RAMP: A New Benchmark for Evaluating AI Agents in Real-World Software Engineering
RAMP has been unveiled by researchers as a production-oriented framework designed for evaluating long-horizon software engineering agents. This system is built on the YatCC integrated platform, offering a cohesive runtime assessment structure through standardized execution and orchestration interfaces. It incorporates realistic workloads for compiler construction that feature serial dependencies and intricate toolchain interactions, as well as a staged recovery mechanism. RAMP seeks to overcome the shortcomings of current evaluation methods, which depend on static, isolated, and short-term benchmarks that do not adequately represent the dynamic complexities of actual production workflows. The goal is to provide a more accurate reflection of practical capabilities in realistic runtime scenarios, including long execution chains and iterative feedback loops.
Key facts
- RAMP is a production-grounded infrastructure for assessing long-horizon software engineering agents.
- It is built upon the YatCC integrated platform.
- RAMP provides a unified runtime assessment architecture through standardized orchestration and execution interfaces.
- It introduces realistic compiler-construction workloads with serial dependencies and complex toolchain interactions.
- RAMP includes a staged recovery mechanism.
- Existing evaluation methodologies rely on static, isolated, and short-horizon benchmarks.
- RAMP aims to capture the dynamic complexity of real-world production workflows.
- The system evaluates agents under realistic runtime environments with long execution chains, tool interactions, dependency management, and iterative feedback loops.
Entities
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