The severity of a reported bug is a critical factor in deciding how soon it needs to be fixed. Unfortunately, while clear guidelines exist on how to assign the severity of a bug, it remains an inherent manual process left to the person reporting the bug. In this paper we investigate whether we can accurately predict the severity of a reported bug by analyzing its textual description using text mining algorithms. Based on three cases drawn from the open-source community (Mozilla, Eclipse and GNOME), we conclude that given a training set of sufficient size (approximately 500 reports per severity), it is possible to predict the severity with a reasonable accuracy (both precision and recall vary between 0.65-0.75 with Mozilla and Eclipse; 0.70-0.85 in the case of GNOME).
Reverse engineering is the process of uncovering the design and the design rationale from a functioning software system. Reverse engineering is an integral part of any successful software system, because changing requirements lead to implementations that drift from their original design. In contrast to traditional reverse engineering techniques -which analyse a single snapshot of a system-we focus the reverse engineering effort by determining where the implementation has changed. Since changes of objectoriented software are often phrased in terms of refactorings, we propose a set of heuristics for detecting refactorings by applying lightweight, object-oriented metrics to successive versions of a software system. We validate our approach with three separate case studies of mature object-oriented software systems for which multiple versions are available. The case studies suggest that the heuristics support the reverse engineering process by focusing attention on the relevant parts of a software system.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.