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The Quality Engineer’s Field Guide to Test Automation

 One of the most interesting aspects of test automation is how fast the sector is going: manual testers are rapidly becoming test automation specialists and further transforming their organizations into cutting-edge innovators in software. As a consequence, the software test automation aspect is changing swiftly, especially as features like low-code, AI, and machine learning obtain broad adoption and frameworks like Agile and DevOps accelerate software development.

This guide is a resource designed to support quality professionals – whether they’re manual testers, test automation engineers, or team leaders – know the exciting world of test automation and how the next generation of intelligent test automation solutions is making complete test coverage more convenient than ever, putting QA at the core of high-velocity software development.

 

Legacy test automation tools

Overworked and understaffed QA teams are simply a new phenomenon, so it’s not shocking that there’s a generation of test automation tools that originated in the 2000s. The major names left standing such as SmartBear, Selenium and Sauce Labs, and Tricentis are likely well-known to those in the software industry have remained to develop new features and contributions in an effort to put up with modern software development.

The older, more established test automation tools rely on an ecosystem strategy that highlights code-heavy tests that need significant maintenance, particularly as applications evolve. Their dominance has added to a division in the QA community as testers either develop coding skills, which isn’t always a likely option, or concentrate on manual testing, which has limited capability. Despite the potential to fully unify the software development method under Agile and DevOps, this division continues in QA. As companies adopt test automation to promote faster, more regular code releases, the training curve with code-heavy legacy tools can be a significant obstacle and include further pits into their workflow.

An additional difficulty with legacy test automation tools is that they’re intended for control versus speed and performance. Coding testing frameworks can be beneficial when fine-tuning a complex test, but when running a number of variables and assertions tests become rigid and likely to break. If the development team is sending new code on a weekly or daily basis, testers jeopardize losing any time saved by test automation to the time required for test maintenance. As a consequence, various high-velocity software teams find legacy test automation frameworks loitering in a DevOps world.

 

The next generation of test automation solutions

With the emergence of DevOps and an Agile method to software development, it became clear that current test automation tools needed the adaptability to maintain weekly or even daily releases. The next generation of test automation tools addresses the requirements of high-velocity teams and provides advanced automation abilities to support them fully into the future.

An important feature for next-generation test automation solutions is the usage of AI and machine learning to improve tests automatically modify to product modifications. As noted above, traditional testing tools can break if even the smallest cosmetic changes are presented, making them unsustainable for organizations that push new code on a frequent basis. Newer testing solutions have accepted this challenge and have renewed test automation with features, which allow tests to support a broad range of modern development frameworks with an agnostic strategy to recognizing and adapting to changes.

New test automation companies have also moved away from the code-heavy requirements of their antecedents to benefit from the rise of no-code and low-code interfaces. Capturing the life of the application’s end-user in a test is an important differentiator when navigating this section of the test automation industry. However, various no-code tools are restricted in capability which also defines adoption over the software development team, and doesn’t promote the distribution of expertise from experienced testers. Modern test automation tools are easing the breakdown of the silos in the DevOps workflow, allowing teams to take benefit of the different skill sets of manual testers, QA engineers, and software developers to embed quality testing over the development lifecycle.

With the next generation of test automation solutions, committing to a shared idea for product quality, customer satisfaction, and growth is essential to making a successful partnership. Modern test automation solutions are better placed to hear and learn from their user communities and utilize those conversations to notify the future of intelligent test automation.

 

Continuous learning is key

Eventually, the purpose of both the quality employee and the employer is diversity. QA and test professionals require to expand their skills as companies need more soft skills and coding accuracy to support existing competencies in quality fundamentals.

Meanwhile, companies trying to more seamlessly integrate quality functions into DevOps teams should operate to create a culture of inclusion that forms a team with a wide base of professional and life practices upon which to draw.

The world is becoming automated as part of Industry 4.0, and it is time we all progress towards this to help make it more efficient. We must begin automating. At the same time, we need to begin sharing and giving the ideas and automation assets with the rest of the test automation community.

 

Testunity is a SaaS-based technology platform that is operated by a wide community of tester and QA spread around the globe. We provide end to end software testing cycle and ensure the best results. Testunity helps in delivering the project on time and without any bugs or issues without the need to spend much on testing.

For more on automation testing in QA, visit our blog or connect with our testing experts at TestUnity.

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