The use of AI models in programming enhances code generation speed but simultaneously increases the burden of checking code correctness. Users often develop heuristics to balance the time saved by AI-generated suggestions against the effort required for validation. This shift alters traditional programming practices as authors face a choice between accepting lower-effort code and ensuring quality. The implications of this balance impact system usability and the effectiveness of code generation tools, leading programmers to focus on shorter code completions for practical reasons.
When code can be generated quickly, checking the correctness of the generated code becomes a major bottleneck, shifting priorities between system efficiency and programmer effort.
Users have developed heuristics to evaluate the cost of checking code versus the time saved in code generation, prioritizing shorter completions for efficiency.
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