CMA
CMA, acronym of Completeness Metric Analyzer, is a command-line tool for runtime monitoring of timing and State Machine status
Hepsy Code
A System-Level Methodology for HW/SW Co-Design of Heterogeneous Parallel Dedicated Systems
Tags
- Anomaly Detection
- Architecture components modeling
- Architecture Viewpoint modelling
- Aspect oriented modeling
- Checking Compatibility
- Code Generation
- Contract-based design
- Correctness by construction
- Dependability analysis
- Detailed Design Modeling
- Document generation
- Domain Specific Languages
- Dynamic model checking
- Failure propagation analysis
- Formal methods
- Full coverage test generation
- Functional analysis
- Inference facility
- LTL monitoring
- Machine Learning
- MAST
- MegaM@Rt2
- Model and traceability management
- Model based testing
- Model identification facility
- Model import/export facility
- Model querying facility
- Model storage facility
- Model Verification & Validation
- Model versioning facility
- Model versioning facility. Model import/export facility
- Model viewpoint/view facility
- Monitor Generation
- Monitoring and logs analysis
- Monitoring Data Parser
- OpenCert
- Participatory Development
- Performance analysis
- Performance Exploration
- Performance Testing
- Probes injection
- Properties modeling
- Regular expressions monitoring
- Reinforcement Learning
- Requirement coverage analysis
- Requirement traceability
- Reuse & Variability modelling
- Runtime analysis
- Runtime verification and online testing
- Schedulability analysis
- Simulation
- Source code repository facility
- Stakeholder needs definition
- Standard Modelling Languages & Profiles
- State-based quantitative analysis
- Static model checking
- SW-FPGA-HW components modelling
- System Engineering
- System requirements specification
- System requirements specification. Requirement traceability
- Testing
- Traceability facility
- Traces analysis
- Traces collection
- Verification
- WCET
Project funded by the Electronic Component Systems for European Leadership Joint Undertaking under grant agreement No 737494. This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and Sweden, France, Spain, Italy, Finland, Czech Republic.