WP1: Live and Exploratory Modeling Foundations

WP1 focuses on establishing the theoretical and methodological foundations for live and exploratory modeling.

Objectives

This work package focuses on the underlying theory to enable change propagation and runtime state co-evolution for live languages. In particular, WP1 specifies what and how the models’ changes are reflected on the runtime states and what strategy to rely on for the co-evolution of the old states to a new consistent state.

The work package proceeds iteratively, ensuring regular synchronization between the global LEM view and the integration of direct manipulation (DM) through exploratory modeling (EM) capabilities.

Partner Contributions

U.Rennes (Lead): Leads the development of language runtimes and workbenches for the coupling live modeling (immediate feedback & direct manipulation) with exploratory modeling.

JKU: Brings expertise in search-based model transformations and tools (e.g., MOMoT), ensuring the DM aspect of live modeling is developed through exploratory modeling techniques.

Tasks

Task T1.1: Efficient and Flexible Coupling of Live and Exploratory Modeling (Lead: U.Rennes)

Description: Creation of language servers that combine immediate feedback (IF) and direct manipulation (DM) capabilities, building upon expertise in co-evolution, change propagation, and modification of runtime state.

Challenge: Finding a way to represent, modify, and explore a potentially large and diverse set of runtime states. If a combined view of IF and DM is not easily representable, the integration will fall back to separated representations.

Task T1.2: Exploration Strategies for Exploratory Modeling (Lead: JKU)

Description: Development of exploratory modeling strategies and preparation of using EM as a solution for direct manipulation (DM). The goal is rapid prototypical implementation for integration in LEM, followed by iterations producing search strategies, computation cost-reduction measures, and user constraint integration.

Challenge: The large search space that must be explored to reach a given runtime state. Mitigation through metaheuristic and search-based solutions as cost-limited options.