{"slug": "correctness-firewalls-for-synthesized-database-components", "title": "Correctness Firewalls for Synthesized Database Components", "summary": "A paper submitted to arXiv on 3 November 2026 proposes \"correctness firewalls,\" lightweight design patterns that let coding agents synthesize database components that affect a system's performance but never its results. The authors present three case studies — cardinality estimation (advisory), searching sorted data (guarded), and data compression (certified) — and report that synthesized components search sorted data up to 3x faster than human-designed learned indexes and compress text 1.5x smaller than Zstd. The paper argues that a purely agentic approach does not automatically inherit decades of correctness guarantees, and outlines a research agenda for exploiting coding agents without giving them up.", "body_md": "# Computer Science > Databases\n\n  [Submitted on 3 Nov 2026]\n\n# Title:Correctness Firewalls for Synthesized Database Components\n\n[View PDF](https://arxiv.org/pdf/2611.05173)\n\nAbstract:For the first time in history, high-performance code is cheap. Today's coding agents can generate bespoke, instance-optimized data systems with excellent performance, and such agents will continue to improve as LLMs advance. But a purely agentic approach, even when validated with strong testing techniques, does not automatically inherit the correctness guarantees our community has spent decades building. We propose a middle ground between hand-crafted and agent-crafted systems: correctness firewalls, lightweight design patterns under which a synthesized component can affect a system's performance but never its results. Behind a correctness firewall, agents are free to synthesize fast components while the overall system remains correct. We present three case studies, each demonstrating a different type of firewall: cardinality estimation (advisory), searching sorted data (guarded), and data compression (certified). In early experiments, synthesized components search sorted data up to 3x faster than human-designed learned indexes and can compress text 1.5x smaller than Zstd. Drawing on these case studies, we outline a research agenda for how data management systems can exploit coding agents without giving up their hard-won correctness guarantees, from protecting synthesized code to measuring the cost of correctness.\n    \n\n### Additional Features\n\n### References & Citations\n\nLoading...\n\n# Bibliographic and Citation Tools\n\nBibliographic Explorer \n\n*(*[What is the Explorer?](https://info.arxiv.org/labs/showcase.html#arxiv-bibliographic-explorer))\nConnected Papers \n\n*(*[What is Connected Papers?](https://www.connectedpapers.com/about))\nLitmaps \n\n*(*[What is Litmaps?](https://www.litmaps.co/))\nscite Smart Citations \n\n*(*[What are Smart Citations?](https://www.scite.ai/))\n# Code, Data and Media Associated with this Article\n\nalphaXiv \n\n*(*[What is alphaXiv?](https://alphaxiv.org/))\nCatalyzeX Code Finder for Papers \n\n*(*[What is CatalyzeX?](https://www.catalyzex.com))\nDagsHub \n\n*(*[What is DagsHub?](https://dagshub.com/))\nGotit.pub \n\n*(*[What is GotitPub?](http://gotit.pub/faq))\nHugging Face \n\n*(*[What is Huggingface?](https://huggingface.co/huggingface))\nScienceCast \n\n*(*[What is ScienceCast?](https://sciencecast.org/welcome))\n# Demos\n\n# Recommenders and Search Tools\n\nInfluence Flower \n\n*(*[What are Influence Flowers?](https://influencemap.cmlab.dev/))\nCORE Recommender \n\n*(*[What is CORE?](https://core.ac.uk/services/recommender))\n# arXivLabs: experimental projects with community collaborators\n\narXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.\n\nBoth individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.\n\nHave an idea for a project that will add value for arXiv's community? [**Learn more about arXivLabs**](https://info.arxiv.org/labs/index.html).", "url": "https://wpnews.pro/news/correctness-firewalls-for-synthesized-database-components", "canonical_source": "https://arxiv.org/abs/2611.05173", "published_at": "2026-11-11 18:43:46+00:00", "updated_at": "2026-11-11 18:50:32.050842+00:00", "lang": "en", "topics": ["artificial-intelligence", "ai-agents", "ai-research", "developer-tools"], "entities": ["arXiv", "Zstd"], "also_reported_by": [], "alternates": {"html": "https://wpnews.pro/news/correctness-firewalls-for-synthesized-database-components", "markdown": "https://wpnews.pro/news/correctness-firewalls-for-synthesized-database-components.md", "text": "https://wpnews.pro/news/correctness-firewalls-for-synthesized-database-components.txt", "jsonld": "https://wpnews.pro/news/correctness-firewalls-for-synthesized-database-components.jsonld"}}