No abstract

No abstract

No abstract

It has been claimed that the advent of user-generated content has reshaped the way people approached all sorts of content realization projects, being multimedia (YouTube, DeviantArt, etc.), knowledge (Wikipedia, blogs), to software in general, when based on a more general Open Source model. After many years of research and evidence, several studies have demonstrated that Open Source Software (OSS) portals often contain a large amount of software projects that simply do not evolve, often developed by relatively small communities, and that still struggle to attract a sustained number of contributors. In terms of such content, the "tragedy" appears to be that the user demand for content and the offer of experts contributing content are on curves with different slopes, with the demand growing more quickly.In this paper we argue that, even given the differences in the requested expertise, many projects reliant on user-contributed content and expertise undergo a similar evolution, along a logistic growth: a first slow growth rate is followed by a much faster evolution growth. When a project fails to attract more developers i.e. contributors, the evolution of project's content does not present the "explosive growth" phase, and it will eventually "burnout", and the project appears to be abandoned. Far from being a negative finding, even abandoned project's content provides a valuable resource that could be reused in the future within other projects.

Novice programmers often encounter difficulties performing debugging tasks effectively. Even if modern development environments (IDEs) provide high-level support for navigating through code elements and for identifying the right conditions leading to the bug, debugging still requires considerable human effort. Programmers usually have to make hypotheses that are based on both program state evolution and their past debugging experiences. To mitigate this effort and allow novice programmers to gain debugging experience quickly, we propose an approach based on the reuse of existing bugs of open source systems to provide informed guidance from the failure site to the fault position. The goal is to help novices in reasoning on the most promising paths to follow and conditions to define. We implemented this approach as a tool that exploits the knowledge about fault and bug position in the system, as long as any bug of the system is known. The effectiveness of the proposed approach is validated through a quasi-experiment that qualitatively and quantitatively evaluates how the debugging performances of the students change when they are trained using the tool.