Manual test cases are difficult to write and costly to maintain. Beaumont Brush suggests that one of the more important but infrequently-discussed reasons is that manual tests are usually written in natural language, which is ineffective for describing test cases clearly. Employing a domain-specific language (DSL), Beaumont and his team approach their manual test cases exactly like programming code and gain the benefits of good development and design practices. He shares their coding standards, reusability approach, and object models that integrate transparently into the version control and code review workflow. Beaumont demonstrates two DSL approaches―a highly specified DSL written in Python and a more functional DSL that leverages Gherkin syntax and does not require a computer language to implement. By making your test cases easier to write and maintain, your team will improve its test suite and have time for automating more tests.
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The quality lead for hardware controls projects at Dematic, Inc., Beaumont Brush started his
career fifteen years ago as a developer of natural language processing and information
extraction technologies. Beaumont became a product manager for companies that leveraged
these technologies to accomplish such tasks as intelligent patent searches, automatically
matching résumés to job descriptions, and extracting event data from unstructured field
intelligence reports. Since settling into quality assurance ten years ago, he has developed and
implemented agile test processes and led test automation projects. Beaumont's primary
interest and specialty are in tightly integrating quality practices into the development lifecycle.
Beaumont Brush
Dematic, Inc.
