Training Overview (old): Difference between revisions
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In order to build and execute the samples that we use in the training, please complete and verify the following prerequisites | In order to build and execute the samples that we use in the training, please complete and verify the following prerequisites | ||
# complete the [[Desktop Installation]]. Be sure to include | # complete the [[Desktop Installation]]. Be sure to include Perl, as described in the [[Desktop_Installation#Perl_Installation_.28Optional.29|article]], if you want to do training related to host-based test scripting. | ||
# setup [[Test Space Setup | Test Space]] for test result publishing | # setup [[Test Space Setup | Test Space]] for test result publishing | ||
# install the desktop development toolchain for your host, as described in the [[Off-Target Environment]] article. This is required for building the STRIDE runtime and samples. | # install the desktop development toolchain for your host, as described in the [[Off-Target Environment]] article. This is required for building the STRIDE runtime and samples. |
Revision as of 19:56, 24 September 2013
Our training approach is based on articles (here in the wiki) and on a set of code samples that readily execute in our off-target (desktop) environment. Our training focuses on a self-guided tour of the product using the samples we provide as the primary study material. Please review the sections below before proceeding to the specific training topics.
Prerequisites
In order to build and execute the samples that we use in the training, please complete and verify the following prerequisites
- complete the Desktop Installation. Be sure to include Perl, as described in the article, if you want to do training related to host-based test scripting.
- setup Test Space for test result publishing
- install the desktop development toolchain for your host, as described in the Off-Target Environment article. This is required for building the STRIDE runtime and samples.
- read the STRIDE Overview article(s) to familiarize yourself with the high-level approach and components of STRIDE.
How we train
Our training articles are based on a handful of samples that we provide with the Desktop installation package. The samples are self-documented (using doxygen or perldoc) and this content will be attached to the test report whenever a sample is executed.
The samples were created to be as simple as possible while sufficiently demonstrating the topic at hand. In particular, the samples are very light on core application logic (that is, the source under test) -- they focus instead on the code that leverages STRIDE to define and execute tests. As you review the sample code, if you find yourself confused about which code is the test logic and which is the source under test, try reading the source file comments to discern this. If you are still unclear about how the source is organized, feel free to contact us for clarification.
What you need to do
In order to get the full benefit from these training articles, we recommend you do the following:
- follow the wiki links we provide in the training articles. These links provide rich technical information on the topics covered by the training. These are also articles you will likely refer to in the future when you are implementing your own tests.
- read/review all sample source code prior to running. The samples consist almost entirely of source code, so it makes sense to use a source code editor (one you are familiar with) for this purpose.
- build and execute the samples using the off-target framework. If you completed your installation as instructed above, it should be fully functional when you do the training.
- review the reports that are produced when you run the samples. The reports give you a feel for how data is reported in the STRIDE Framework. The extracted documentation is also provided in the report.
- For most samples, we provide some observations that help summarize aspects of the results that might be of interest to you. These observations are not necessarily comprehensive - in fact, we hope you'll discover other interesting features in the samples that we haven't mentioned.