testing-debugging

name	testing-debugging
description	Testing and debugging for Zephyr RTOS. Covers the Ztest framework for unit and integration tests, the Twister test runner for automated HIL/SIM validation, and advanced tracing/debugging techniques (SystemView, Thread Analyzer, Stack analysis). Trigger when writing unit tests, setting up CI/CD pipelines, or analyzing system performance and latency.

Zephyr Testing & Debugging

Ensure code quality and system reliability using Zephyr's comprehensive testing framework and observability tools.

Core Workflows

1. Ztest Framework

Write robust unit and integration tests for native simulation and real hardware.

• Reference: ztest_framework.md
• Key Tools: ZTEST_SUITE, ZTEST, zassert_equal.

2. Twister Test Runner

Automate test execution across multiple platforms and generate professional reports.

• Reference: twister_testing.md
• Key Tools: twister script, testcase.yaml, hardware mapping.

3. Tracing & Debugging

Analyze system behavior, timing, and memory usage with advanced tracing tools.

• Reference: tracing_debugging.md
• Key Tools: CONFIG_TRACING, Segger SystemView, Thread Analyzer.

Quick Start (Ztest)

#include <zephyr/ztest.h>

ZTEST_SUITE(basic_test, NULL, NULL, NULL, NULL, NULL);

ZTEST(basic_test, test_pass) {
    zassert_true(true, "Boolean evaluation failed");
}

Professional Patterns (Reliability)

• Continuous Integration: Integrate Twister reports (twister.json) into CI/CD pipelines for automated regression testing.
• HIL Validation: Use hardware maps to consistently run critical hardware tests on real devices during every release cycle.
• Stack Safety: Always enable CONFIG_STACK_SENTINEL and the Thread Analyzer during development to catch memory issues early.

Automation Tools

• twister_smoke.py: Run a small Twister suite and print result summary.

Examples & Templates

• testcase.yaml.template: Starter testcase metadata for Twister.

Validation Checklist

• twister executes selected test suites with no unexpected failures.
• At least one ZTEST suite runs in simulation and reports pass/fail correctly.
• Tracing or thread-analyzer output is captured and reviewed for hotspots.
• CI artifacts include machine-readable reports (for example twister.json).

Resources

• References:
  • ztest_framework.md: Writing tests with expectations and suites.
  • twister_testing.md: Using the test runner and metadata.
  • tracing_debugging.md: Tracing, stack analysis, and debugging backends.
• Scripts:
  • twister_smoke.py: Lightweight Twister runner with summary output.
• Assets:
  • testcase.yaml.template: Reusable testcase metadata template.