CausalSE applies SCMs and propensity score matching to reveal that causal analysis of prompt engineering on GPT-3 code generation often finds no significant effect where associational analysis suggests improvement.
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A systematic literature review that organizes recent work on LLMs for code generation into a taxonomy covering data curation, model advances, evaluations, ethics, environmental impact, and applications, with benchmark comparisons.
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Rethinking Software Empirical Studies with Structural Causal Models
CausalSE applies SCMs and propensity score matching to reveal that causal analysis of prompt engineering on GPT-3 code generation often finds no significant effect where associational analysis suggests improvement.
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A Survey on Large Language Models for Code Generation
A systematic literature review that organizes recent work on LLMs for code generation into a taxonomy covering data curation, model advances, evaluations, ethics, environmental impact, and applications, with benchmark comparisons.