I. Abío and P. J. Stuckey, Encoding Linear Constraints into SAT, CP, pp.75-91, 2014.
DOI : 10.1007/978-3-319-10428-7_9

R. Amadini, M. Gabbrielli, and J. Mauro, An enhanced features extractor for a portfolio of constraint solvers, Proceedings of the 29th Annual ACM Symposium on Applied Computing, SAC '14, pp.1357-1359, 2014.
DOI : 10.1145/2554850.2555114

URL : https://hal.archives-ouvertes.fr/hal-01089183

R. Amadini, M. Gabbrielli, and J. Mauro, Abstract, Theory and Practice of Logic Programming, vol.41, issue.4-5, pp.509-524, 2014.
DOI : 10.1007/s10601-008-9051-2

R. Amadini, M. Gabbrielli, and J. Mauro, A Multicore Tool for Constraint Solving, IJCAI, pp.232-238, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01227592

R. Amadini, M. Gabbrielli, and J. Mauro, Portfolio approaches for constraint optimization problems. AMAI, pp.1-18, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01088429

R. Amadini, M. Gabbrielli, and J. Mauro, SUNNY-CP, Proceedings of the 30th Annual ACM Symposium on Applied Computing, SAC '15, pp.1861-1867, 2015.
DOI : 10.1145/2695664.2695741

URL : https://hal.archives-ouvertes.fr/hal-01227589

R. Amadini and P. J. Stuckey, Sequential Time Splitting and Bounds Communication for a Portfolio of Optimization Solvers, CP, pp.108-124, 2014.
DOI : 10.1007/978-3-319-10428-7_11

URL : https://hal.archives-ouvertes.fr/hal-01091664

A. Arbelaez, Y. Hamadi, and M. Sebag, Online heuristic selection in constraint programming, SoCS, 2009.
URL : https://hal.archives-ouvertes.fr/inria-00392752

A. Arbelaez, Y. Hamadi, and M. Sebag, Continuous Search in Constraint Programming, ICTAI, pp.53-60, 2010.
URL : https://hal.archives-ouvertes.fr/inria-00515137

G. Audemard, B. Hoessen, S. Jabbour, J. Lagniez, and C. Piette, Pene- LoPe, a Parallel Clause-Freezer Solver, SAT Challenge, pp.43-44, 2012.

P. Barahona, S. Hölldobler, and V. Nguyen, Representative Encodings to Translate Finite CSPs into SAT, CPAIOR, pp.251-267, 2014.
DOI : 10.1007/978-3-319-07046-9_18

B. Bischl, P. Kerschke, L. Kotthoff, M. T. Lindauer, Y. Malitsky et al., ASlib: A benchmark library for algorithm selection, Artificial Intelligence, vol.237, 2015.
DOI : 10.1016/j.artint.2016.04.003

G. Chu, M. Garcia-de-la-banda, and P. J. Stuckey, Automatically Exploiting Subproblem Equivalence in Constraint Programming, CPAIOR, pp.71-86, 2010.
DOI : 10.1007/978-3-642-13520-0_10

R. Cipriano, A. Dovier, and J. Mauro, Compiling and Executing Declarative Modeling Languages to Gecode, ICLP, pp.744-748, 2008.
DOI : 10.1007/978-3-540-74610-2_18

C. Fawcett, M. Vallati, F. Hutter, J. Hoffmann, H. H. Hoos et al., Improved features for runtime prediction of domain-independent planners, ICAPS. AAAI, 2014.

A. M. Frisch, W. Harvey, C. Jefferson, B. Martínez-hernández, and I. Miguel, Essence: A constraint language for specifying combinatorial problems, Constraints, vol.12, issue.1, pp.268-306, 2008.
DOI : 10.1007/s10601-008-9047-y

. Fullcontact, How We Used Immutable Servers to Simplify Our Cloud Infrastructure, 2014.

A. Van-gelder, Careful Ranking of Multiple Solvers with Timeouts and Ties, SAT, pp.317-328, 2011.
DOI : 10.1007/978-1-4615-4459-3

P. Ian, T. Gent, and . Walsh, Csp lib : A Benchmark Library for Constraints, CP, pp.480-481, 1999.

D. Geschwender, F. Hutter, L. Kotthoff, Y. Malitsky, H. H. Hoos et al., Algorithm Configuration in the Cloud: A Feasibility Study, LNCS, vol.8426, pp.41-46, 2014.
DOI : 10.1007/978-3-319-09584-4_5

C. P. Gomes and B. Selman, Algorithm portfolios, Artificial Intelligence, vol.126, issue.1-2, pp.43-62, 2001.
DOI : 10.1016/S0004-3702(00)00081-3

H. Guo and W. H. Hsu, A machine learning approach to algorithm selection for $\mathcal{NP}$ -hard optimization problems: a case study on the MPE problem, Annals of Operations Research, vol.151, issue.3, pp.61-82, 2007.
DOI : 10.1007/s10479-007-0229-6

I. Guyon and A. Elisseeff, An introduction to variable and feature selection, The Journal of Machine Learning Research, vol.3, pp.1157-1182, 2003.

E. Hebrard, E. O. Mahony, and B. O. Sullivan, Constraint Programming and Combinatorial Optimisation in Numberjack, CPAIOR-10, pp.181-185, 2010.
DOI : 10.1007/978-3-642-13520-0_22

URL : https://hal.archives-ouvertes.fr/hal-00561698

H. Holger, R. Hoos, and . Kaminski, Marius Thomas Lindauer, and Torsten Schaub. aspeed: Solver scheduling via answer set programming, p.2015

H. Holger, B. Hoos, T. Kaufmann, M. Schaub, and . Schneider, Robust Benchmark Set Selection for Boolean Constraint Solvers, LNCS, vol.7997, pp.138-152, 2013.

H. Holger, M. T. Hoos, F. Lindauer, and . Hutter, From Sequential Algorithm Selection to Parallel Portfolio Selection

B. Hurley, L. Kotthoff, Y. Malitsky, O. Barry, and . Sullivan, Proteus: A Hierarchical Portfolio of Solvers and Transformations, CPAIOR, pp.301-317, 2014.
DOI : 10.1007/978-3-319-07046-9_22

F. Hutter, H. H. Hoos, and K. Leyton-brown, Sequential Model-Based Optimization for General Algorithm Configuration, LNCS, vol.56, issue.4, pp.507-523, 2011.
DOI : 10.1007/978-0-387-84858-7

F. Hutter, H. H. Hoos, K. Leyton-brown, and T. Stützle, ParamILS: An Automatic Algorithm Configuration Framework, J. Artif. Intell. Res. (JAIR), vol.36, pp.267-306, 2009.

F. Hutter, L. Xu, H. H. Hoos, and K. Leyton-brown, Algorithm Runtime Prediction: The State of the Art, 1211.

S. Kadioglu, Y. Malitsky, A. Sabharwal, H. Samulowitz, and M. Sellmann, Algorithm Selection and Scheduling, CP, 2011.
DOI : 10.1007/978-3-642-23786-7_35

S. Kadioglu, Y. Malitsky, M. Sellmann, and K. Tierney, ISAC -Instance- Specific Algorithm Configuration, ECAI, 2010.

Z. Kiziltan and J. Mauro, Service-Oriented Volunteer Computing for Massively Parallel Constraint Solving Using Portfolios, CPAIOR, pp.246-251, 2010.
DOI : 10.1007/978-3-642-13520-0_27

L. Kotthoff, LLAMA: Leveraging Learning to Automatically Manage Algorithms. CoRR, abs, 1031.

L. Kotthoff, Algorithm Selection for Combinatorial Search Problems: A Survey, pp.48-60, 2014.
DOI : 10.1007/978-3-642-31612-8_18

L. Kotthoff, Reliability of computational experiments on virtualised hardware, Journal of Experimental & Theoretical Artificial Intelligence, vol.33, issue.5, pp.33-49, 2014.
DOI : 10.1002/cpe.938

C. Kroer and Y. Malitsky, Feature Filtering for Instance-Specific Algorithm Configuration, 2011 IEEE 23rd International Conference on Tools with Artificial Intelligence, pp.849-855, 2011.
DOI : 10.1109/ICTAI.2011.132

Y. Malitsky, A. Sabharwal, H. Samulowitz, and M. Sellmann, Parallel SAT Solver Selection and Scheduling, CP, pp.512-526, 2012.
DOI : 10.1007/978-3-642-33558-7_38

Y. Malitsky, A. Sabharwal, H. Samulowitz, and M. Sellmann, Algorithm Portfolios Based on Cost-Sensitive Hierarchical Clustering, IJCAI. IJCAI/AAAI, 2013.

M. Maratea, L. Pulina, and F. Ricca, Multi-engine ASP solving with policy adaptation, Journal of Logic and Computation, vol.25, issue.6, 2013.
DOI : 10.1093/logcom/ext068

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.385.8216

M. Maratea, L. Pulina, and F. Ricca, Abstract, Theory and Practice of Logic Programming, vol.20, issue.06, pp.841-868, 2014.
DOI : 10.1145/1149114.1149117

K. Morris, Immutable server web page

N. Nethercote, P. J. Stuckey, R. Becket, S. Brand, G. J. Duck et al., MiniZinc: Towards a Standard CP Modelling Language, CP, 2007.
DOI : 10.1007/978-3-540-74970-7_38

O. Ohrimenko, J. Peter, M. Stuckey, and . Codish, Propagation via lazy clause generation, Constraints, vol.37, issue.1???3, pp.357-391, 2009.
DOI : 10.1007/s10601-008-9064-x

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.145.8691

O. Eoin, E. Mahony, A. Hebrard, C. Holland, . Nugent et al., Using case-based reasoning in an algorithm portfolio for constraint solving, AICS, vol.08, 2009.

L. Pulina and A. Tacchella, A Multi-engine Solver for Quantified Boolean Formulas, CP, pp.574-589, 2007.
DOI : 10.1007/978-3-540-74970-7_41

L. Pulina and A. Tacchella, A self-adaptive multi-engine solver for quantified Boolean formulas, Constraints, vol.2, issue.1, pp.80-116, 2009.
DOI : 10.1007/s10601-008-9051-2

J. R. Rice, The Algorithm Selection Problem, Advances in Computers, vol.15, pp.65-118, 1976.
DOI : 10.1016/S0065-2458(08)60520-3

O. Roussel and C. Lecoutre, XML Representation of Constraint Networks: Format XCSP 2.1. CoRR, abs/0902, p.2362, 2009.
URL : https://hal.archives-ouvertes.fr/hal-00872825

A. Sabharwal and H. Samulowitz, Insights into Parallelism with Intensive Knowledge Sharing, CP, pp.655-671, 2014.
DOI : 10.1007/978-3-319-10428-7_48

H. Samulowitz, C. Reddy, A. Sabharwal, and M. Sellmann, Snappy: A Simple Algorithm Portfolio, SAT, pp.422-428, 2013.
DOI : 10.1007/978-3-642-39071-5_33

K. Smith-miles, Cross-disciplinary perspectives on meta-learning for algorithm selection, ACM Computing Surveys, vol.41, issue.1, 2008.
DOI : 10.1145/1456650.1456656

M. Stojadinovic and F. Maric, Instance-based Selection of CSP Solvers using Short Training, Pragmatics of SAT, 2014.

M. Stojadinovic and F. Maric, meSAT: multiple encodings of CSP to SAT, Constraints, vol.32, issue.2, pp.380-403, 2014.
DOI : 10.1007/s10601-014-9165-7

J. Peter, R. Stuckey, J. Becket, and . Fischer, Philosophy of the MiniZinc challenge, Constraints, vol.15, issue.3, pp.307-316, 2010.

N. Tamura, A. Taga, S. Kitagawa, and M. Banbara, Compiling finite linear CSP into SAT, Constraints, vol.64, issue.2, pp.254-272, 2009.
DOI : 10.1007/s10601-008-9061-0

O. Telelis and P. Stamatopoulos, Combinatorial optimization through statistical instance-based learning, Proceedings 13th IEEE International Conference on Tools with Artificial Intelligence. ICTAI 2001, pp.203-209, 2001.
DOI : 10.1109/ICTAI.2001.974466

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.156.2725

R. A. Valenzano, H. Nakhost, M. Müller, J. Schaeffer, and N. R. Sturtevant, ArvandHerd: Parallel Planning with a Portfolio, ECAI, pp.786-791, 2012.

L. Xu, F. Hutter, J. Shen, H. Hoos, and K. Leyton-brown, SATzilla2012: Improved Algorithm Selection Based on Cost-sensitive Classification Models, SAT Challenge, 2012.

L. Xu, F. Hutter, H. H. Hoos, and K. Leyton-brown, SATzilla: Portfolio-based Algorithm Selection for SAT, JAIR, vol.32, pp.565-606, 2008.

X. Yun and S. L. Epstein, Learning Algorithm Portfolios for Parallel Execution, ION, pp.323-338, 2012.
DOI : 10.1007/978-3-642-34413-8_23