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JioHotstar Benchmarks Knowledge Bases for AI Coding Agents

Source: InfoQ ·

JioHotstar evaluated 6 approaches to code retrieval for AI coding agents using SWE, CodeScale Bench, and an internal question-answering harness. Structural search performed well on concrete tasks, while semantic retrieval helped with ambiguous requirements. The findings highlight trade-offs in accuracy, token use, and tool design, underscoring the need to match retrieval tools to task types. By Leela Kumili

What is JioHotstar Benchmarks Knowledge Bases for AI Coding Agents?

JioHotstar Benchmarks Knowledge Bases for AI Coding Agents is a article discovery curated from InfoQ. JioHotstar evaluated 6 approaches to code retrieval for AI coding agents using SWE, CodeScale Bench, and an internal question-answering harness. Structural search performed well…

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