TY  - BOOK
AU  - Bertrand,Nathalie
AU  - Bortolussi,Luca
ED  - International Conference on the Quantitative Evaluation of Systems
TI  - Quantitative evaluation of systems: 14th International Conference, QEST 2017, Berlin, Germany, September 5-7, 2017, Proceedings 
T2  - Lecture notes in computer science,
SN  - 9783319663357
AV  - QA76.9.E94 
U1  - 004.2/5 23
PY  - 2017///
CY  - Cham, Switzerland
PB  - Springer
KW  - Computer systems
KW  - Evaluation
KW  - Congresses
KW  - Computer networks
KW  - Reliability (Engineering)
KW  - Petri nets
KW  - Machine theory
KW  - Electronic Data Processing
KW  - Systèmes informatiques
KW  - Évaluation
KW  - Congrès
KW  - Réseaux d'ordinateurs
KW  - Fiabilité
KW  - Réseaux de Pétri
KW  - Théorie des automates
KW  - Informatique
KW  - computer science
KW  - aat
KW  - data processing
KW  - simulation
KW  - Systems analysis & design
KW  - bicssc
KW  - Maths for computer scientists
KW  - User interface design & usability
KW  - Computer modelling & simulation
KW  - Computer programming
KW  - software development
KW  - Computers
KW  - Hardware
KW  - Handheld Devices
KW  - bisacsh
KW  - Mathematical & Statistical Software
KW  - Machine Theory
KW  - Computer Simulation
KW  - Programming
KW  - General
KW  - fast
KW  - Congress
KW  - proceedings (reports)
KW  - Conference papers and proceedings
KW  - lcgft
KW  - Actes de congrès
KW  - rvmgf
N1  - Includes author index; Probabilistic modeling -- Smart energy systems over the cloud -- Petri nets and performance modeling -- Parametric verification -- Machine learning and formal methods -- Tools
N2  - This book constitutes the proceedings of the 14th International Conference on Quantitative Evaluation Systems, QEST 2017, held in Berlin, Germany, in September 2017. The 20 full papers and 4 tool papers presented were carefully reviewed and selected From 58 submissions. The papers are organized in topical sections entitled: probabilistic modeling; smart energy systems over the cloud; Petri nets and performance modeling; parametric verification; machine learning and formal methods; tools
UR  - https://link.springer.com/10.1007/978-3-319-66335-7
ER  -