"Coding agents powered by large language models excel in software engineering tasks, yet comprehensive performance evaluation remains a significant challenge across diverse programming languages and real-world scenarios."
"Amazon's SWE-PolyBench marks a significant advancement in assessing AI coding agents, introducing rich metrics for evaluation across complex codebases and multiple programming languages."
The article discusses the challenges of evaluating the performance of coding agents powered by large language models across various programming languages. While previous benchmarks like SWE-Bench have made significant strides, they are limited by their focus on Python and specific task types. In response, Amazon has launched SWE-PolyBench, the first industry benchmark that assesses AI coding agents' abilities to navigate complex codebases across four programming languages. SWE-PolyBench includes various metrics like pass rates and precision to provide a deeper understanding of coding agents' performance in real-world scenarios.
Read at Amazon Web Services
Unable to calculate read time
Collection
[
|
...
]