Functional testing of LAVA source code


Unit tests are routinely run against each change in a review and again nightly against the master branch, as well as during development. However, unit tests cannot properly test the run() functions or performance of the code with real hardware. Two extra levels of testing are available:

  • meta-lava - tests the run() functions against static log files. This is useful for devices which are not available to a particular instance but will need updating if changes in the code cause differences in the messages sent to the device.

  • Functional testing - running test jobs on real hardware. The extra cost of infrastructure, administration and maintenance is worthwhile to ensure that changes actually perform the required work. Also provides opportunities to test the scheduling of the queue and can highlight resource limitations.

The LAVA UI is not part of functional testing. Wherever possible, unit tests are used for the UI. Functional testing relates to the code paths required to schedule, run and cleanup test jobs.


meta-lava is a way of running idealized test jobs to test changes in the LAVA codebase. It was developed to provide limited test coverage when suitable hardware was not available. It can be used to provide test coverage for code which detects unusual or intermittent behavior by replaying a static log against changes in the codebase. meta-lava creates a DummySys device based on real log files and then checks that the inputs from LAVA are correct for that specific use case.

meta-lava is a python script that will:

  • build lava-server and lava-dispatcher docker image

    • install lava-server or lava-dispatcher using debian packaging

    • fetch the source from git and add the right symlinks

  • start the containers and link them in the same network (lava-worker, lava-server-gunicorn)

  • during the startup, fetch the last git commits (in case the docker image were build with an old version)

  • wait for the xmlrpc api to show up

  • wait for the worker to be up and running (polling the xmlrpc api)

  • run a bunch of lava jobs and compare the results with the expected ones.

Currently we test:

  • tests/health-checks: Check that lava is sending exactly the same set of commands and providing the right binaries (ramdisk, kernel, dtb over tftp)

  • tests/bootloader: Check that lava is detecting and classifying common bootloader errors

  • tests/notitications: Check that lava is sending the notifications as expected (no irc or emails yet)

Future plans

  • Add more use cases and job output (logs).

  • Make test runs public

Purpose of functional tests

Functional tests serve to check the changes in the codebase against unchanging test job images, resources, metadata, submitter and results running on real hardware.

Functional tests are similar to health checks and both differ from test jobs used elsewhere in your CI due to fundamentally different objectives.


Often, functional tests are developed from the sample test jobs submitted as part of code reviews to merge changes to integrate a new device-type. Unit tests will need all URLs to be permanent to be able to check the code being reviewed.

In particular, functional tests exist to test code paths involved in running test jobs which cannot be tested using other means, e.g. unit tests or meta-lava. Testing the LAVA codebase using real hardware is not without problems; infrastructure failures need to be isolated from the results and issues like resource starvation need to be managed. Where possible, testing the LAVA codebase needs to be done within the codebase using unit tests or using meta-lava.

Functional tests are measured on a binary Complete or Incomplete for each submitted test job.

For a successful run, the suite of functional tests provides a clean set of Complete test job results. To be able to identify all test jobs in the functional test run, always use a dedicated submitter for functional tests, distinct from user tests and other automated tests.

Requirements for a functional test job

The overriding principle for a functional test is that the job is testing the LAVA software code, not the deployed system. This is similar to a health check which is designed to test the DUT and related infrastructure to provide an assurance that test jobs will be able to run successfully.

  1. Image files used in functional tests need to remain static, and they need to be stored in static locations. Do not rely on files that may change easily, e.g. releases on If you need those files, copy them to a stable location.

  2. Use stable, unchanging tools (e.g from the stable release of a Linux distribution like Debian).

  3. Use the deployment tools from the distribution to ensure that the behavior of those tools does not change unexpectedly.

  4. Use checksums to ensure the downloaded files have not changed.

  5. Separate out single and multiple deployment test jobs. If the DUT can support OE and AOSP or ramdisk and NFS, submit one test job for each variant as well as a functional test explicitly designed to test that the DUT can run a test in one environment and be redeployed with a new environment, if that can be supported.

  6. Ensure that advanced LAVA software functionality is also covered by submitting representative MultiNode test jobs, especially if the staging instance is capable of supporting VLANd

  7. Unreliable functional tests need to be triaged and removed if the problems cannot be fixed. This may lead to the underlying code support being deprecated or removed, including a device-type template.

  8. Unreliable devices need to be triaged and test jobs using those devices removed from the functional tests if the problems cannot be fixed. If those devices are the sole use of a particular deployment method or boot method, then that code support needs to be reviewed and possibly removed.

  9. If firmware has to be upgraded on devices and the functional test needs changes, create a new functional test with new metadata. Remove the old functional test unless devices running the old firmware remain available using a separate device-type.

  10. Removing a functional test requires a review to remove source code support for a deployment method, boot method, device-type template etc.

  11. Email notifications are optional but can be useful. Use sparingly to avoid flooding the developers with noise.

  12. If a particular device or deployment method or boot method is not covered by at least one functional test, add a new functional test and/or add meta-lava support.

    If a test job exists which cannot be made into a functional test, and meta-lava support is not available, the code support for the affected method will need to be reviewed with a view to probable removal.

  13. Test job definitions also remain static.

    1. No changes in prompts, metadata, image files, checksums, LXC suites or submitter.

    2. Changes to timeouts only by code review to handle resource limitations.

    3. Infrastructure to remain static, as far as possible. Only change ports (PDU, USB etc.) when failures have been identified. As much as possible, leave the devices undisturbed in the racks.

    4. Minimal work done in the test shell definitions. Smoke tests and setup checks if specific external hardware is configured, e.g. ARM Energy Probe. Any setup code must use lava-test-raise for all known failure modes.

  14. Devices are checked as per the current master branch configuration.

    1. Devices which do not have full support already merged are not candidates for functional testing.

    2. Test job use cases for which the device support is still in development are not candidates for functional testing.

    3. Test jobs which download third-party software which may change outside the control of the functional test are not candidates for functional testing.

Test jobs and use cases outside of these requirements can still be submitted on a regular basis but not using the same metadata or job submitter as the functional tests. Completion of these test jobs will not count towards the functional test report. Consider using the notification support to send email to developers when such tests finish in state Incomplete as there will be no other coverage for such failures.

Using the functional test frontend

The LAVA software team will be setting up a dedicated frontend to run functional tests across multiple instances to increase the functional test coverage to include devices not available in the current instances.

This service will coordinate:

  • The list of test job submissions used in functional testing.

  • The set of test shell definitions used in functional testing.

  • The submission of functional tests to instances according to device availability, as determined using the XML-RPC API.

  • The selection of the appropriate workers for available devices on each instance, using the relevant build of the master branch.

  • The retrieval of functional test results from multiple instances.

  • The display of a summary of the functional tests for a specific build of the master branch.

Dedicated workers

If your instance has a mix of devices, some with upstream LAVA support and some without (or with support in development / review), then one or more dedicated workers will be needed to work with the functional test frontend.

Any one piece of hardware can run multiple lava-worker processes, as long as the hostname option is unique.

For functional testing, the worker will need to be running a specific build of the master branch, so docker based workers will need to be available.

During the functional tests, the relevant devices will be switched to the functional test worker in the relevant docker container (API is yet to be scoped) before test job submissions start. When all functional test jobs are complete, the devices are switched back to the original worker.

Currently, functional testing occurs on and more work is needed to support combining results across multiple staging instances. More content will be added here as the relevant services are developed.