Bug Reports

To ensure quality of software systems, developers use bug reports to track defects. It is in the interest of users and developers that bug reports provide the necessary information to ease the fixing process. Past research found that users do not provide the information that developers deem ideally useful to fix a bug. This raises an interesting question: What is the satisficing information to speed up the bug fixing process? We conducted an observational study on the relation between provided report information and its lifetime, considering more than 650,000 reports from open-source systems using popular bug trackers. We distilled a meta-model for a minimal bug report, establishing a basic layer of core features. We found that few fields influence the resolution time and that customized fields have little impact on it. We performed a survey to investigate what users deem easy to provide in a bug report.

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.