New project “ESSENTIALS – People-Centric Essentials for Software Evolution” was accepted by the SNF / www.snf.ch. The project is in collaboration with Prof. Michele Lanza from the University of Lugano (USI) and will fund 4 PhD students.
Monthly Archives: March 2014
Assessing Task Difficulty in Software Development
Knowing how hard a software development task is as it is being performed can be helpful for many reasons. For instance, the estimate for completing a task might be revised or the likelihood of a bug occurring the source code might be predicted. Furthermore, a real time task difficulty classification could be used to stop software developers when they experience difficulties and prevent them from introducing bugs into the code.
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Our paper “A Dictionary to Translate Change Tasks to Source Code” has been accepted for MSR 2014
We are excited to announce that our paper “A Dictionary to Translate Change Tasks to Source Code” has been accepted for the 11th Working Conference on Mining Software Repositories (MSR 2014). In the paper, we present a novel approach for static concept location, which translates change tasks into source code elements via a dictionary. We demonstrate in an empirical analysis on four open source projects its effectiveness and improvement over a traditional static concept location approach.
Our paper “Automatic Search Term Identification for Change Tasks” was accepted for publication at the ICSE 2014 NIER track
We are excited to announce that our paper “Automatic Search Term Identification for Change Tasks” was accepted in the New Ideas and Emerging Results (NIER) track of the 36th International Conference on Software Engineering. In this research we investigated whether we can support developers in finding good search terms to query the source code in order to locate relevant places for a given change task. Based on existing work and an analysis of change tasks, we determined a set of heuristics for the identification of good search terms and analyzed their predictive value through logistic regression. Based on these results we developed a general and easy applicable approach that automatically identifies good search terms within a change task.
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