Supporting Pragmatic Interoperability: An LLM Based Process to Analyze Distributed Intentionality (i*) Models

Given the advent of large language models (LLM), automatic goal-based model analysis in goal-oriented requirements engineering is a new opportunity. A well-known problem within systems collaboration is the interoperability of its components. Pragmatic interoperability is more challenging than other levels (e.g., syntactic, semantic) since it depends on usage. Automatic detection of variation points in goal-based models and variant analysis are vital to improving pragmatic interoperability between components since they deal with different uses. We propose an integrative process using a distributed intentionality modeling language (i*) strategic rationale (SR) goal model with an LLM to detect independent variation points and analyze which variant is desirable to improve systems’ pragmatic interoperability. The automatic analysis of the LLM is experimented with using image classification contexts to detect risk-situation objects. The detected LLM variation points in i* SR models are evaluated through a controlled experiment, calculating precision, recall, and F-measure. The results present an F-measure of 0.3, indicating that the proposed process is promising in improving pragmatic interoperability.