arXiv CS
open access
GTDD: Generative Test-Driven Development for AI Coding Agents with Adversarial Testing
Test-driven development gives AI coding agents executable requirements for implementing software. Because these agents can adapt their implementations to the examples they observe, passing a predetermined collection of tests can leave substantial parts of the intended behavior unimplemented. We prop
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- GTDD: Generative Test-Driven Development for AI Coding Agents with Adversarial Testing#1187630
- CodeForge-MA: Execution-Verified Multi-Agent Learning with Language-Conditioned LoRA for Multilingual Code Generation#1201494
- Breaking, Stale, or Missing? Benchmarking Coding Agents on Project-Level Test Evolution#168382
- Test vs Mutant: Adversarial LLM Agents for Robust Unit Test Generation#819299
- Test vs Mutant: Adversarial LLM Agents for Robust Unit Test Generation#809306
Record · ID 1181706
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive