A Context-Aware Platform for Evaluating LLM-Generated Backend Applications
Large Language Models (LLMs) are now widely used for code generation, yet even syntactically correct output may contain logical and semantic errors that remain invisible until runtime, particularly in framework-driven applications, where correctness depends on dependency injection, framework conventions, configuration,...