J. Andersson, L. Baresi, N. Bencomo, R. De-lemos, A. Gorla et al., Software Engineering Processes for Self-Adaptive Systems, Software Engineering for Self-Adaptive Systems II Lecture Notes in Computer Science, vol.7475, 2013.

A. Amin, A. Colman, and L. Grunske, An approach to forecasting QoS attributes of web services based on ARIMA and GARCH models, International Conference on Web Services, vol.2012, pp.74-81

A. Amin, L. Grunske, and A. Colman, An automated approach to forecasting QoS attributes based on linear and non-linear time series modeling, ASE, vol.2012, pp.130-139

, Run-time Models for Self-managing Systems and Applications, 2010.

M. Autili, V. Cortellessa, D. Di-ruscio, P. Inverardi, P. Pelliccione et al., Integration architecture synthesis for taming uncertainty in the digital space, Lecture Notes in Computer Science, vol.7539, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00730880

L. Baresi, D. Bianculli, C. Ghezzi, S. Guinea, and P. Spoletini, Validation of Web Service Compositions, IET Software, vol.1, issue.6, pp.219-232, 2007.

L. Baresi and C. Ghezzi, The disappearing boundary between development-time and runtime. FSE/SDP workshop on Future of software engineering research, 2010.

N. Bencomo, QuantUn: Quantification of Uncertainty for the Reassessment of Requirements, Next! track at the 23rd International Requirements Engineering Conference, 2015.

N. Bencomo, R. B. France, and B. H. Cheng, Models@run.time: Foundations, Applications, and Roadmaps, vol.8378, 2014.
URL : https://hal.archives-ouvertes.fr/hal-00733338

A. Beugnard, J. Jezequel, N. Plouzeau, and D. Watkins, Making components contract aware, In IEEE Computer, vol.32, issue.7, pp.38-45
URL : https://hal.archives-ouvertes.fr/hal-02141773

R. Calinescu and M. Kwiatkowska, Using quantitative analysis to implement autonomic IT systems, Proceedings of the 31st International Conference on Software Engineering (ICSE '09), pp.100-110
URL : https://hal.archives-ouvertes.fr/inria-00458053

R. Calinescu, C. Ghezzi, M. Kwiatkowska, and R. Mirandla, Self-adaptive software needs quantitative verification at runtime, Commun. ACM, vol.55, p.2012

R. Calinescu, L. Grunske, M. Kwiatkowska, R. Mirandola, and G. Tamburrelli, Dynamic QoS management and optimization in service-based systems, IEEE Transactions on Software Engineering, vol.37, issue.3, pp.387-409, 2011.

R. Calinescu, K. Johnson, and Y. Rafiq, Developing self-verifying service-based systems, /ACM 28th International Conference on Automated Software Engineering, 2013.

R. Calinescu, K. Johnson, and Y. Rafiq, Using observation ageing to improve markovian model learning in QoS engineering, 2nd ACM/SPEC International Conference on Performance engineering ACM, 2011.

R. Calinescu, S. Kikuchi, and J. K. , Compositional reverification of probabilistic safety properties for large-scale complex IT systems, Large-Scale Complex IT Systems, vol.7539, pp.303-329, 2012.

R. Calinescu, Y. Rafiq, K. Johnson, and M. E. Bak?r, Adaptive model learning for continual verification of non-functional properties, 5th ACM/SPEC international conference on Performance engineering, pp.87-98, 2014.

J. Cámara, R. De-lemos, N. Laranjeiro, R. Ventura, and M. Vieira, Testing the robustness of controllers for self-adaptive systems, Journal of the Brazilian Computer Society, vol.20, issue.1, 2014.

J. Camara, G. Moreno, D. Garlan, and B. Schmerl, Analyzing latency-aware selfadaptation using stochastic games and simulations, ACM Transactions on Autonomous and Adaptive Systens, vol.10, issue.4, pp.1-23, 2016.

V. Cardellini, E. Casalicchio, V. Grassi, S. Iannucci, F. Lo-presti et al., MOSES: A Framework for QoS Driven Runtime Adaptation of Service-Oriented Systems, IEEE Trans. Softw. Eng, vol.38, pp.1138-1159, 2012.

B. Cavallo, M. Di-penta, and G. Canfora, An empirical comparison of methods to support QoS-aware service selection, PESOS, vol.2010, pp.64-70

B. Cheng, Software engineering for self-adaptive systems: A research roadmap, Software Engineering for Self-Adaptive Systems, vol.5525, 2009.

B. H. Cheng, K. I. Eder, M. Gogolla, L. Grunske, M. Litoiu et al., Using Models at Runtime to Address Assurance for Self-Adaptive Systems, LNCS, vol.8378, pp.47-100, 2014.

A. David, K. Larsen, A. Legay, M. Mikuaionis, and D. Poulsen, Uppaal smc tutorial, International Journal on Software Tools for Technology Transfer, vol.17, issue.4, pp.397-415, 2015.

D. G. De-la-iglesia and D. Weyns, Guaranteeing Robustness in a Mobile Learning Application Using Formally Verified MAPE Loops, SEAMS 2013

D. G. De-la-iglesia and D. Weyns, MAPE-K Formal Templates to Rigorously Design Behaviors for Self-Adaptive Systems, ACM Transactions on Autonomous and Adaptive Systems, vol.10, issue.3, p.2015

R. De-lemos, Software engineering for self-adaptive systems: A second research roadmap, Software Engineering for Self-Adaptive Systems II, vol.7475, 2013.
URL : https://hal.archives-ouvertes.fr/inria-00638157

I. Epifani, C. Ghezzi, and G. Tamburrelli, Change-point detection for black-box services, Proceedings of the eighteenth ACM SIGSOFT international symposium on Foundations of software engineering, 2010.

I. Epifani, C. Ghezzi, R. Mirandola, and G. Tamburrelli, Model evolution by runtime parameter adaptation, Proceedings of the 31st International Conference on Software Engineering IEEE Computer Society, vol.5070513, 2009.

N. Esfahani, S. Malek, and S. , Uncertainty in self-adaptive software systems, Software Engineering for Self-Adaptive Systems II, vol.7475, pp.214-238, 2013.

A. Filieri, C. Ghezzi, and G. Tamburrelli, A formal approach to adaptive software: continuous assurance of non-functional requirements, Formal Asp. Comput, vol.24, issue.2, pp.163-186, 2012.

A. Filieri, C. Ghezzi, and G. Tamburrelli, Runtime efficient probabilistic model checking. International Conference on Software Engineering, 2011.

A. Filieri, L. Grunske, and A. Leva, Lightweight Adaptive Filtering for Efficient Learning and Updating of Probabilistic Models, International Conference on Software Engineering, vol.2015, pp.200-211

E. M. Fredericks, A. J. Ramirez, and B. H. Cheng, Towards runtime testing of dynamic adaptive systems, 8th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, 2013.

S. Funtowicz and R. J. , Uncertainty and Quality in Science for Policy, 1990.

D. Garlan, Software engineering in an uncertain world, Future of Software Engineering Research workshop, FoSER, 2010.

C. Ghezzi, On requirements verification for model refinements. Requirements Engineering Conference (RE), 2013 21st IEEE, 2013.

H. Giese, N. Bencomo, L. Pasquale, A. J. Ramirez, P. Inverardi et al., Living with Uncertainty in the Age of Runtime Models, LNCS, vol.8378, pp.47-100, 2014.

L. Grunske and P. Zhang, Monitoring probabilistic properties, Proceedings of the 7th joint meeting of the European software engineering conference and the ACM SIGSOFT symposium on The foundations of software engineering, pp.183-192, 2009.

E. M. Hahn, H. Hermanns, B. Wachter, and L. Zhang, PARAM: A Model Checker for Parametric Markov Models, CAV, pp.660-664, 2010.
URL : https://hal.archives-ouvertes.fr/hal-00650737

U. Iftikhar and D. Weyns, ActivFORMS: Active Formal Models for Self-Adaptation, SEAMS, 2014.

U. Iftikhar and D. Weyns, A Case for Runtime Statistical Model Checking for SelfAdaptive Systems, Techical Report Katholieke Universiteit Leuven CW, vol.693, 2016.

P. Inverardi and P. Mori, Model checking requirements at runtime in adaptive systems, Workshop on Assurances for Self-Adaptive Systems, 2011.

P. Inverardi, Software of the Future Is the Future of Software? Trustworthy Global Computing, vol.4661, 2007.

K. Johnson, R. Calinescu, and S. Kikuchi, An incremental verification framework for component-based software systems, CBSE'13. Pages, pp.33-42, 2013.

M. Kwiatkowska, G. Norman, and D. Parker, PRISM 4.0: Verification of Probabilistic Real-time Systems, Proc. 23rd International Conference on Computer Aided Verification (CAV'11), vol.6806, pp.585-591, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00648035

M. Kwiatkowska, G. Norman, D. Parker, and H. Qu, Assume-guarantee verification for probabilistic systems, TACAS'10, vol.6105, pp.23-37, 2010.
URL : https://hal.archives-ouvertes.fr/inria-00458058

M. Kwiatkowska, D. Parker, and H. Qu, Incremental quantitative verification for Markov decision processes, Proceedings 2011 IEEE/IFIP International Conference Dependable Systems and Networks, 2011.
DOI : 10.1109/dsn.2011.5958249
URL : https://hal.archives-ouvertes.fr/hal-00647057

A. Legay, B. Delahaye, and S. Bensalem, Statistical Model Checking: An Overview, Proceedings of the First International Conference on Runtime Verification (RV 2010), pp.122-135, 2010.
DOI : 10.1007/978-3-642-16612-9_11
URL : https://hal.archives-ouvertes.fr/inria-00591593

S. Mahdavi-hezavehi, P. Avgeriou, and D. Weyns, A Classification of Current Architecture-based Approaches Tackling Uncertainty in Self-Adaptive Systems with Multiple Requirements, Managing Trade-offs in Adaptable Software Architectures, 2016.

J. Mula, R. Poler, J. Garcia-sabater, and F. Lario, Models for production planning under uncertainty: A review, IJPE, vol.103, issue.1, pp.271-285, 2006.
DOI : 10.1016/j.ijpe.2005.09.001
URL : http://core.ecu.edu/omgt/krosj/appart2.pdf

E. Pavese, V. Braberman, and U. S. , Probabilistic environments in the quantitative analysis of (non-probabilistic) behaviour models, Proceedings of the 7th joint meeting of the European software engineering conference and the ACM SIGSOFT symposium on The foundations of software engineering, pp.335-344

D. Perez-palacin and R. Mirandola, Uncertainties in the modeling of self-adaptive systems: A taxonomy and an example of availability evaluation, Proc. of the, p.5

, ACM/SPEC Int. Conf. on Performance Engineering, 2014.

A. Ramirez, A. Jensen, and B. Cheng, A taxonomy of uncertainty for dynamically adaptive systems, 2012.

J. C. Refsgaard, J. P. Van-der-sluijs, A. L. Højberg, and P. A. Vanrolleghem, Uncertainty in the environmental modeling process -a framework and guidance, Environ. Model. Softw, vol.22, issue.11, pp.1543-1556, 2007.

S. Shevtsov, U. Iftikhar, and D. Weyns, SimCA vs ActivFORMS: Comparing Control-and Architecture-Based Adaptation on the TAS Exemplar, Control Theory and Software Engineering, 2015.

S. Stoller, E. Bartocci, J. Seyster, R. Grosu, K. Havelund et al., Runtime Verification with State Estimation, Runtime Verification, Lecture Notes in Computer Science, vol.7186, 2012.
DOI : 10.1007/978-3-642-29860-8_15
URL : http://www.cs.sunysb.edu/%7Estoller/papers/rv2011.pdf

D. Sykes, D. Corapi, J. Magee, J. Kramer, A. Russo et al., Learning revised models for planning in adaptive systems, Proceedings of the 2013 International Conference on Software Engineering (ICSE '13), pp.63-71

S. Uttamchandani, L. Yin, G. Alvarez, J. Palmer, and G. Agha, Chameleon: a selfevolving, fully-adaptive resource arbitrator for storage systems, USENIX Technical Conference, 2005.

N. Villegas, H. Müller, G. Tamura, L. Duchien, and C. R. , A Framework for Evaluating Quality-Driven Self-Adaptive Software Systems. 6th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, pp.80-89, 2011.
DOI : 10.1145/1988008.1988020
URL : https://hal.archives-ouvertes.fr/inria-00578337

T. Vogel and H. Giese, Model-Driven Engineering of Self-Adaptive Software with EUREMA, ACM Trans. Auton. Adapt. Syst, vol.8, issue.4, 2014.
DOI : 10.1145/2555612
URL : http://arxiv.org/pdf/1805.07353

W. Walker, P. Harremos, J. Romans, J. Van-der-sluus, M. Van-asselt et al., Defining uncertainty. a conceptual basis for uncertainty management in model-based decision support, Integrated Assessment, vol.4, issue.1, pp.5-17, 2003.

D. Weyns and C. R. , Tele Assistance: A Self-Adaptive Service-Based System Exemplar, 2015.
DOI : 10.1109/seams.2015.27
URL : http://eprints.whiterose.ac.uk/93152/1/PID3580031.pdf

D. Weyns and U. Iftikhar, Model-based Simulation at Runtime for Self-adaptive Systems, 2016.
DOI : 10.1109/icac.2016.67

D. Weyns, M. U. Iftikhar, D. G. De-la-iglesia, A. , and T. , A survey of formal methods in self-adaptive systems, Fifth International C* Conference on Computer Science and Software Engineering, C3S2E '12, pp.67-79, 2012.

D. Weyns, S. Malek, and J. Andersson, FORMS: Unifying Reference Model for Formal Specification of Distributed Self-Adaptive Systems, ACM Transactions on Autonomous and Adaptive Systems, vol.7, issue.1, p.2012

J. Whittle, P. Sawyer, N. Bencomo, B. Cheng, and J. M. Bruel, Relax: Incorporating uncertainty into the specification of self-adaptive systems, Requirements Engineering Conference, 2009.

C. Ye, S. C. Cheung, and C. W. , Process Evolution with Atomicity Consistency, 2007.
DOI : 10.1109/seams.2007.14
URL : http://www.cs.cityu.edu.hk/~wkchan/papers/seams07-ye+cheung+chan.pdf

H. L. Younes and R. G. Simmons, Statistical probabilistic model checking with a focus on time-bounded properties, Information and Computation, vol.204, issue.9, pp.1368-1409, 2006.

H. L. Younes, M. Z. Kwiatkowska, G. Norman, and P. D. , Numerical vs. statistical probabilistic model checking. STTT, vol.8, pp.216-228, 2006.

J. Zhang and B. Cheng, Using temporal logic to specify adaptive program semantics, The Journal of Systems and Software, vol.79, pp.1361-1369, 2006.
DOI : 10.1016/j.jss.2006.02.062

J. Zhang and B. Cheng, Model-based development of dynamically adaptive software, 28th International Conference on Software Engineering, 2006.