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P2 Tuning backfired? not (always) your fault: understanding and detecting configuration-related performance bugs

调优适得其反?不(总是)你的错:理解并检测配置相关的性能缺陷
FSE Proceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering2019匹配度 2/10 · 该论文研究配置调优作为性能缺陷检测的测试预言,属于软件测试与调试方向,不涉及静态分析、LLM/Agent、浮点程序分析或贝叶斯程序分析,与用户研究方向关联较弱。引用 3 inbox
Haochen He
crossref: 2026-09-12

AI 速览

一句话:提出将配置调优作为性能缺陷检测的通用测试预言,并分析配置相关性能缺陷。

性能缺陷由于通常不会导致程序失败停止,难以被检测;现有调试技术只能发现具有已知模式的性能问题(如低效循环),其关键瓶颈在于缺少通用的测试预言。本文主张配置调优可以成为性能缺陷检测的强候选方案。其依据有两点:已有工作表明大多数性能缺陷与配置相关;调优过程反映了用户对性能变化的预期。如果调优后的实际性能表现与用户直觉不符,那么相关代码段很可能存在问题。论文据此提出理解与检测配置相关性能缺陷的思路,但摘要未给出具体实现细节与实验评估结果。

问题
性能缺陷缺乏通用测试预言,且症状非失败停止,导致现有调试技术只能检测已知模式的性能问题。
方法
提出以配置调优作为性能缺陷检测的 oracle:将调优后实际性能与用户预期进行对比,从而定位可能包含性能问题的代码段。
评估
摘要未报告具体实验或评估结果,主要通过已有工作观察和调优反映用户预期的论证来支持该检测思路。
原文摘要(Abstract)

Performance bugs (PBugs) are often hard to detect due to their non fail-stop symptoms. Existing debugging techniques can only detect PBugs with known patterns (e.g. inefficient loops). The key reason behind this incapability is the lack of a general test oracle. Here, we argue that the configuration tuning can serve as a strong candidate for PBugs detection. First, prior work shows that most performance bugs are related to configurations. Second, the tuning reflects users’ expectation of performance changes. If the actual performance behaves differently from the users’ intuition, the related code segment is likely to be problematic.

链接与引用

DOI 原文 ·

BibTeX
@inproceedings{paperbot5034,
  title = {Tuning backfired? not (always) your fault: understanding and detecting configuration-related performance bugs},
  author = {Haochen He},
  booktitle = {FSE},
  year = {2019},
  doi = {10.1145/3338906.3342498}
}