Development Progress

Project Timeline

Phase 1 — Literature Review & Research Foundation

• Studied MLIR compiler infrastructures and intermediate representations
• Analyzed existing AI-for-code and semantic reasoning benchmarks
• Investigated execution-grounded evaluation methodologies
• Explored compiler validation and transformation workflows
• Defined the research scope and benchmark objectives

Phase 2 — Mutation Agent Development

• Designed controlled semantic mutation strategies
• Implemented compiler-aware transformation workflows
• Developed mutation taxonomy across five mutation levels
• Added legality verification for generated mutations
• Integrated structured mutation metadata generation

Phase 3 — Execution Sandbox Agent Development

• Built isolated execution and validation environments
• Integrated MLIR, Torch-MLIR, LLVM, and IREE pipelines
• Implemented deterministic runtime behavior analysis
• Added compilation failure and divergence detection
• Generated execution-grounded semantic labels

Phase 4 — LLM Reasoning Agent Development

• Integrated LLM-based semantic reasoning workflows
• Developed execution-blind reasoning evaluation pipelines
• Implemented semantic divergence interpretation tasks
• Added structured reasoning prompt generation
• Evaluated reasoning consistency across mutations

Phase 5 — Judge Agent Development

• Designed execution-grounded reasoning evaluation workflows
• Implemented semantic correctness scoring mechanisms
• Added hallucination and faithfulness analysis
• Compared reasoning outputs against runtime behavior
• Generated benchmark evaluation metrics and labels

Phase 6 — Dataset Generation & Benchmark Evaluation

• Generated large-scale semantic mutation datasets
• Executed benchmark evaluation across multiple models
• Collected reasoning accuracy and divergence metrics
• Organized benchmark artifacts and evaluation outputs
• Prepared datasets and experimental results for publication and release