Scope and Topics

The two flagship conferences QEST (International Conference on Quantitative Evaluation of SysTems) and FORMATS (International Conference on Formal Modeling and Analysis of Timed Systems) are pursuing a strategic process of joining forces and sparking a new joint conference for quantitative modelling, analysis, and verification. This culminated in 2024 in the first QEST+FORMATS joint conference. In 2026, the two conferences will form the third QEST+FORMATS joint conference, which will be held on 2-4 September 2026 in Liverpool, UK, as part of the CONFEST 2026 umbrella conference.

The joint conference is the leading forum for the quantitative evaluation and verification of systems. QEST+FORMATS aims to promote the study of fundamental and practical aspects of systems with quantitative nature (such as probability, timing, and cost). It aims to bring together researchers from different disciplines who share interests in the modelling, design, and analysis of computational systems. Systems of interest include biological and chemical systems; computer networks; critical infrastructures; cyber-physical systems; data-driven AI systems; energy systems; hardware and software systems; industrial systems; mobility networks; and quantum systems. The QEST+FORMATS joint conference also aims to attract researchers interested in real-time issues in hardware design, performance analysis, real-time software, scheduling, semantics and verification of timed, hybrid, and probabilistic systems. In general, the conference aims to attract experts in quantitative and timed systems from any domain.

Topics and scientific areas of interest include:

    Models and metrics for the correctness, performance, reliability, safety, and security of systems (stochastic, probabilistic, quantum, and non-deterministic models including Markov chains, automata, Petri nets, process algebra, and their variations);
    Languages and methods for the specification of quantitative properties of systems;
    Techniques, algorithms, and data structures for the analysis, evaluation, and verification of the above models, e.g., for model checking, testing, constraint solving, scheduling, optimization, and worst-case execution time analysis;
    Quantitative and probabilistic aspects of programming;
    Data-driven and machine-learning techniques for the analysis, prediction, and verification of quantitative properties of systems;
    Case studies that highlight the role of quantitative specification, modelling, and evaluation in the design and analysis of systems, with emphasis on emerging problems and technologies, or novel domains;
    Software tools to support the practical application of research results in all of the above areas.