Hasso-Plattner-Institut
Prof. Dr. Holger Giese
 

25.10.2022

Paper presented at MODELS 2022 Educators Symposium

Our accepted paper on "Tool Support for the Teaching of State-Based Behavior Modeling" was successfully presented at the 18th Educators Symposium at the ACM / IEEE 25th International Conference on Model Driven Engineering Languages and Systems (MODELS) 2022 in Montreal, Canada on October 25 2022.

The paper was authored by HPI members Christian Zöllner, Christian Adriano, Simon Wietheger and Prof. Dr. Holger Giese in joint collaboration with our former senior researcher and current professor at BTU Cottbus-Senftenberg Prof. Dr. Leen Lambers.

The tools and teaching materials featured in the paper are available to other educators and researchers on our GitHub profile. The work is based on our teaching activities with regards to foundations of modeling (courses "Modeling Languages and Formalisms" and "Modelling II").

Abstract

Modeling tools are commonly adopted in classrooms. However, complex state-based behavioral models still pose a challenge for students to understand and validate, mostly because of the intricate semantics of these models.We investigated this challenge and developed dedicated tool support in the form of a validation framework based on the YAKINDU Statechart Tools. Our validation framework simulates environments that interact with the code generated from statecharts as means to animate various open-ended scenarios and predefined test cases that challenge the students’ models. This enabled shorter and user-friendly feedback cycles, which lowered the barrier for students to learn state-based behavioral models. We designed the validation framework to be extensible and made it available as an open source project together with two example environments and complete teaching materials. We report on our experiences in two undergraduate modeling courses (approx. 100 students each). Our results are promising in a sense that we detected positive effects of tool adoption and surprising lack thereof, which we discuss w.r.t. lessons learned and future work.