodologies. The advantages and novelties of this approach include modelling HF uncertainties through their fuzzification in SDP activities, modelling different SDP methodologies using a case-handling approach, and simulating a dynamic, case-based SDP with real HF-related data collected from several IT organizations. The results show that the impact of the HF on SDP performance differs across the Waterfall and Agile methodologies. The results also allow researchers and practitioners working on software development projects to familiarize themselves with the impact of the HF on different SDPs, and to assess the degree of development risk associated with the SDP depending on the methodology chosen.

References

Ambler, S. W., & Lines, M. (2012). Introduction to Disciplined Agile Delivery. IBM Press.

Amrit, C., Daneva, M., & Damian, D. (2014). Human factors in software development: On its underlying theories and the value of learning from related disciplines. A guest editorial introduction to the special issue. Information and software technology, 56(12), 1537-1542. https://doi.org/10.1016/j.infsof.2014.07.006

Andrei, B. A., Casu-Pop, A. C., Gheorghe, S. C., & Boiangiu, C. A. (2019). A study on using Waterfall and Agile methods in software project management. Journal of Information Systems & Operations Management, 125-135.

Bai, Z., Li, Y., Wo'zniak, M., Zhou, M., & Li, D. DecomVQANet: Decomposing visual question answering deep network via tensor decomposition and regression. Pattern Recognit. 2021, 110, 107538. https://doi.org/10.1016/j.patcog.2020.107538

Boehm, B. W. (1988). A Spiral Model of Software Development and Enhancement. ACM SIGSOFT Software Engineering Notes, 11(4), 14-24. https://doi.org/10.1145/12944.12948

Capretz, L. F., & Ahmed, F. (2010). Making sense of software development and personality types. IT professional, 12(1), 6-13. https://doi.org/10.1109/MITP.2010.33

Capretz, L. F. (2014). Bringing the human factor to software engineering. IEEE software, 31(2), 104-104. https://doi.org/10.1109/MS.2014.30

Choi, B., & Rhee, F. (2009). Interval type-2 fuzzy memberships function generation methods for pattern recognition. Information Sciences, 179(13), 2102-2122. https://doi.org/10.1016/j.ins.2008.04.009

Cockburn, A. (2002). Agile software development. Addison-Wesley.

Dutra, E., Diirr, B., & Santos, G. (2021, September). Human factors and their influence on software development teams-a tertiary study. In Proceedings of the XXXV Brazilian Symposium on Software Engineering (pp. 442-451). https://doi.org/10.1145/3474624.3474625

Dyba, T., & Dingsøyr, T. (2008). Empirical studies of Agile software development: A systematic review. Information and Software Technology, 50(9-10), 833-859. https://doi.org/10.1016/j.infsof.2008.01.006

Earl, D.J., & Deem, M.W. Monte Carlo simulations. Methods Mol. Biol. 2008, 443, 25-36. https://doi.org/10.1007/978-1-59745-177-2_2

Gilbert, N. (2019). Agent-based models. Sage Publications. https://doi.org/10.4135/9781506355580

Gonçalves, W. F., de Almeida, C. B., de Araújo, L. L., Ferraz, M. S., Xandú, R. B., & de Farias, I. (2017, June). The influence of human factors on the software testing process: The impact of these factors on the software testing process. In 2017 12th Iberian conference on information systems and technologies (CISTI) (pp. 1-6). IEEE. https://doi.org/10.23919/CISTI.2017.7975873

Guveyi, E., Aktas, M. S., & Kalipsiz, O. (2020). Human factor on software quality: a systematic literature review. In Computational Science and Its Applications-ICCSA 2020: 20th International Conference, Cagliari, Italy, July 1-4, 2020, Proceedings, Part IV 20 (pp. 918-930). Springer International Publishing. https://doi.org/10.1007/978-3-030-58811-3_65

Highsmith, J. (2002). Agile software development ecosystems. Addison-Wesley.

Jang, J. ANFIS: adaptive-network-based fuzzy inference system, 1993; Vol. 23, Issue 3. https://ieeexplore.ieee.org/abstract/document/256541/ https://doi.org/10.1109/21.256541

Kacker, R. N., & Lawrence, J. F. (2007). Trapezoidal and triangular distributions for Type B evaluation of standard uncertainty. Metrologia, 44(2), 117. https://doi.org/10.1088/0026-1394/44/2/003

Klügl, F., & Bazzan, A. Agent-based modeling and simulation. AI Magazine, 2012. https:// ojs.aaai.org/index.php/aimagazine/article/view/2425 https://doi.org/10.1609/aimag.v33i3.2425

Machuca-Villegas, L., Gasca-Hurtado, G. P., & Muñoz, M. (2021). Measures related to social and human factors that influence productivity in software development teams. International Journal of Information Systems and Project Management, 9(3), 43-67. https://doi.org/10.12821/ijispm090303

Machuca-Villegas, L., Hurtado, G. G., Puente, S. M., & Tamayo, L. M. R. (2021). An Instrument for Measuring Perception about Social and Human Factors that Influence Software Development Productivity. J. Univers. Comput. Sci., 27(2), 111-134. https://doi.org/10.3897/jucs.65102

Manikavelan, D., & Ponnusamy, R. Software quality analysis based on cost and error using fuzzy combined COCOMO model. J. Ambient. Intell. Humaniz. Comput. 2020, 1-11. https://doi.org/10.1007/s12652-020-01783-9

Marin, M.A., Lotriet, H., & Van Der Poll, J.A. Metrics for the Case Management Modeling and Notation (CMMN) Specification. In Proceedings of the 2015 Annual Research Conference of the South African Institute of Computer Scientists and Information Technologists, Stellenbosch, South Africa, 28-30 September 2015. https://doi.org/10.1145/2815782.2815813

Mao, J. Optimizing Enterprise Marketing Project Portfolios Using Fuzzy Ant Colony Optimization. International Journal of Computers Communications & Control, 2024, 19 (3), 6458. https://doi.org/10.15837/ijccc.2024.3.6458

Nogueira, R.P.; Melicio, R.; Valério, D.; Santos, L.F. Learning methods and predictive modeling to identify failure by human factors in the aviation industry. Appl. Sci. 2023, 13, 4069. https://doi.org/10.3390/app13064069

Pirzadeh, L. (2010). Human factors in software development: a systematic literature review.

Royce, W. W. (1970). Managing the Development of Large Software Systems: Concepts and Techniques. In Proceedings of IEEE WESCON, 1-9.

Ruiz, M., & Salanitri, D. (2019). Understanding how and when human factors are used in the software process: a text-mining based literature review. In Product-Focused Software Process Improvement: 20th International Conference, PROFES 2019, Barcelona, Spain, November 27-29, 2019, Proceedings 20 (pp. 694-708). Springer International Publishing. https://doi.org/10.1007/978-3-030-35333-9_54

Sielskait˙e, Š., & Kalibatien˙e, D. (2023). On Fuzzy and Case-Based Dynamic Software Development Process Modeling and Simulation Approach. Applied Sciences, 13(11), 6603. https://doi.org/10.3390/app13116603

Schwaber, K. (2004). Agile Project Management with Scrum. Microsoft Press.

Sommerville, I. (2011). Software Engineering (9th ed.). Addison-Wesley.

Thesing, T., Feldmann, C., & Burchardt, M. (2021). Agile versus Waterfall project management: decision model for selecting the appropriate approach to a project. Procedia Computer Science, 181, 746-756. https://doi.org/10.1016/j.procs.2021.01.227

Urquhart, L.; Wodehouse, A.; Loudon, B.; Fingland, C. The application of generative algorithms in human-centered product development. Appl. Sci. 2022, 12, 3682. https://doi.org/10.3390/app12073682

Wróbel, K.; Gil, M.; Chae, C.J. On the influence of human factors on safety of remotely-controlled merchant vessels. Appl. Sci. 2021, 11, 1145. https://doi.org/10.3390/app11031145

Additional Files

Published

2025-07-01

Most read articles by the same author(s)

Obs.: This plugin requires at least one statistics/report plugin to be enabled. If your statistics plugins provide more than one metric then please also select a main metric on the admin's site settings page and/or on the journal manager's settings pages.