In software development, bug reports provide crucial information to developers. However, these reports widely differ in their quality. We conducted a survey among developers and users of APACHE, ECLIPSE, and MOZILLA to find out what makes a good bug report.The analysis of the 466 responses revealed an information mismatch between what developers need and what users supply. Most developers consider steps to reproduce, stack traces, and test cases as helpful, which are at the same time most difficult to provide for users. Such insight is helpful to design new bug tracking tools that guide users at collecting and providing more helpful information.Our CUEZILLA prototype is such a tool and measures the quality of new bug reports; it also recommends which elements should be added to improve the quality. We trained CUEZILLA on a sample of 289 bug reports, rated by developers as part of the survey. In our experiments, CUEZILLA was able to predict the quality of 31-48% of bug reports accurately.

In a survey we found that most developers have experienced duplicated bug reports, however, only few considered them as a serious problem. This contradicts popular wisdom that considers bug duplicates as a serious problem for open source projects. In the survey, developers also pointed out that the additional information provided by duplicates helps to resolve bugs quicker. In this paper, we therefore propose to merge bug duplicates, rather than treating them separately. We quantify the amount of information that is added for developers and show that automatic triaging can be improved as well. In addition, we discuss the different reasons why users submit duplicate bug reports in the first place.

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In software engineering experiments, the description of bug reports is typically treated as natural language text, although it often contains stack traces, source code, and patches. Neglecting such structural elements is a loss of valuable information; structure usually leads to a better performance of machine learning approaches. In this paper, we present a tool called infoZilla that detects structural elements from bug reports with near perfect accuracy and allows us to extract them. We anticipate that infoZilla can be used to leverage data from bug reports at a different granularity level that can facilitate interesting research in the future.

Abstract-A widely shared belief in the software engineering community is that stack traces are much sought after by developers to support them in debugging. But limited empirical evidence is available to confirm the value of stack traces to developers. In this paper, we seek to provide such evidence by conducting an empirical study on the usage of stack traces by developers from the ECLIPSE project. Our results provide strong evidence to this effect and also throws light on some of the patterns in bug fixing using stack traces. We expect the findings of our study to further emphasize the importance of adding stack traces to bug reports and that in the future, software vendors will provide more support in their products to help general users make such information available when filing bug reports.