CloudEval-YAML: A Practical Benchmark for Cloud Configuration Generation

• URL: http://arxiv.org/abs/2401.06786v1
• Date: Fri, 10 Nov 2023 01:49:57 GMT
• Title: CloudEval-YAML: A Practical Benchmark for Cloud Configuration Generation
• Authors: Yifei Xu, Yuning Chen, Xumiao Zhang, Xianshang Lin, Pan Hu, Yunfei Ma, Songwu Lu, Wan Du, Zhuoqing Mao, Ennan Zhai, Dennis Cai
• Abstract summary: We present CloudEval-YAML, a practical benchmark for cloud configuration generation. The dataset consists of hand-written problems with unit tests targeting practical scenarios. The dataset consists of 1011 problems that take more than 1200 human hours to complete.
• Score: 9.320732264679238
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Among the thriving ecosystem of cloud computing and the proliferation of Large Language Model (LLM)-based code generation tools, there is a lack of benchmarking for code generation in cloud-native applications. In response to this need, we present CloudEval-YAML, a practical benchmark for cloud configuration generation. CloudEval-YAML tackles the diversity challenge by focusing on YAML, the de facto standard of numerous cloud-native tools. We develop the CloudEval-YAML benchmark with practicality in mind: the dataset consists of hand-written problems with unit tests targeting practical scenarios. We further enhanced the dataset to meet practical needs by rephrasing questions in a concise, abbreviated, and bilingual manner. The dataset consists of 1011 problems that take more than 1200 human hours to complete. To improve practicality during evaluation, we build a scalable evaluation platform for CloudEval-YAML that achieves a 20 times speedup over a single machine. To the best of our knowledge, the CloudEval-YAML dataset is the first hand-written dataset targeting cloud-native applications. We present an in-depth evaluation of 12 LLMs, leading to a deeper understanding of the problems and LLMs, as well as effective methods to improve task performance and reduce cost.

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