The International Conference on Quantitative Evaluation of SysTems (QEST) is the leading forum on quantitative evaluation and verification of computer systems and networks. Areas of interest include quantitative specification methods, stochastic models, and metrics for performance, reliability, safety, correctness, and security. QEST is interested in both theoretical and experimental research.
QEST welcomes a diversity of modeling formalisms, programming languages and methodologies that incorporate quantitative aspects such as probabilities, approximations and other quantitative aspects. Papers may advance empirical, simulation and analytic methods. Of particular interest are case studies that highlight the role of quantitative specification, modeling and evaluation in the design of systems. Systems of interest include computer hardware and software architectures, communication systems, cyber-physical systems, infrastructural systems, and biological systems. Papers that describe novel tools to support the practical application of research results in all of the above areas are also welcome.
Special Sessions
To encourage submissions of papers in frontier topics, submissions in selected areas are encouraged. Paper submitted to special sessions will be treated as regular submitted papers, they will be peer reviewed, and subject to the same quality requirements. A special session with accepted papers on the selected topics will be organised during the conference. This year selected topics are:
Smart Energy Systems over the Cloud
We solicit contributions dealing with quantitative analysis, verification, and performance evaluation of models of networks of smart devices interconnected physically and over the cloud, and in particular within the technological context of smart energy, dealing with smart buildings, the smart grid, or with modern power networks. Instances of problems of interest are energy management in smart buildings, demand response over smart grids, or frequency control over power networks. We are interested in configurations related to cyber-physical systems, of systems of systems, and of the Internet of things, and on models encompassing continuous and digital components, and uncertainty (either environmental, adversarial, or probabilistic).
Machine Learning and Formal Methods
We call for contributions on the fusion of formal methods and machine learning techniques. In particular, we are interested in the use of machine learning approaches, such as reinforcement learning, learning automata, decision trees, gradient based methods, etc. in (statistical) model checking, controller synthesis, program analysis and synthesis, timed systems, compositional verification, etc. The
main aim is to disseminate learning based techniques that have potential of improving theory and practice of formal methods.
SPECIAL ISSUE: A selection of the best papers presented at QEST 2017 will be invited to submit an extended version of their paper for a Special Issue that will appear in the ACM Transactions of Modelling and Computer Simulation.
All submitted papers will be evaluated by at least three reviewers on the basis of their originality, technical quality, scientific or practical contribution to the state of the art, methodology, clarity, and adequacy of references.