Halifax, Nova Scotia — August 21, 2019 — Less than three years ago, QRA Corp developed QVscribe to leverage Natural Language Processing. The goal was to assist engineers in writing unambiguous and compliant requirements for complex systems engineering projects. Today, the tool has emerged as a leading requirements authoring tool for teams around the world – reducing requirements review time by over 50% by catching weaknesses & compliance issues during the authoring process.
Leveraging Natural Language Processing for the requirements engineering process is crucial for the efficient development of today’s complex and safety-critical machines. To further facilitate the authoring of this critical documentation, QRA has developed automated templating and compliance checking of the celebrated Easy Approach to Requirements Syntax (EARS) and INCOSE Guidelines for Writing Requirements. Both EARS templating and INCOSE Guideline compliance checks are now available within one update: QVscribe 2.10.
The authoring and structural conformance of EARS enables engineers to jumpstart the authoring of their requirements. Users can select a template from multiple fill-in-the-blank EARS scenarios such as ubiquitous, state-driven, event-driven, and unwanted behaviour. These templates ensure that all requirements are structured to be accurate, clear, and a dream to work with.
The INCOSE Guide for Writing Requirements is one of the most widely used and highly respected references in requirements engineering. Due to the INCOSE rule set being so vast – forty-one rules in the latest revision – accounting for all of them during authoring and review proved to be cumbersome and prone to error. Fortunately, QVscribe’s quality analysis now includes most of INCOSE’s Guidelines such as immeasurable quantification, passive voice, superfluous infinitives, and optional escape clauses – to name a few. Now, checking for compliance with the majority of the INCOSE Guidelines is efficient and proactive throughout the authoring process.
“Increasingly, the content of the requirements are the key drivers of success. By automating the authoring process to conform with industry-wide best practices, we can streamline the requirements engineering process and enable the designers and creators to better focus on completeness and correctness.” – Jordan Kyriakidis, QRA Corp CEO
To learn more about QVscribe 2.10 and how leveraging Natural Language Processing enables engineers to build safety-critical machines confidently and efficiently, visit qracorp.com/qvscribe.