祸不单行:CrowdStacking追踪帮助发现问题

Tommaso Dal Sasso, Andrea Mocci, Michele Lanza
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引用次数: 4

摘要

在软件开发过程中,异常绝不是例外:程序员反复尝试和测试他们的代码,以确保它按预期工作。在此过程中,会引发运行时异常,指出各种问题,例如API的不当使用、复杂的代码以及缺陷。这样的失败会导致堆栈跟踪,堆栈跟踪是由导致程序中断的方法调用序列组成的列表。堆栈跟踪对调试源代码很有用,如果共享,还可以提高bug报告的质量。然而,它们是手动和单独处理的,而我们认为它们可以自动和集体地利用,以实现我们所说的“众堆”,即在整个开发社区的规模上自动收集堆栈跟踪。我们展示了我们的众包方法,由Shore-Line Reporter支持,这是一个在程序开发和执行期间无缝收集堆栈跟踪并将其存储在中央存储库中的工具。我们说明了如何利用来自几个开发人员的ide的数千个堆栈跟踪来识别涉及故障的代码中的常见热点,使用这些知识来检索相关的和相关的错误报告,并为开发人员提供一个有效的、即时的问题上下文。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Misery loves company: CrowdStacking traces to aid problem detection
During software development, exceptions are by no means exceptional: Programmers repeatedly try and test their code to ensure that it works as expected. While doing so, runtime exceptions are raised, pointing out various issues, such as inappropriate usage of an API, convoluted code, as well as defects. Such failures result in stack traces, lists composed of the sequence of method invocations that led to the interruption of the program. Stack traces are useful to debug source code, and if shared also enhance the quality of bug reports. However, they are handled manually and individually, while we argue that they can be leveraged automatically and collectively to enable what we call crowdstacking, the automated collection of stack traces on the scale of a whole development community. We present our crowdstacking approach, supported by Shore-Line Reporter, a tool which seamlessly collects stack traces during program development and execution and stores them on a central repository. We illustrate how thousands of stack traces stemming from the IDEs of several developers can be leveraged to identify common hot spots in the code that are involved in failures, using this knowledge to retrieve relevant and related bug reports and to provide an effective, instant context of the problem to the developer.
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