Empirical Validation of a Multilevel Cognitive Architecture for Collaborative Software Development

Abstract

Modern software development represents a form of collective intellectual activity in which many project decisions emerge through interactions among team members. This study presents an empirical analysis of changes in developers’ representations that occur during collaborative discussions of requirements, architectural decisions, and implementation strategies. The study is grounded in a multilevel cognitive architecture of collaborative software development that links developers’ cognitive processes, project artifacts, and the phases of the Software Development Life Cycle (SDLC). The empirical investigation is based on observations of five software development teams and the analysis of 20 episodes of collaborative interaction. The analysis identified 42 cognitive transitions, defined as changes in team members’ understanding of design and implementation decisions, traced through team communication and project artifacts. To systematize the observed changes, a typology of cognitive transitions is proposed, including alignment, refinement, reconstruction, and reinforcement of representations. The results show that the distribution of transition types varies across different phases of the development process and depends on the tasks and roles of team members: alignment and refinement dominate during requirements engineering and design, while reconstruction and reinforcement become more prominent during implementation and testing. These findings refine the dynamic aspect of the proposed cognitive architecture and provide empirical validation of its core assumptions about cognitive change in software development teams. They suggest that the software development process can be understood as a sequence of cognitive transitions emerging through collaborative interaction and lay the groundwork for future research and tool support for collaborative software engineering.

Author Biographies

Navruza Farhadovna Tulkunova, Innopolis University

Postgraduate Student of the Faculty of Computer Science and Engineering

Giancarlo Succi, Innopolis University

Professor of the Faculty of Computer Science and Engineering, Candidate of Science in Computer and Electrical Engineering

References

1. Buchan J. An empirical cognitive model of the development of shared understanding of requirements. In: Requirements Engineering. In: D. Zowghi, Z. Jin (eds.). Berlin; Heidelberg: Springer; 2014. p. 165-179. https://doi.org/10.1007/978-3-662-43610-3_13
2. Tulkunova N.F., Succi G. Multilevel cognitive architecture for collaborative software development across all stages of the software development lifecycle (SDLC). Information Science and Control Systems. 2026;(1):86-97. (In Russ., abstract in Eng.) https://doi.org/10.22250/18142400_2026_87_1_86
3. Peitek N., Siegmund J., Apel S., Kästner C., Parnin C., Bethmann A., Leich T., Saake G., Brechmann A. A look into programmers’ heads. IEEE Transactions on Software Engineering. 2018;46(4):442-462. https://doi.org/10.1109/TSE.2018.2863303
4. Gonçales L.J., Farias K., da Silva B.C. Measuring the cognitive load of software developers: An extended systematic mapping study. Information and Software Technology. 2021;136:106563. https://doi.org/10.1016/j.infsof.2021.106563
5. Xu S., Rajlich V. Dialog-based protocol: an empirical research method for cognitive activities in software engineering. In: Proceedings of the International Symposium on Empirical Software Engineering. 2005. p. 10. https://doi.org/10.1109/ISESE.2005.1541848
6. Hollan J., Hutchins E., Kirsh D. Distributed cognition: toward a new foundation for human-computer interaction research. ACM Transactions on Computer-Human Interaction. 2000;7(2):174-196. https://doi.org/10.1145/353485.353487
7. Ciancarini P., Farina M., Masyagin S., Succi G., Yermolaieva S., Zagvozkina N. Non-verbal communication in software engineering: an empirical study. IEEE Access. 2021;9:71942-71953. https://doi.org/10.1109/ACCESS.2021.3075983
8. Lanubile F., Ebert C., Prikladnicki R., Vizcaíno A. Collaboration tools for global software engineering. IEEE Software. 2010;27(2):52-55. https://doi.org/10.1109/MS.2010.39
9. Sharp H., Giuffrida R., Melnik G. Information flow within a dispersed agile team: A distributed cognition perspective. In: Agile Processes in Software Engineering and Extreme Programming. Berlin, Heidelberg: Springer; 2012. p. 62-76. https://doi.org/10.1007/978-3-642-30350-0_5
10. Sharp H., Robinson H., Segal J., Furniss D. The role of story cards and the wall in XP teams: a distributed cognition perspective. AGILE 2006. IEEE Press; 2006. p. 75-84. https://doi.org/10.1109/AGILE.2006.56
11. Jones P.H., Chisalita C. Cognition and collaboration: analyzing distributed community practices for design. In: CHI EA ’05. New York: ACM; 2005. p. 2120. https://doi.org/10.1145/1056808.1057116
12. Meyer A.N., Barr E.T., Bird C., Zimmermann T. Today was a good day: The daily life of software developers. IEEE Transactions on Software Engineering. 2019;47(5):863-880. https://doi.org/10.1109/TSE.2019.2904957
13. Fernandes R.G., da Silva L.F., Vils L. Distributed team cognition and collaborative problem-solving in project management. International Journal of Managing Projects in Business. 2023;16(6-7):713-742. https://doi.org/10.1108/IJMPB-05-2023-0100
14. Hyysalo J., Lehto J., Aaramaa S., Kelanti M. Supporting cognitive work in software development workflows. In: Product-Focused Software Process Improvement. Berlin, Heidelberg: Springer; 2013. p. 20-34. https://doi.org/10.1007/978-3-642-39259-7_5
15. Murtazina M.Sh., Avdeenko T.V. The ontology-driven approach to support the requirements engineering process in scrum framework. In: Proceedings of IV International Conference on Information Technology and Nanotechnology (ITNT-2018). Samara: Novaya tekhnika; 2018. p. 2610-2620. (In Russ., abstract in Eng.) EDN: UONRCV
16. Batovrin V.K. Requirements engineering process in the system lifecycle. In: Technologies for the Development of Information Systems TRIS-2016: Conference Proceedings. Vol. 1. Gelendzhik: Southern Federal University; 2016. p. 26-43. (In Russ., abstract in Eng.) EDN: WKYPSP
17. Fernandes R.G., Vils L., da Silva L.F. Distributed cognition model for project management. Revista Gestão & Tecnologia. 2023;23(3):85-127. https://doi.org/10.20397/2177-6652/2023.v23i3.2646
18. Zaina L.A.M., Sharp H., Barroca L. UX information in the daily work of an agile team: A distributed cognition analysis. International Journal of Human-Computer Studies. 2021;147:102574. https://doi.org/10.1016/j.ijhcs.2020.102574
19. Mangalaraj G., Nerur S., Mahapatra R.K., Price K.H. Distributed cognition in software design: An experimental investigation of the role of design patterns and collaboration. MIS Quarterly. 2014;38(1):249-274. https://doi.org/10.25300/MISQ/2014/38.1.12
20. Xiao X., Lindberg A., Hansen S., Lyytinen K. Computing requirements for open source software: A distributed cognitive approach. Journal of the Association for Information Systems. 2018;19(12):2-29. https://doi.org/10.17705/1jais.00525
21. Drury-Grogan M.L. The changes in team cognition and cognitive artifact use during agile software development project management. Project Management Journal. 2021;52(2):127-145. https://doi.org/10.1177/8756972820960301
Published
2026-04-15
How to Cite
TULKUNOVA, Navruza Farhadovna; SUCCI, Giancarlo. Empirical Validation of a Multilevel Cognitive Architecture for Collaborative Software Development. Modern Information Technologies and IT-Education, [S.l.], v. 22, n. 1, p. 106-116, apr. 2026. ISSN 2411-1473. Available at: <http://sitito.cs.msu.ru/index.php/SITITO/article/view/1290>. Date accessed: 14 oct. 2026. doi: https://doi.org/10.25559/SITITO.022.202601.106-116.
Section
Research and Development in the Field of New IT and Their Applications