LLM-based SE tools lack stable ground truth and deterministic outputs, making standard evaluation assumptions invalid and requiring new approaches for reliable assessment.
Exploring large language models for code explanation
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Survey of 188 engineers using SEM finds that UTAUT2 constructs influence LLM adoption differently across five SE purposes, with some factors showing negative effects when examined in isolation.
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Evaluation of LLM-Based Software Engineering Tools: Practices, Challenges, and Future Directions
LLM-based SE tools lack stable ground truth and deterministic outputs, making standard evaluation assumptions invalid and requiring new approaches for reliable assessment.
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Exploring Individual Factors in the Adoption of LLMs for Specific Software Engineering Purposes
Survey of 188 engineers using SEM finds that UTAUT2 constructs influence LLM adoption differently across five SE purposes, with some factors showing negative effects when examined in isolation.