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Most people interact with software applications daily, whether it’s on a tablet, smartphone, or computer, because of the rapid growth in mobile technology, the web, and app development industry is more competitive than ever before. This is why popular software programs are visually appealing, easy-to-use, and stable. The only way to achieve this, apart from the effective development, is with thorough software testing.
To automate or not to automate: that is a never-ending debate. Let's face it: a fast-growing amount of data in software testing and programming leaves no choice but to replace manual practices with more efficient automated solutions. Although it's still not always clear which situations are best suited for automation, the tools are becoming refined and more accurate with each year, while the role of QA automation tester is dropping. The world of IT is moving fast to automating technical aspects of software. But the use of the human resource is left for more important tasks.
Bain's recent study predicts that IoT markets combined will reach over $520 billion by 2021. In addition, data analytics will be the fastest developing sector of IoT. This means that system integration, connectors, consumer devices, network, and data centers are key areas in the IoT market. Since IoT is showing immense promise, software testing is one of the ways to help secure the industry's bright future and make all these predictions come true.
But first, what can we expect from IoT in the next few years?
You might have come across DevOps so often that it may seem to penetrate each and every organization slightly related to IT. But the reality is different, as always. The point is that this model is far more complicated to apply compared to Agile and other popular forms of SDLC because the role of each department undergoes significant changes.
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Although many definitions are available, we think of DevOps as the space for keeping the software deployable regardless of the new features implemented. Most importantly, DevOps means that everyone — from Jr. Analyst to developer, QA engineer, project manager, and owner — takes equal responsibility and makes a contribution to product success.
Software testing performed by human resources still has its value, although Artificial Intelligence (AI) is a promising way to make the process easier, faster, and clearer. Someday, the emerging technology of AI may force software testers to start looking for a new job elsewhere. But don't get tripped up with such predictions.
Strategies to implement AI and machine learning are far from perfect; companies still have plenty of challenges to work through. However, one thing is certain: the use of AI by QA professionals would upgrade the whole testing process, enhance testers' professional skills, and contribute to business growth.