Speaker: Alessandra Gorla , IMDEA, Spain
Area: App Mining
When and where: Tuesday, July 19, 11:25 – 12:55 at DFKI
Abstract: Software engineering researchers suddenly have access to a huge software ecosystem that can be analyzed: Millions of mobile apps on public stores such as the Google Play. Together with code, apps come with lots of metadata information such as the natural language description that states what the application should be doing, the list of permissions the app needs in order to function correctly, and the list of reviews that users provide.
In this talk I will present the fundamental techniques and tools to analyze this large body of information. I will introduce static and dynamic analysis techniques to analyze apps behavior, and I will leverage machine learning and natural language processing techniques for several purposes such as finding similar applications or anomalous behavior.
More on Alessandra:
Alessandra Gorla received her Bachelor’s and Master’s degrees in computer science from the University of Milano-Bicocca in Italy. She completed her Ph.D. in informatics at the Universita’ della Svizzera Italiana in Lugano, Switzerland in 2011. In her Ph.D. thesis she defined and developed the notion of Automatic Workarounds, a self-healing technique to recover Web applications from field failures, a work for which she received the Fritz Kutter Award for the best industry related Ph.D. thesis in computer science in Switzerland.
Before joining IMDEA Software Institute in December 2014 as Assistant Research Professor, she has been a postdoctoral researcher in the software engineering group at Saarland University in Germany. During her postdoc, she has also been a visiting researcher at Google in Mountain View.
Alessandra’s research interests are in software engineering, and in particular on testing and analysis techniques to improve the reliability and security of software systems. She is also interested in malware detection for mobile applications.