Learn More
While the users of completed applications are heavily moving from desktop to the web browser, the majority of developers are still working with desktop IDEs such as Eclipse or Visual Studio. In contrast to professional installable IDEs, current web-based code editors are simple text editors with extra features. They usually understand lexical syntax and can(More)
All material supplied via TUT DPub is protected by copyright and other intellectual property rights, and duplication or sale of all or part of any of the repository collections is not permitted, except that material may be duplicated by you for your research use or educational purposes in electronic or print form. You must obtain permission for any other(More)
Massive Open Online Courses (MOOCs) have rapidly become an important tool for educational institutes in teaching programming. Nevertheless, high drop-out rates have always been a problem in online learning. As MOOCs have become an important part of modern education, reducing the drop-out rate has become a more and more relevant research problem. This work(More)
This paper studies how useful the standard 2-norm regularized SVM is in approximating the 1-norm SVM problem. To this end, we examine a general method that is based on iteratively re-weighting the features and solving a 2-norm optimization problem. The convergence rate of this method is unknown. Previous work indicates that it might require an excessive(More)
While the popularity of web applications is growing, most of the software is still developed using desktop tools. Nevertheless, a browser-based development environment could offer a multitude of advantages. For example, only an up-to-date web browser is needed and therefore the user has no need to carry out complex tool installation and update procedures.(More)
Methods for learning decision rules are being successfully applied to many problem domains, especially where understanding and interpretation of the learned model is necessary. In many real life problems, we would like to predict multiple related (nominal or numeric) target attributes simultaneously. Methods for learning rules that predict multiple targets(More)
Software engineering has both technological and social dimensions. As development teams spanning across the globe are increasingly the norm and while the web enables massive online collaboration, there is a growing need for effective collaboration tools. In this paper, we describe experiences on collaborative programming as a tool for learning software(More)
We propose a well-founded method of ranking a pool of m trained classifiers by their suitability for the current input of n instances. It can be used when dynamically selecting a single classifier as well as in weighting the base classifiers in an ensemble. No classifiers are executed during the process. Thus, the n instances, based on which we select the(More)