Design of Dynamic Testing Tool for VxWorks Concurrent Programs

As real-time embedded systems grow more complex, concurrent programming with multithreads and interrupts has become a cornerstone of modern design. However, testing such concurrent systems in VxWorks remains a challenge due to the overlapping execution of threads and interrupts, which introduces uncertainty and hidden concurrency errors.

This blog explores the dynamic testing tool for VxWorks concurrent programs proposed by researchers, highlighting its framework, algorithms, and experimental validation.

Why Concurrency Testing Matters in VxWorks

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• Real-time embedded systems require high reliability.
• Concurrency introduces uncertainty due to random interleavings of threads and interrupts.
• Common concurrency errors include:
  • Data races
  • Deadlocks
  • Atomicity violations

Traditional testing methods (static analysis or simulation) often fall short. A dynamic testing tool that works directly with running programs provides a more practical solution.

Framework of the Dynamic Testing Tool

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The tool is built around Labeled Transition Systems (LTS) as the formal model for concurrent programs. The framework consists of four main modules:

1. Program Analyzer

   • Extracts shared objects and execution states.
   • Converts complex statements into simple forms (if, while, goto, assignments).
   • Builds the state space model for concurrency.

2. Program Instrumentor

   • Inserts monitoring hooks into source code.
   • Handles shared objects, thread functions, and interrupt service routines (ISRs).
   • Tracks access to shared resources and interrupt events.

3. Interrupt Generator

   • Simulates realistic interrupt signals.
   • Uses high-speed serial interfaces (HSSI) for accurate timing.
   • Allows systematic exploration of interrupt-triggered concurrency errors.

4. Execution Controller

   • Manages execution flow.
   • Implements Dynamic Partial-Order Reduction (DPOR) to reduce redundant state exploration.
   • Detects concurrency errors in real time.

Key Algorithms

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1. Dynamic Partial-Order Reduction (DPOR)

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• Reduces the state explosion problem in concurrency testing.
• Eliminates redundant interleavings while ensuring coverage.
• Extended to handle multi-thread + multi-interrupt scenarios in VxWorks.

2. Concurrency Error Detection

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The tool checks for:

• Deadlocks – by analyzing blocked states.
• Atomicity violations – by detecting inconsistent read/write sequences.
• Data races – when higher-priority interrupts preempt lower-priority tasks improperly.

Testing Workflow

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1. Analyze source program → generate LTS model.
2. Instrument code → insert hooks for threads, interrupts, and shared objects.
3. Compile with instrumentation libraries → produce controllable executables.
4. Deploy to target system (ARM/PPC with VxWorks).
5. Run with Execution Controller + Interrupt Generator → dynamically explore all concurrency paths.
6. Report detected concurrency errors for debugging.

Experimental Platform & Results

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• Hardware Platforms:
  • ARM (Exynos 4412, VxWorks 5.5)
  • PPC (MPC8247, VxWorks 5.5)
• Controller: Intel i7 with Windows
• Interrupt Generator: S3C6410 with Linux

Results

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• DPOR-based tool significantly reduced execution time.
• Example:
  • Without DPOR: 1193k transitions, 472s
  • With DPOR: 236k transitions, 89s
• Compared with VeriSoft and thread-based methods, the tool achieved higher accuracy and better efficiency, especially in multi-interrupt cases.

Why This Matters for Developers

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For VxWorks system developers, this dynamic testing tool provides:

• Automated concurrency error detection in real applications.
• Support for multithread + multi-interrupt programs, reflecting real-world embedded systems.
• Efficient state-space reduction, making large systems testable.

This approach helps ensure safety, reliability, and correctness in mission-critical embedded applications such as aerospace, defense, and industrial control.

Conclusion

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The dynamic testing tool for VxWorks concurrent programs offers a powerful solution to detect data races, deadlocks, and atomicity violations in embedded real-time systems. By combining LTS modeling, instrumentation, and DPOR algorithms, it achieves high accuracy and efficiency.

For developers working on complex embedded systems, adopting such a tool can drastically improve system robustness and reduce the risk of concurrency-induced failures.