Evolving Intentions


Evolving Intentions: Support for Modeling and Reasoning about Requirements that Change over Time

Full dissertation available here.

Abstract: In early-phase requirements engineering, modeling stakeholder goals and intentions helps stakeholders understand the problem context and evaluate tradeoffs, by exploring possible "what if" questions. Prior research allows modelers to make evaluation assignments to desired goals and generate possible selections for task and dependency alternatives, but this treats models as static snapshots, where once the evaluation of the fulfillment of an intention is determined, it remains constant. Using these techniques stakeholders are unable to reason about possible evolutions, leaving questions about project viability unanswered when the fulfillment of goals or availability of components is not guaranteed in the future. In this dissertation, we propose Evolving Intentions: a framework for specifying, modeling, and reasoning about goals that change over time, enabling stakeholders to explore model evolution. We present Evolving Intentions in the context of both the i* and Tropos goal modeling languages. We specify a set of functions that define how intentions and relationships evolve, and use simulation strategies for asking a variety of "what if" questions about such changes. We present GrowingLeaf and BloomingLeaf, two web-based goal modeling and analysis tools that implement this technique for iStar and Tropos models, respectively. Using the development of GrowingLeaf as an example, we demonstrate that this technique is efective for debugging goal models and answering stakeholder questions, and show the analysis to be scalable for representative goal models. We describe a between-subjects controlled experiment that empirically validated the effectiveness of our approach and tool usability. We also report on the applicability and effectiveness, of our technique on a substantial case, where we use historical data and rational reconstruction to understand how a project evolved in the past, and explore alternative futures.


Alicia M. Grubb
Marsha Chechik
Gary Song
Marcel Serikawa
Jake Fear
Navie (Yikhei) Chan
Allen (Hanbin) Chang
Farhan Samir
Woran (Rose) Gao
Caroline Hu
Nasir Hemed
David Kwon


A. M. Grubb and M. Chechik. Formal Reasoning for Analyzing Goal Models that Evolve Over Time. Requirements Engineering, 26(3): 423-457 2021.

A. M. Grubb and M. Chechik. Reconstructing the Past: The Case of the Spadina Expressway. Requirements Engineering, 25(2): 253-272 2020.
This is a post-peer-review, pre-copy edit version of an article published in Requirements Engineering. The final authenticated version is available online at: http://dx.doi.org/10.1007/s00766-019-00321-0.
Supplementary Information

A. M. Grubb and M. Chechik. Modeling and Reasoning with Changing Intentions: An Experiment. 2017 IEEE 25th International Requirements Engineering Conference (RE), 2017.
© IEEE 2017.
Supplementary Information
Talk Slides.

A. M. Grubb and M. Chechik. Looking into the Crystal Ball: Requirements Evolution over Time. 2016 IEEE 24th International Requirements Engineering Conference (RE), 2016.
© IEEE 2016.
Supplementary Information
Talk Slides.

A. M. Grubb and M. Chechik. BloomingLeaf: A Formal Tool for Requirements Evolution over Time. 2018 IEEE 26th International Requirements Engineering Conference (RE): Tool Demo, 2018.

A. M. Grubb, G. Song, and M. Chechik. GrowingLeaf: Supporting Requirements Evolution over Time. In Proceedings of the 9th International i* Workshop, 2016.
Talk Slides.

A. M. Grubb. Adding Temporal Intention Dynamics to Goal Modeling: A Position Paper. In Proceedings of the Seventh International Workshop on Modeling in Software Engineering at ICSE’15, pages 66–71, 2015.
Talk Slides.


A. M. Grubb and M. Chechik. BloomingLeaf: A Formal Tool for Requirements Evolution over Time. 2018 IEEE 26th International Requirements Engineering Conference (RE), 2018.

A. M. Grubb and M. Chechik. GrowingLeaf: Modeling and Analysis for Goals with Temporal Dynamics. Department of Computer Science Research in Action, March 2016.

Review of Undergraduate Computer Science Papers

Jake Fear. Visually Simulating Goal Models over Time. Department of Computer Science, Fall 2015.

Gary Song. Representing Constraints and Complex Dynamics in Goal Models. Department of Computer Science, Fall 2016.


BloomingLeaf: Formally modeling and Analysis for Goals with Temporal Dynamics in Tropos. GitHub

GrowingLeaf: is an iStar modeling and analysis tool focused on understanding model evolution and how the evaluations of intentional elements change over time. GitHub

Leaf2.0: an goal modeling tool complient with the iStar 2.0 language guide. GitHub

Leaf (beta): is a prototype tool for modeling i* (iStar) goal models.

Last Updated: November 1, 2021