This study analyzes how developers evolve prompts in LLM applications by examining 1,262 prompt changes across 243 GitHub repositories, revealing patterns in prompt engineering practices.
https://arxiv.org/abs/2412.17298
⚡ Methods of this Paper:
→ The researchers analyzed GitHub repositories to track prompt evolution patterns, focusing on change types, documentation, and impact on system behavior.
→ They developed a comprehensive methodology combining qualitative analysis of prompt changes with automated tools to detect inconsistencies.
→ The study classified prompt changes into component-dependent (additions, modifications, removals) and component-independent (rephrasing, formatting) categories.
→ They evaluated prompt changes against software maintenance activities like feature development, bug fixing, and refactoring.
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💡 Key Insights:
→ Most prompt changes (64.4%) directly affect specific components through additions and modifications
→ Only 21.9% of prompt changes are documented in commit messages
→ Feature development accounts for 59.7% of prompt changes
→ Developers prioritize refining instructions over structural changes
→ Prompt modifications don't consistently achieve intended effects on LLM responses
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📊 Results:
→ 30.1% of changes were additions to existing prompts
→ 25.5% involved semantic modifications
→ 17.4% focused on rephrasing without changing meaning
→ 15 instances of logical inconsistencies detected in prompt changes
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