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A complexity-aware framework for evaluating LLM code comprehension using cyclomatic complexity, nesting depth, branching factor, and Halstead volume demonstrates that complexity-aware evaluation provides a more diagnostic assessment of LLM code-comprehension reliability than aggregate accuracy alone.
Behavior-Driven Development (BDD) scenarios coexist with large volumes of semi-structured records (e.g., documentation, issues, informal feature descriptions), and keeping the two synchronized is laborintensive. We present a study of bidirectional generation 11https://github.com/Artin-Biniek/Submission-Project between...
The findings provide practical guidelines for selecting augmentation techniques that maximize test diversity while preserving realistic image characteristics, thereby enabling the construction of comprehensive and effective test suites for image retrieval systems while reducing the cost of manual data labeling through...
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