Race Conditions
Understanding concurrency defects and the role of deterministic execution
Note: This page illustrates concurrency behaviour under deterministic and non-deterministic execution models. Examples are simplified and intended to demonstrate architectural principles. Actual system behaviour depends on programming model, execution constraints, and integration context. Deterministic execution does not eliminate all defects or operational risk.
A Significant Class of Software Defect
Race conditions are timing-dependent bugs that occur when multiple threads access shared resources concurrently. They are among the most challenging defects to detect and diagnose: often silent during testing, difficult to reproduce, and potentially serious in production.
Post-incident analyses of several high-profile system failures have identified timing-dependent software behaviour among contributing factors. Investigations into the Therac-25 radiation therapy incidents highlighted race condition-like behaviour in the safety interlock system. The 2003 Northeast blackout analysis implicated timing issues in energy management software. The Mars Pathfinder mission experienced priority inversion—a specific type of concurrency issue. Toyota's unintended acceleration recalls involved scrutiny of concurrent access patterns in electronic throttle control software.
Traditional operating systems are inherently susceptible to race conditions because thread scheduling is non-deterministic. Two threads accessing the same memory location may interleave differently on each execution, producing different results. Deterministic platforms can significantly reduce this class of defect by constraining execution order to reproducible, predefined sequences.
Understanding Race Conditions
The Classic Race Condition
The visualization above demonstrates a simple race condition: two threads (A and B) attempting to increment a shared counter. In a correct execution, if both threads increment the counter, it should increase by 2. But watch what happens in the Traditional RTOS panel when you run it multiple times—you may see varying final values, seemingly at random.
This non-determinism occurs because thread scheduling is unpredictable. Sometimes Thread A reads the counter, then Thread B reads it (both see the same value), then both write back incremented values—but only one increment is preserved. The other is lost. This is called a read-modify-write race condition.
Why Race Conditions Are Challenging
The Testing Challenge
Race conditions are often called Heisenbugs—bugs that can disappear when you try to observe them. Add logging to debug the issue? The timing changes, and the bug may vanish. Run in a debugger? Different timing, different behaviour. Deploy to production? The race condition may return.
A system can pass many test iterations without triggering a race condition, then exhibit unexpected behaviour in production when timing conditions align. This is why race conditions contribute to some of the most challenging field issues in safety-critical systems.
Common Manifestations
- Data corruption: Shared data structures become inconsistent, causing downstream issues
- Deadlocks: Threads wait for each other indefinitely, freezing the system
- Priority inversion: High-priority threads blocked by low-priority threads
- Use-after-free: One thread frees memory while another is still using it
- Double-free: Two threads free the same memory, corrupting the allocator
- Initialization races: Thread B uses data before Thread A finishes initializing it
Traditional Mitigation Approaches (And Their Limitations)
Engineers have developed numerous techniques to manage race conditions in non-deterministic systems:
Locks and Mutexes
Approach: Protect shared resources with locks. Only one thread can access at a time.
Limitations: Can introduce deadlocks, priority inversion, performance bottlenecks, and verification complexity
Lock-Free Data Structures
Approach: Use atomic operations and memory barriers to avoid locks.
Limitations: Complex to implement correctly, performance can be unpredictable, difficult to verify
Message Passing
Approach: Reduce shared memory, communicate via messages.
Limitations: Message ordering can still be non-deterministic, latency may be unpredictable
Static Analysis Tools
Approach: Analyze code to detect potential race conditions.
Limitations: Can have high false-positive rates, may not detect all races, addresses symptoms rather than root cause
These approaches share a common characteristic: they attempt to manage non-determinism rather than constrain it at the architectural level. They add complexity and still face challenges in providing complete coverage.
How Determinism Addresses Race Conditions
Look at the MDCP panel in the visualization. Run it multiple times. Notice the final value is consistent. This consistency comes from deterministic execution order, not from added locks or atomic operations.
Tick-Based Execution
In deterministic platforms such as MDCP, all events (including thread scheduling decisions) align to discrete time boundaries called ticks. Within a tick, execution order is deterministic based on event properties and system state—not on unpredictable interrupt timing.
When Thread A and Thread B both want to access the shared counter, the scheduler assigns them to specific ticks in a deterministic order. Thread A executes first at tick N, Thread B executes at tick N+1. Under this model, the interleaving order is constrained rather than variable.
✓ Result: Reduced concurrency risk, simplified synchronization strategies, and improved reproducibility for verification
The Reproducibility Advantage
In a deterministic system, given:
Initial system state: S₀ Input event sequence: E₁, E₂, E₃, ..., Eₙ
The final system state Sₙ is reproducible. Every execution with the same inputs produces identical state transitions. This transforms verification: instead of testing many interleavings hoping to find race conditions, you can analyze deterministic execution paths and verify that concurrency behaviour is as intended.
The set of reachable execution states is significantly constrained, improving confidence that verified behaviour aligns with deployed behaviour.
Certification and Safety Considerations
Automotive (ISO 26262 / ASIL)
ISO 26262 requires "freedom from interference"—evidence that software components cannot interfere with each other through shared resources. In traditional systems, this requires extensive locking, testing, and static analysis. Race conditions are a primary concern in ASIL-C and ASIL-D certification.
With deterministic execution, freedom from interference can be supported architecturally. Concurrency behaviour becomes reproducible and analyzable, which can support stronger forms of evidence for certification.
Aerospace (DO-178C)
DO-178C Level A software (flight-critical) requires demonstrating that the software cannot enter hazardous states. Race conditions are a source of unanalyzed states—states that weren't considered during verification but can occur due to timing variations.
Deterministic platforms constrain the set of reachable states. This can simplify verification and improve confidence that verified behaviour reflects operational behaviour.
Medical (IEC 62304)
Medical device software in Class C (life-critical) must demonstrate "predictable and reproducible" behavior. Race conditions are inherently unpredictable. Regulatory reviewers specifically examine concurrency handling in device submissions.
Deterministic execution provides the reproducibility that supports regulatory requirements. Hazard analysis becomes more tractable because behaviour is constrained.
Historical Context: Concurrency Issues in Safety-Critical Systems
The following examples are drawn from published incident analyses and academic literature. Root causes in complex system failures are typically multifactorial; timing-dependent software behaviour was identified as a contributing factor in each case.
Therac-25 Radiation Therapy Incidents (1985-1987)
Investigations into the Therac-25 medical linear accelerator incidents identified timing-dependent software behaviour among contributing factors. Analysis suggested that specific operator input sequences during initialization could bypass safety checks under certain timing conditions. The behaviour was difficult to reproduce, occurring infrequently across many operations.
Northeast Blackout (2003)
Post-incident analysis of the 2003 Northeast blackout identified timing issues in GE Energy's XA/21 energy management system among contributing factors. The analysis suggested that alarm system behaviour was affected when multiple conditions occurred simultaneously. The issue had existed for an extended period but manifested only under specific circumstances.
Mars Pathfinder Priority Inversion (1997)
NASA's Mars Pathfinder rover experienced system resets attributed to priority inversion—a type of concurrency issue where a low-priority thread can block a high-priority thread. The issue occurred when specific combinations of tasks executed simultaneously. Engineers were able to diagnose the issue using telemetry data transmitted from Mars.
This incident illustrates the value of reproducible execution: with deterministic replay capability, such issues can potentially be reconstructed more quickly from logged execution traces.
Toyota Electronic Throttle Control Analysis (2009-2011)
Independent analyses of Toyota's electronic throttle control software examined concurrent access patterns and task scheduling. While findings and interpretations varied, the reviews highlighted challenges in verifying concurrent software behaviour in complex embedded systems. NASA's independent review noted areas where concurrency analysis could be strengthened.
Discuss Deterministic Execution Models
The visualization above demonstrates a simplified race condition with two threads and one counter. Real safety-critical systems have many threads, numerous shared resources, and complex interactions. Traditional mitigation approaches add complexity and face verification challenges.
Deterministic architecture addresses concurrency at the execution model level: if execution order is constrained and reproducible, certain classes of race conditions can be prevented by construction, while remaining behaviour becomes analyzable.