My place of mind

About

I completed my PhD in Computer Science at Radboud University Nijmegen. My work involved model learning techniques and their application to real-world systems. With my PhD drawing to a close, I decided to try my hands in industry as a Software Developer at a nice company. Research is still close to my heart however, and it's what I will mostly cover here. Aside from research and developing (research/industry) software, I am always looking to improve my knowledge on computers, programming... That is, when I'm not singing (most likely in a choir), browsing Internet overloading my mind with irrelevant information...

Research Interest

As previously mentioned, my research area is/was model learning and its application. In particular, my focus is on developing model learning techniques for Extended Finite State Machines, formalisms that allow the representation of data flow. A side goal is to apply model learning to practical software, like network protocols.

More generally, my research interests lie in:

model learning algorithms and applications
conformance and model-based testing
reverse engineering
application of formal methods to practice
network protocols

Software

I contributed to several software projects. Among these I mention:

Tomte an active learner for Register Automata which are EFSMs supporting equality conditions, assignment operations and arbitrary output value generation
Z3GI an passive/active learner for various FSMs and EFSMs which uses the Z3 SMT solver
tcp-learner a learning setup for learning TCP stacks using abstract alphabets

Teaching

I assisted with the following courses at Radboud University:

Computer Networking 2016-2017
Computer Networking 2015-2016
Testing Techniques 2014-2015
Computer Networking 2014-2015
Testing Techniques 2013-2014

Publications

A listing of all my scientific contributions:

[1]	F. Aarts, P. Fiterāu-Brostean, H. Kuppens, and F. W. Vaandrager. Learning register automata with fresh value generation. In ICTAC 2015, volume 9399 of LNCS, pages 165-183. Springer, 2015. [ bib ][ pdf ]
[2]	F. Aarts, P. Fiterāu-Brostean, H. Kuppens, and F. W. Vaandrager. Learning register automata with fresh value generation. 2016. [ bib ]
[3]	P. Fiterāu-Brostean, R. Janssen, and F.W. Vaandrager. Learning fragments of the TCP network protocol. In FMICS 2014, volume 8718 of LNCS, pages 78-93. Springer, 2014. [ bib ][ pdf ]
[4]	P. Fiterāu-Brostean, R. Janssen, and F.W. Vaandrager. Combining model learning and model checking to analyze TCP implementations. In CAV 2016, volume 9780 of LNCS, pages 454-471. Springer, 2016. [ bib ][ pdf ]
[5]	Paul Fiterāu-Brostean and Falk Howar. Learning-based testing the sliding window behavior of TCP implementations. In Critical Systems: Formal Methods and Automated Verification, pages 185-200. Springer, 2017. [ bib ][ pdf ]
[6]	Rick Smetsers, Paul Fiterāu-Brostean, and Frits Vaandrager. Model learning as a satisfiability modulo theories problem. pages 182-194, 2018. [ bib ][ pdf ]
[7]	P. Fiterāu-Brostean, T. Lenaerts, J. de Ruiter, E. Poll, F.W. Vaandrager, and P. Verleg. Model learning and model checking of ssh implementations. In Proceedings of the 24th ACM SIGSOFT International SPIN Symposium on Model Checking of Software, SPIN 2017, pages 142-151. ACM, 2017. [ bib ][ pdf ]

This list cannot be complete without my PhD thesis which mostly stitches these works together. A copy of the thesis can be found here. What might be interesting to readers is the introduction, which gives a unified overview of all the work done during my PhD. My thesis also features on the IPA website. I successfully defended my PhD thesis on the 13th of April 2018!

Hobbies

I love singing, staying informed (thanks BBC), gaming and just going for a walk. Also do running, more for keeping my health in check than for the love of it.

The publications section was generated with the help of bibtex2html 1.95.