A context-aware LLM pipeline generates metamorphic relations for 142 AR repositories; hierarchical context plus agentic deliberation yields 3,760 refined MRs that human raters judge mostly valid and testable, with 5 case-study MRs detecting 16 injected faults.
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Repository-Aware Metamorphic Relation Generation for Augmented Reality Applications using Large Language Models
A context-aware LLM pipeline generates metamorphic relations for 142 AR repositories; hierarchical context plus agentic deliberation yields 3,760 refined MRs that human raters judge mostly valid and testable, with 5 case-study MRs detecting 16 injected faults.