Here’s how machine intelligence is making a dent in the testing market:
- Machine-written test cases;
- Automating API test generation;
- Automated UI testing;
- Creating automated tests more reliable, and others.
But that’s not even half of the superpowers it possesses.
Eventually, the unbeatable combo of NLP, ML, and reasoning will help developers minimize their direct participation in the process and automate testing completely.
It Fits
Modern approaches are also merging principles of DevOps with QA into QAOps. This novel approach inherits the best from CI/CD projects and combines it with the best from the QA process.
Thus, instead of having a minor role, QAOps introduces quality assurance into the whole software development lifecycle.
It keeps the testing team constantly engaged and helps them fix bugs sooner, boosting the value delivered to users.
Interconnected Future
This year, the Internet of Things will continue its exponential growth accelerated by 4G and 5G network standards.
It means that the projected surge in the number of IoT devices will increase the need and scope of IoT testing as well. Hence, QA engineers should be ready to face the new challenges and test the software built for entirely new types of hardware.
Among the micro-trends of IoT testing are also IoT Network Security Challenges, Big Data Testing, and Micro Services Test Automation.
Testing in Chains
This staggering growth suggests that record-keeping databases are some of the most promising market technologies in 2021.
From healthcare and energy to supply chains and media, blockchain has been making its mark on almost every industry.
Therefore, we’ll see the tech market crying out for QA specialists with blockchain domain skills to provide professional testing services.
