Alicia M. Grubb is a teaching scholar whose work focuses on how individuals learn, make decisions and understand change, and they address these questions in the context of empirical software engineering. In early-phase software engineering, goal modeling elicits and connects stakeholders’ intentions and social needs with technical requirements in order to help stakeholders understand and evaluate potential tradeoffs. Within this context, Grubb’s prior work enables stakeholders to model and reason about tradeoff decisions in the context of evolving requirements and dependencies.
Undergraduate research projects in the Grubb Lab include: using stakeholder preferences to reduce the solution space of possible evolutions; comparing expressive power and usability of goal modeling languages; visualizing trends in evolutionary reasoning; and exploring the utility of goal modeling activities. See the Grubb Lab webpage for current students and projects.
*denotes Smith undergraduate student
Y. Baatartogtokh*, I. Foster*, and A. M. Grubb. An Experiment on the Effects of using Color to Visualize Requirements Analysis Tasks. 31st IEEE International Requirements Engineering Conference, pages 146–156, 2023.
Y. Baatartogtokh*, I. Foster*, and A. M. Grubb. Visualizations for User-supported State Space Exploration of Requirements Models. 31st IEEE International Requirements Engineering Conference, pages 281–286, 2023.
A. M. Grubb and P. Spoletini. Bringing Stakeholders Along for the Ride: Towards Supporting Intentional Decisions in Software Evolution. 29th International Working Conference on Requirements Engineering: Foundation for Software Quality, pages 56–64, 2023.
M. Daun, A. M. Grubb, V. Stenkova, and B. Tenbergen. A Systematic Literature Review of Requirements Engineering Education. Requirements Engineering, 28(2):145-175, 2023.
K. R. Hablutzel*, A. Jain*, and A. M. Grubb. A Divide & Concur Approach to Collaborative Goal Modeling with Merge in Early-RE. In Proceedings of the IEEE 30th International Requirements Engineering Conference, 2022.
M. Dhaouadi, K. M. B. Spencer*, M. H. Varnum*, A. M. Grubb, M. Famelis. Towards a Generic Method for Articulating Design-time Uncertainty. Journal of Object Technology, 20(3):1-14, 2021.