[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"branding":3,"analytics":7,"article-researchers-split-code-translation-into-three-ai-agents":10,"sections":35},{"siteName":4,"siteTagline":5,"publisherName":4,"contactEmail":6},"The Revision","Tech news, decoded.","editor@therevision.news",{"gaMeasurementId":8,"adsenseClientId":9},"G-ZW2MV82GYR","ca-pub-8533917693782264",{"article":11},{"id":12,"slug":13,"title":14,"dek":15,"body_md":16,"tags_json":17,"published_at":18,"created_at":19,"updated_at":20,"status":21,"review_note":22,"review_notes":23,"image_url":22,"persona_id":22,"persona_name":22,"section":24,"tags":25,"sources":30,"feedback":34,"feedback_at":22,"cost_usd":34,"total_tokens":34},8122,"researchers-split-code-translation-into-three-ai-agents","Researchers Split Code Translation Into Three AI Agents","BabelCoder assigns separate AI agents to translate, test, and fix code, beating prior methods by up to 13.5 percent across four benchmarks.","A new research framework called BabelCoder splits code translation across three specialized AI agents instead of relying on one model to do everything.\n\nBabelCoder assigns one agent to generate translated code, a second to test it against the original program's behavior, and a third to repair whatever breaks. Researchers evaluated the system on four benchmark datasets against four existing state-of-the-art translation methods. BabelCoder won by 0.5 to 13.5 percent in 94 percent of test cases, reaching an average accuracy of 94.16 percent.\n\nCode migration - moving an app from Python to Go, or modernizing a legacy system - is tedious, expensive, and easy to get subtly wrong. Splitting the job into generate, test, and repair roles mirrors how a careful engineer actually works, and the accuracy gain suggests structured decomposition, not just bigger models, is where translation quality is headed.\n\nA 94 percent benchmark score is tidy, but these test suites are far cleaner than the sprawling, dependency-heavy codebases most companies actually want to migrate - so this reads as a promising lab result, not a tool you hand your legacy stack to yet.","[\"ai agents\",\"code translation\",\"developer tools\",\"llm\"]","2026-09-28T04:00:00.000Z","2026-09-28T10:18:57.750Z","2026-09-28T10:19:04.601Z","published",null,[],"ai",[26,27,28,29],"ai agents","code translation","developer tools","llm",[31],{"name":32,"url":33},"arXiv cs.AI","https:\u002F\u002Farxiv.org\u002Fabs\u002F2512.06902",0,{"sections":36},[37,40,44,49,54,59,63,68,73,78,83,88,92,97],{"name":38,"slug":24,"count":39,"latest_published_at":18},"AI",4794,{"name":41,"slug":42,"count":43,"latest_published_at":18},"Security","security",762,{"name":45,"slug":46,"count":47,"latest_published_at":48},"Policy","policy",399,"2026-09-27T18:39:02.000Z",{"name":50,"slug":51,"count":52,"latest_published_at":53},"Deals","deals",261,"2026-09-27T15:30:35.000Z",{"name":55,"slug":56,"count":57,"latest_published_at":58},"Hardware","hardware",188,"2026-09-27T20:46:36.000Z",{"name":60,"slug":61,"count":62,"latest_published_at":18},"Science","science",151,{"name":64,"slug":65,"count":66,"latest_published_at":67},"Consumer Tech","consumer-tech",135,"2026-09-26T14:30:00.000Z",{"name":69,"slug":70,"count":71,"latest_published_at":72},"Software","software",91,"2026-09-25T20:55:00.000Z",{"name":74,"slug":75,"count":76,"latest_published_at":77},"Dev Tools","dev-tools",84,"2026-09-26T04:20:58.000Z",{"name":79,"slug":80,"count":81,"latest_published_at":82},"Startups","startups",76,"2026-09-25T18:33:59.000Z",{"name":84,"slug":85,"count":86,"latest_published_at":87},"Gaming","gaming",48,"2026-09-25T18:35:21.000Z",{"name":89,"slug":90,"count":86,"latest_published_at":91},"General","general","2026-09-26T17:02:42.000Z",{"name":93,"slug":94,"count":95,"latest_published_at":96},"Reviews","reviews",30,"2026-09-24T20:07:31.000Z",{"name":98,"slug":99,"count":100,"latest_published_at":101},"How-To","how-to",6,"2026-06-16T09:00:00.000Z"]