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.