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Past Seminars

18/12/2014 - 16:00

I will present the paper:

NLP-KAOS for Systems Goal Elicitation: Smart Metering System Case Study, by E. Casagrande, S. Woldeamlak, Wei Lee Woon, H. H. Zeineldin, D. Svetinovic. IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, VOL. 40, NO. 10, OCTOBER 2014.

04/12/2014 - 16:00

"The Value of Uncertainty and Risk in Software Requirements", from an invited lecture (Louvain, 2013) and an ICSE paper (Hyderabad, 2014) by Emmanuel Letier, David Stefan, and Earl T. Barr.

27/11/2014 - 16:00

I will show the current status of the RISCOSS project after 2 year of work; I will focus in particular on the implementation work done, showing the actual models that have been developed and how they are used by the inference system, and presenting the platform and its functionalities.

20/11/2014 - 16:00

I will present the paper: Alessandra Gorla, Ilaria Tavecchia, Florian Gross, and Andreas Zeller. "Checking App Behavior Against App Descriptions" Proceedings of the 36th International Conference on Software Engineering (ICSE 2014). Pages 1025-1035. ACM New York, NY, USA.

13/11/2014 - 16:00
I will report the experience of working with geographically-distributed heterogeneous people. The objective of this work was the collection of e-mail discussions annotated with intentions.
30/10/2014 - 16:00
This seminar is about the paper:
"FlowDroid: Precise Context, Flow, Field, Object-sensitive and Lifecycle-aware Taint Analysis for Android Apps"
Steven Arzt, Siegfried Rasthofer, Christian Fritz, Eric Bodden, Alexandre Bartel, Jacques Klein, Yves Le Traon, Damien Octeau and Patrick McDaniel
Presented at PLDI14
23/10/2014 - 16:00

I will present the work: "Modelling Business and Software Ecosystems”, by Xavier Franch, Angelo Susi, Eric S.K. Yu.

16/10/2014 - 16:00
This seminar is about the paper:
Hai-Feng Guo, and  Zongyan Qiu, "A dynamic stochastic model for automatic grammar-based test generation", Journal of Software: Practice and Experience, June 2014 (early view).
25/09/2014 - 16:00

Paolo Tonella, Roberto Tiella, Cu Duy Nguyen, "Interpolated N-Grams for Model Based Testing" [ICSE 2014]


Models – in particular finite state machine models – provide an invaluable source of information for the derivation of effective test cases. However, models usually approximate part of the program semantics and capture only some of the relevant dependencies and constraints. As a consequence, some of the test cases that are derived from models are infeasible.