RTAS is a top-tier conference with a focus on systems with timing requirements. RTAS’26 welcomes papers describing applications, case studies, methodologies, tools, algorithms, operating systems, middleware, or hardware innovations that contribute to the state of the art in the design, implementation, validation, verification, and evolution of systems with timing requirements.

RTAS’26 consists of two tracks:

    Track 1: Systems and Applications
    Track 2: Applied Methodologies and Foundations

Scope

To be in scope, papers must explicitly consider at least one of the following:

    Some kind of timing requirements
    Improvements or innovations that directly support the fundamental properties of systems with timing requirements

Timing Requirements

The timing requirements of interest are broadly defined, including:

    Hard real-time
    Soft real-time
    Probabilistic timing
    QoS, throughput, or latency constraints

Example: Speeding up an AI algorithm is not in scope. Guaranteeing response time is.

Authors must state clearly the type of timing properties addressed.
Innovations Supporting Timing-Critical Systems

We welcome work that enhances:

    Determinism
    Predictability
    Dependability
    Efficiency

In scope examples:

    OS verification to ensure timing guarantees
    Compiler reducing WCET or providing sound timing variability

Not in scope: Functional test case generation without timing aspects.

Application Areas

Any system with timing requirements, such as:

    Embedded systems
    Distributed CPS
    Cloud, edge, fog computing
    IoT, robotics, smart grid, smart cities
    Middleware and runtime frameworks
    ML and signal processing with timing guarantees

Both formal proofs and empirical validations are welcome.

Tracks

Track 1: Systems and Applications

Focus on empirical research related to:

    Applications with timing constraints
    RTOSes, hypervisors, middleware
    Hardware architectures (memory, FPGAs, GPUs)
    Real-time networks and CPS/IoT infrastructure
    Cloud/Edge/AI systems with timing requirements
    Tools, compilers, benchmarks, WCET analysis

Experiments required: Must include evaluation on real systems or compelling industrial case studies. Simulation is acceptable with justification.

Surveys welcome: Empirical methods (e.g., interviews, use cases) about state-of-the-practice in real-time systems are encouraged.

Track 2: Applied Methodologies and Foundations

Focus on models and analysis techniques, including:

    Modeling languages and learning
    Scheduling, resource allocation
    Co-design and optimization methods
    Design space exploration
    Verification/validation methods

Must include a real use case and experimental results.
Synthetic data is fine if well motivated.