@misc {42883,
	title = {openCAESAR: A Next Generation Platform for Systems Engineering},
	howpublished = {Simula Research Laboratory, Norway},
	year = {2022},
	author = {Elaasar, Maged}
}
@article {25979,
	title = {Testing Self-Healing Cyber-Physical Systems under Uncertainty: A Fragility-Oriented Approach},
	journal = {Software Quality Journal},
	volume = {27},
	year = {2019},
	month = {03/2019},
	pages = {615{\textendash}649},
	publisher = { Springer},
	url = {https://link.springer.com/article/10.1007/s11219-018-9437-3},
	author = {Ma, Tao and Ali, Shaukat and Yue, Tao and Elaasar, Maged}
}
@inproceedings {25461,
	title = {Fragility-Oriented Testing with Model Execution and Reinforcement Learning},
	journal = {The 29th International Conference on Testing Software and Systems},
	year = {2017},
	publisher = {LNCS},
	author = {Ma, Tao and Ali, Shaukat and Yue, Tao and Elaasar, Maged}
}
@techreport {25201,
	title = {Fragility-Oriented Testing with Model Execution and Reinforcement Learning},
	year = {2017},
	publisher = {Simula Research Laboratory},
	abstract = {Self-healing is becoming an intrinsic feature of Cyber-Physical Systems (CPSs), which allows them to recover from faults in an autonomous manner during their operation. It becomes even more challenging when testing self-healing behaviors of CPSs in the presence of environment uncertainty. Such uncertainty makes system behaviors even more unpredictable in addition to the autonomous nature of self-healing behaviors. To this end, we propose Fragility-Oriented Testing (FOT) relying on model execution and reinforcement learning to efficiently test self-healing behaviors of a CPS in the presence of environment uncertainty. To evaluate the efficiency of FOT, we compared it with random testing (RT) and coverage-based testing (CBT). Results show that FOT significantly outperformed the two baselines for 7 out of 10 experiments in terms of fault revelation. Compared with RT and CBT, FOT respectively reduces 50\% and 35\% test execution time to find a fault.},
	author = {Ma, Tao and Ali, Shaukat and Yue, Tao and Elaasar, Maged}
}
@inproceedings {Elaasar.2006.1,
	title = {A Metamodeling Approach to Pattern Specification and Detection},
	journal = {Proc. of ACM/IEEE International Conference on Model Driven Engineering Languages and Systems (MoDELS)},
	year = {2006},
	pages = {484-498},
	publisher = {Springer},
	type = {Conference},
	isbn = {3-540-45772-0},
	author = {Elaasar, Maged and Briand, Lionel and Labiche, Yvan},
	editor = {Nierstrasz, Oscar and Whittle, Jon and Harel, David and Reggio, Gianna}
}
