CDDRefactorER constrains AI-driven refactoring using Cognitive-Driven Development rules to cut failures by 54-71% and raise novice comprehension scores by 22-31%.
2018.Refactoring: improving the design of existing code
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An AI-native TDD framework operationalizes classical TDD principles as prompt-level and workflow-level governance mechanisms in a layered multi-agent architecture to improve stability and reproducibility of LLM code generation.
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Improving Code Comprehension through Cognitive-Load Aware Automated Refactoring for Novice Programmers
CDDRefactorER constrains AI-driven refactoring using Cognitive-Driven Development rules to cut failures by 54-71% and raise novice comprehension scores by 22-31%.
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TDD Governance for Multi-Agent Code Generation via Prompt Engineering
An AI-native TDD framework operationalizes classical TDD principles as prompt-level and workflow-level governance mechanisms in a layered multi-agent architecture to improve stability and reproducibility of LLM code generation.