Early-Stage Product Line Validation Using LLMs: A Study on Semi-Formal Blueprint Analysis
We study whether Large Language Models (LLMs) can perform feature model analysis operations (AOs) directly on semi-formal textual blueprints, i.e., concise constrained-language descriptions of feature hierarchies and constraints, enabling early validation in Software Product Line scoping. Using 12 state-of-the-art LLMs and 16 standard AOs, we compare their outputs against the solver-based oracle FLAMA. Results show that reasoning-optimized models (e.g., Grok 4 Fast Reasoning, Gemini 2.5 Pro) achieve 88-89% average accuracy across all evaluated blueprints and operations, approaching solver correctness. We identify systematic errors in structural parsing and constraint reasoning, and highli...
| Authors | Viet-Man Le, Thi Ngoc Trang Tran, Sebastian Lubos et al. |
|---|---|
| Primary category | cs.SE |
| Published | 22 April 2026 |
| Last updated at source | 22 April 2026 |
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