Nowadays, there is a lot of Buzz, around the term “QA vs. QE”.
In earlier days, developers used to rely on quality assurance analysts in order to know the quality of software prior to deployment. Considering customary waterfall operational model—in which products are designed, employed and verified in chronological order, that’s why the quality assurance team is usually the last phase to eradicate any bug/s in the code former to production release.
In this model, the first and most primary role of a QA engineer is to primarily detect defects, size the impact, and—when they consistently discover an issue—send the code back to the developers to start the cycle afresh. On the other hand Quality engineering is basically about defect prevention versus defect measurement. QE is effectively an upstream event in which quality engineer’s work alongside cross-functional development teams to discover and decipher issues in real time.
Facilitated by an agile, iterative incremental development model, the move to QE ensures quality is scorched into the software at the onset of development and remains in focus not only up to but also beyond Production deployment.
This process utilizes quality measurements at build time allowing for continuous quality check prior to code submission in production. The stretched feedback loop has gone, in which QA and the development team play hot potato with the code base until a fix occurs. In an agile model, quality is simply engineered into the entire process as testing takes place parallel to development.
Although we cannot say that this is the only factor that leads to enriched product quality. While most CIOs who expertise a micro service-oriented architecture will emphasize the ease and pace of continuous deployment, the transition towards minor component-based releases which in turn also brings focus to specific desired outcomes.
Break up of a massive application may create more moving chunks as components, however, it means development teams and quality engineers are running tests on smaller pieces of code, with discrete functions to analyze and assess—few variables which result into the simplified root-cause analysis. In addition to that, test strategies which include performance, security, and end-to-end integration are driven into continuous integration and continuous deployment (CI/CD) pipelines for all applications.
Moreover, the CI/CD pipelines are extensible and consistent, allowing for all applications to be delivered in a similar fashion while also removing the need for “manual” code delivery, which inherently degrades the customer experience.
One of the core principles of quality engineering in software testing is test automation, which creates predictable developments. Prominence on automation through component testing and end-to-end user experience testing allows for feedback loops within seconds of code merges. Test failures force design teams to think through challenges and be proactive in solving problems immediately, knowing that if they do not, and the code cannot move forward.
Considering the acceptance of CI/CD, automated measurements and notifications have become innate to the agile process, that’s why if a build fails; development and QE teams are flagged instantly in order to deal with the issues on the spot. In an agile framework, everything from functionality and usability to API integration and deployment tests can be automated.
Even code style verification tools, known as a linter, can be preset, measured and structured to avoid programmatic or stylistic errors at build time. This highlights the importance of consistency in transitioning to an agile model that can also facilitate the extensibility of the platform.
As quality improves, the delivery and support model also evolves. For instance, software updates can be moved directly into production and evade the weeks or even months’ time that new software releases would conventionally occupy in a test environment. On the other hand, rapid deployment only becomes possible when users trust the QE process care that strengthens the quality and resiliency of software.
The paradigm shift from QA to QE might seem like mere semantics but quality engineering is the process that imparts and maintains quality in software delivery. As such, software QE not only provides a base for vendors adopting agile development models, it also helps end users who get assistance from improved quality and faster time to value.