Learn More
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(More)
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(More)
The information in bug reports influences the speed at which bugs are fixed. However, bug reports differ in their quality of information. We conducted a survey among ECLIPSE developers to determine the information in reports that they widely used and the problems frequently encountered. Our results show that steps to reproduce and stack traces are most(More)
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(More)
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(More)
—Current research on code clones tries to address the question whether or not code clones are harmful for the quality of software. As most of these studies are based on the fine-grained analysis of inconsistent changes at the revision level, they capture much of the chaotic and experimental nature inherent to any ongoing software development process.(More)
Much research energy in software engineering is focused on the creation of effort and defect prediction models. Such models are important means for practitioners to judge their current project situation, optimize the allocation of their resources, and make informed future decisions. However, software engineering data contains a large amount of variability.(More)
Software monitoring systems have high performance overhead because they typically monitor all processes of the running program. For example, to capture and replay crashes, most current systems monitor all methods; thus yielding a significant performance overhead. Lowering the number of methods being monitored to a smaller subset can dramatically reduce this(More)
—Correcting software defects accounts for a significant amount of resources such as time, money and personnel. To be able to focus testing efforts where needed the most, researchers have studied statistical models to predict in which parts of a software future defects are likely to occur. By studying the mathematical relations between predictor variables(More)
To study the impact of code clones on software quality, researchers typically carry out their studies based on fine-grained analysis of inconsistent changes at the revision level. As a result, they capture much of the chaotic and experimental nature inherent in any ongoing software development process. Analyzing highly fluctuating and short-lived clones is(More)