Archive tests
Archive Tests
Some degree of change control or version control can be extremely valuable for
managing scripts, scenarios, and/or data changes between each test execution, and for
communicating these differences to the rest of the team. Some teams prefer to check their
test scripts, results, and reports into the same version-control system as the build of the
application to which they apply. Other teams simply save copies into dated folders on a
periodic basis, or have their own version-control software dedicated to the performance
team. It is up to you and your team to decide what method is going to work best for you,
but in most cases archiving tests, test data, and test results saves much more time than it
takes over the course of a performance-testing project.
Additional Considerations
Consider the following additional points when creating baselines and benchmarking:
·
You can use archived test scripts, data, and results to create the baseline for the next
version of your product. Archiving this information together with the build of the
software that was tested satisfies many auditability standards.
·
In most cases, performance test scripts are improved or modified with each new
build. If you do not save a copy of the script and identify the build it was used
against, you can end up doing a lot of extra work to get your scripts running again in
the case of a build rollback.
·
With the overwhelming majority of load-generation tools, implementing the test is a
minor software-development effort in itself. While this effort generally does not need
to follow all of the team's standards and procedures for software development, it is a
good idea to adopt a sound and appropriately "weighted" development process for
performance scripts that complements or parallels the process your development team
employs.
Summary
Performance test execution involves activities such as validating test
environments/scripts, running the test, and generating the test results. It can also include
creating baselines and/or benchmarks of the performance characteristics.
It is important to validate the test environment to ensure that the environment truly
represents the production environment.
Validate test scripts to check if correct metrics are being collected, and if the test script
design is correctly simulating workload characteristics.