SlopCodeBench: Benchmarking How Coding Agents Degrade Over Long-Horizon Iterative Tasks

1. 1Identify the limitations of existing agentic coding benchmarks
2. 2Design a language-agnostic benchmark that allows for flexible design decisions
3. 3Evaluate coding agents' performance over long-horizon iterative tasks
4. 4Analyze the degradation of code quality and its impact on future extensions

Software engineers and AI researchers benefit from SlopCodeBench as it helps evaluate coding agents' performance in iterative tasks, informing the development of more efficient and effective coding tools

💡 Coding agents' performance degrades over long-horizon iterative tasks, highlighting the need for benchmarks that evaluate code quality beyond single-shot solutions

🤖 Benchmarking coding agents' degradation over time 📊