Software bugs occur at different rate depending on the characteristic of the software systems. Automatically collecting bugs from online or offline source (e.g., issue repositories) and visualising them over time help to understand the reliability of the system and to predict its future behaviour. We offer to develop a simple tool that mines the repository and visualises optimal curves representing the occurrences of bugs over time will be developed._
A dataset of bugs with their occurrence time stamps or an online bug repository (e.g., Jira).
A Java - R application that connects to the repository or the dataset and visualises both bugs over time and the optimal curve representing their cumulative number.
The costs amount to 5.000€+VAT. You can also take advantage of the Lab bonus, which covers 50% to 65% of the incurred costs.
Barbara Russo is professor of computer science at the Free University of Bozen/Bolzano and vice-dean for research. She holds a PhD in pure mathematics from the University of Trento. She was visiting researcher at the Max-Plank-Institut für Mathematik, Bonn and the University of Liverpool. She has published 150 papers in pure mathematics and computer science with more than 2100 citations. She is a reviewer for leading software and systems engineering journals and conferences. Her recent research focuses on artificial intelligence for the creation, design and development of innovative software systems. Find out more about her checking out his website.
We have created a diagram that displays common keywords from articles written by Barbara Russo. This is often useful to see what the respective researcher is doing: click here.
Software engineering, Machine learning