PersonaCodeBench: Evaluating Coding Agents in Persona-driven Human-Interactive Sessions
arXiv cs.AIen
arXiv cs.AI
AI Global WirearXiv:2611.05739v1 Announce Type: new Abstract: Coding agents must deliver correct software while respecting users' expertise, preferences, and working conditions. Existing benchmarks increasingly incorporate interaction, yet personalized requirement fulfillment remains underexplored. We introduce PersonaCodeBench, which turns user characteristics into verifiable obligations in persona-driven multi-turn coding sessions. Our persona pool spans roles, technical abilities, interaction preferences, and practical constraints, yielding task-grounded evolved requirements for implementation, permissions, testing, explanation, and delivery. At runtime, a controller governs user simulator responses an
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