{
  "id": 16002026,
  "title": "SWE-DIVE: Multi-Turn Coding Agent Evaluation with Dynamic User Simulation",
  "url": "https://urgent.news/2026/10/21/swe-dive-multi-turn-coding-agent-evaluation-with-dynamic-user",
  "topic": "ai",
  "section": "AI",
  "published": "2026-10-21T17:06:34.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2610.30047v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Coding agents are typically evaluated using one-shot, well-formulated prompts. Benchmarks such as SWE-bench use existing GitHub issues as input for a coding agent and evaluate whether the agent successfully solves the task. However, in real-world use cases, prompts are often not as well-formulated or structured as existing GitHub issues. Additionally, a coding agent session is not limited to a…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}