首页> 外文会议>IEEE/ACM International Conference on Software Engineering: Software Engineering in Practice >Industry-scale IR-based Bug Localization: A Perspective from Facebook
【24h】

Industry-scale IR-based Bug Localization: A Perspective from Facebook

机译:业界规模的基于IR的错误本地化:来自Facebook的透视

获取原文

摘要

We explore the application of Information Retrieval (IR) based bug localization methods at a large industrial setting, Facebook. Facebook’s code base evolves rapidly, with thousands of code changes being committed to a monolithic repository every day. When a bug is detected, it is often time-sensitive and imperative to identify the commit causing the bug in order to either revert it or fix it. This is complicated by the fact that bugs often manifest with complex and unwieldy features, such as stack traces and other metadata. Code commits also have various features associated with them, ranging from developer comments to test results. This poses unique challenges to bug localization methods, making it a highly non-trivial operation.In this paper we lay out several practical concerns for industry-level IR-based bug localization, and propose Bug2Commit, a tool that is designed to address these concerns. We also assess the effectiveness of existing IR-based localization techniques from the software engineering community, and find that in the presence of complex queries or documents, which are common at Facebook, existing approaches do not perform as well as Bug2Commit. We evaluate Bug2Commit on three applications at Facebook: client-side crashes from the mobile app, server-side performance regressions, and mobile simulation tests for performance. We find that Bug2Commit outperforms the accuracy of existing approaches by up to 17%, leading to reduced time for triaging regressions and attributing bugs found in simulations.
机译:我们探讨信息检索(IR)基于Bug定位方法在大型工业环境中的应用。 Facebook的代码基础快速发展,数以千计的代码更改每天都会致电单片存储库。当检测到错误时,识别导致错误以恢复或修复它的提交通常是时分敏感和必要的。这一事实是,错误通常用复杂和笨重的功能(如堆栈迹线和其他元数据)明显的事实是复杂的。代码提交还具有与它们相关的各种功能,从开发人员注释范围到测试结果。这造成了对错误本地化方法的独特挑战,使其成为一个高度琐碎的操作。在本文中,我们为行业级的IR的错误本地化奠定了几个实际问题,并提出了一种旨在解决这些问题的工具。 。我们还评估了来自软件工程界的现有IR的本地化技术的有效性,并在存在复杂的查询或文档的情况下,在Facebook中常见,现有方法不会表现以及错误2.错误。我们在Facebook的三个应用程序中评估错误2:客户端崩溃从移动应用程序,服务器端性能回归和移动仿真测试进行性能。我们发现Bug2commit优于现有方法的准确性高达17%,导致在模拟中的三元回归和归属错误的时间减少。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号