Test Execution Logs Data for LLM Benchmarking for Root Cause Analysis

The test execution logs are obfuscated to enhance privacy. To replicate our experiment:

Log in through the OpenRouter website, 

Navigate to the “Chat” tab,

Select and add desired language models. In this case: Aion-1.0, DeepSeek R1, DeepSeek V3 0324, Mistral Small 3.1 24B, GPT o3-mini, Gemini 2.5 Pro Experimental, and QwB 32B,

Input the following prompt and the corresponding log (one log at a time) into the chat interface:

You are a debugging assistant. Given the following information:    1. A test execution log2. A list of possible root causes    Your task is to:- Provide a step-by-step reasoning to analyze the failure- Select the most likely root cause (only one) from the list- Suggest a reasonable action or next step to resolve it- Output the result in JSON format as shown below    ---Log File:{"<log-file-name>"}    Possible Root Causes:{ "misconfiguration", "signal_timeout", "test_aborted", "expired_bugfix", "unknown" }    Respond strictly in the following JSON format:{{   "File name": "{file_name}",   "Step-by-steps reasoning": "1. ...\n2. ...\n3. ...",   "Root cause": "<select one from above>",   "Action suggestion": "..."}}

Lastly, read the response directly in the chat box, or export it to JSON for later analysis.

Note:

Sometimes, one of the language models fail to generate the response. In this case, a retry is needed until the language model successfully generate the response.

本数据集的测试执行日志已进行混淆处理以强化隐私保护。若需复现本实验，请遵循以下步骤：
1. 通过OpenRouter网站完成登录；
2. 导航至「聊天」标签页；
3. 选择并添加所需的语言模型，本次实验选用的模型包括：Aion-1.0、DeepSeek R1、DeepSeek V3 0324、Mistral Small 3.1 24B、GPT o3-mini、Gemini 2.5 Pro Experimental 及 QwB 32B。

将下述提示词与单条对应测试执行日志依次输入至聊天界面：

你是一名调试助手，需基于以下两类信息开展工作：
1. 测试执行日志
2. 潜在根因列表

你的任务为：
- 逐步推理分析故障成因
- 从给定列表中选出唯一最具可能性的根因
- 提出合理的解决方案或后续操作步骤
- 严格按照以下JSON格式输出结果：
---
日志文件：{"<日志文件名>"}
潜在根因列表：{ "配置错误（misconfiguration）", "信号超时（signal_timeout）", "测试中止（test_aborted）", "修复包过期（expired_bugfix）", "未知（unknown）" }
请严格遵循如下JSON格式回复：
{
"文件名": "{file_name}",
"分步推理过程": "1. ...
2. ...
3. ...",
"根因": "<从上述列表中选取其一>",
"操作建议": "..."
}

最后，若某语言模型未能成功生成回复，请重试直至其完成有效输出。