1. The Rare Glitch Project: Verification Tools for Embedded Systems Carnegie Mellon University Pittsburgh, PA Ed Clarke, David Garlan, Bruce Krogh, Reid Simmons, Jeannette Wing

2. Carnegie Mellon: The Rare Glitch Project2Jeannette M. Wing Embedded Systems They are highly distributed, multi-task, concurrent real-time systems. They control increasingly sophisticated physical systems. They operate with increasing autonomy under adverse and unpredictable conditions. They eventually will be seamlessly woven into the fabric of our everyday lives.

3. Carnegie Mellon: The Rare Glitch Project3Jeannette M. Wing Verification Grand Challenge  To ensure the correctness of these embedded systems as they operate in increasingly complex environments—for the safety and good of the general public. Opportunity  State of the art verification tools are well suited for control systems.  Embedded systems have narrow hardware/software interface.  Embedded systems architectures are simpler and more regular. Feasibility  We are not trying to solve the whole verification problem, but one for a class of systems for which we believe we can make the next big success story.

4. Carnegie Mellon: The Rare Glitch Project4Jeannette M. Wing Our Long-Term Vision To provide design engineers with lightweight “push- button” tools, each checking a specific application- specific property. Check Restart Check Fuel usage Check Race Check Power usage Check Deadlock

5. Carnegie Mellon: The Rare Glitch Project5Jeannette M. Wing Three Main Thrusts of Our Project Verifying system integrity  Synchronization constraints  Resource constraints  Real-time constraints Modeling the environment  Hybrid dynamics  Stochastic models Usability  Extracting models  Explaining tool feedback system environment

6. Carnegie Mellon: The Rare Glitch Project6Jeannette M. Wing Technical Challenges Interleavings of multiple task executions Inter-task dependencies and synchronization requirements System resource constraints Hard real-time constraints Interactions with complex physical dynamic systems Adverse, unpredictable environments Stringent requirements for autonomy, fault tolerance, and survivability

7. Carnegie Mellon: The Rare Glitch Project7Jeannette M. Wing Technical Approach Embedded SystemEnvironment Design Engineer’s Verification Toolbox Usability System Integrity Properties Synchronization Constraints Real-time Constraints Resource Constraints Modeling the Environment Modeling Uncertainty: Stochastic Models System-Environment Interactions: Hybrid Dynamics Foundational Building Blocks Model checking techniques and tools Task-level system architecture, task executive languages Continuous dynamics, quantitative analysis, reliability analysis

8. Carnegie Mellon: The Rare Glitch Project8Jeannette M. Wing Cross-Cutting Themes Exploit model checking techniques and tools. Focus on the task level. Incorporate continuous domains in our models.

9. Carnegie Mellon: The Rare Glitch Project9Jeannette M. Wing Verifying System Integrity Synchronization constraints  Publish-subscribe architecture  Cyclic-tasks with shared variables Research question: How can we reason about their aggregate behavior? Resource constraints  Continuous, consumable (e.g., fuel) and renewable (e.g., bandwidth, disk space) resources Research question: How should we specify and verify resource constraints? Real-time constraints  Quantitative timing analysis Research questions: How can we extend this technique to continuous time? How can we deal with dynamic process creation and deletion?

10. Carnegie Mellon: The Rare Glitch Project10Jeannette M. Wing Modeling the Environment Hybrid dynamics  Dealing with both discrete and continuous state variables Research question: How can we automate and scale differential equations models for large systems? Stochastic models  Dealing with uncertainty, unpredictability  Using continuous variables (e.g., probabilities) for reliability and cost-benefit analyses Research questions: How can we handle dependent events, cascading of events? Both nondeterministic and probabilistic state transitions?

11. Carnegie Mellon: The Rare Glitch Project11Jeannette M. Wing Usability Extracting models  Synchronization skeletons  Translators for task execution languages Research question: How can we balance expressibility of languages with efficiency of verification and user-friendliness? Explaining verification tool results  Adopt AI techniques to explain counterexamples for task executive programs.  Develop techniques to view and browse the temporal evolution of counterexamples. Research question: How can we create virtual execution traces that can be used by existing visualization tools?

12. Carnegie Mellon: The Rare Glitch Project12Jeannette M. Wing The Rare Glitch Tool Suite … Prism Checkmate PVS Symp SMV Specification Model Counter- examples Checkers and Provers Specification and Modeling Languages Analysis Engines Reliability and Cost Analyzers Explanation Generator Abstraction/ Refinement Processor …

13. Carnegie Mellon: The Rare Glitch Project13Jeannette M. Wing Preliminary Planning Technical  So far: Technical presentations of our current work  To do Identification of case studies Identification of common group project  Continue to pursue existing two-way and three-way collaborations Administrative  Weekly project meetings, project name, project web page

14. Carnegie Mellon: The Rare Glitch Project14Jeannette M. Wing Project Administration Principal Investigators  Ed Clarke, David Garlan, Bruce Krogh, Reid Simmons, Jeannette Wing (POC) Industrial connections  Honeywell Technology Center  CMU High Dependability Computing Consortium Years 3 and 5  Hold workshops for technical exchange with industry

15. Carnegie Mellon: The Rare Glitch Project15Jeannette M. Wing Preview of This Afternoon’s Talks Ed Clarke  Verifying Bus Protocol Standards for Embedded Systems Bruce Krogh  Model Checking for Hybrid Systems Jeannette Wing  Scenario Graph Generation and MDP-Based Analysis David Garlan  Model Checking Publish-Subscribe Software Architectures