RubberDuck provides a semantic verification layer designed to increase certainty in software engineering workflows involving LLM-based tools. By building comprehensive models of an entire codebase—including module boundaries, call chains, and data flows—it helps developers understand connections, locate bugs with evidence, review pull requests for wider impact, and generate contextually accurate patches.
- Achieved 77.33% Pass@1 on SWE-bench Lite.
- Includes Codebase Atlas to enable rapid repo onboarding through graph-verified maps.
- Employs "Fit Packs" to ensure generated code adheres to architectural patterns and avoids dependency cycles.
- Achieved 77.33% Pass@1 on SWE-bench Lite.
- Includes Codebase Atlas to enable rapid repo onboarding through graph-verified maps.
- Employs "Fit Packs" to ensure generated code adheres to architectural patterns and avoids dependency cycles.
This article explores how to represent sentences as graphs, moving beyond traditional semantic modeling to a more natural-language oriented approach using reification and context graphs. It demonstrates how to translate sentences into RDF, Turtle, Open Cypher, and JSON-LD, highlighting the benefits of reification for capturing nuanced information and creating cleaner, more intuitive knowledge representations.
