Software testing plays an imperative role in enhancing the quality of any app or website. In fact, 40% of the IT budget will be allocated on software testing in 2019.
Keeping this scenario in mind, we are presenting 7 predictions in the software testing industry in 2019.
The Agile Software Development Methodologies Will Create Confusions Among Software Testers
The rise of agile testing methodologies has already created so many misconceptions and confusions regarding the role of software testers.
In the near future, the situation is expected to get more complicated. This because the agile software testing is rapidly becoming the standard instead of just an advanced approach for the software development teams.
Nevertheless, ultimately agile will truly become universal and companies in all sectors will gain a greater degree of understanding of these techniques. After that, the role played by testers on agile teams will become clearer, and testers would not need to persuade the C-level of their importance.
The Expectations from The Software Testers Will Grow in The Future
The expectations from the testers will grow even more in the future. They will have to learn more about the latest test management tool and testing strategies. Experts believe that testers will have to update their skills and be aware of how code functions and businesses work to generate profit.
This does not just include technical know-how. In fact, in the near future, the majority of the company leaders are expected to play an assertive role in guiding development and QA broadly. These days, speaking up and presenting practical insight will permit software testers to stand out.
Automation’s Popularity Will Grow
The impact of automation on software testing is expected to expand. The fast-growing amount of data consumed in development and software testing will make it difficult for companies to uphold efficiency while continuing to depend more on manual practices.
Automation is expected to become a default approach for the majority of the elements of software testing. Presently, automation is the biggest challenge for numerous software testing teams. this is because it is sometimes not clear which situations are best suited for automation testing. Companies will begin to apply these tools whenever possible to enhance accuracy and efficiency in their testing processes, as automation becomes more refined and common.
Also Read: Automation Testing In The Agile World
Growing Focus on Digital Testing
This is an era of digital transformation. The software industries are boarding on decreased time to market life cycle with an enhanced focus on testing and QA. The major approach of these organizations is to include enhanced functional testing across the channels. You will witness more digital testing in 2019.
A huge rise in IOT Testing
Presently, a majority of the business operations are adopting Internet of Things (IoT). IoT apps and devices are tested for usability, security, and performance. Majority of the customers depend on the IoT testing prior to the purchase of their product. All the IoT devices need internet connectivity thus susceptible to risks and security defects. This guarantees the requirement for IoT testing. This trend is expected to grow more in the coming time period.
More Focus on Machine learning in testing
Machine learning has brought revolutionary changes in processes and workflows. Machine learning can be used for test suite optimization, predictive analysis, log analytics, traceability and defect analytics. Obviously, every tester wants effective traceability and defect analytics. Therefore, the organizations are going to place more focus on machine learning in testing.
Big Data Testing
Big data is the huge amount of data produced at a high speed. Testers have to confirm that terabytes of data are effectively processed using other supportive components and commodity cluster. This form of testing concentrates on functional testing and performance testing.
Data quality is an important factor in big data testing. It is verified prior to the beginning of the testing procedure. The quality of data is evaluated on the basis of different characteristics like data completeness, duplication, validity, consistency, accuracy, and conformity. In the coming year, big data testing will require more concentration from the testers.