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Significance of Testing in today's Digital Environment
Quality Analysis (QA) is one of the most significant aspects of the software development process. QA analysts collaborate with software developers to ensure that the most utilatrian software is delivered within the stipulated time frame.
The days of manual software testing are gone as many innovative software tools that have enhanced the efficiency of the software testing process. In recent years, many trends have emerged that has put the software testing process at the forefront of the software delivery cycle. Here we are discussing a few trends:
Popularity of DevOps: DevOps has become one of the most used solutions for software development. According to a survey by Statista, Only nine percent of the respondents had not adopted or had no plans to embrace DevOps for software development. In a DevOps development process, both the development teams and QA teams work in tandem for the software development, pushing the significance of testing and monitoring to another height.
Automation Tools: The software testing process has a large number of repetitive and mundane tasks, and the manual process of testing was proving to be a waste of resources for organizations. Automation tools can automate the repetitive task in real-time with more efficiency. These tools have become vital for the continuous testing and delivery required by agile teams. Automation tools allow testers to create more test cases instead of executing them.
Internet of Things (IoT): IoT devices are growing at a rapid pace. These devices depend on software to function efficiently. The ubiquity of IoT devices require the communication protocols and operating systems testers to test all the possible combinations for efficient functioning of the IoT network.
Big Data Testing: The biggest issue with big data analytics is verifying that the data has been successfully processed. The verification process is not time-efficient, and can hours depending on the quantity of data. There is a massive demand by Big data analytics companies for test platforms that can replicate the behavior of individual data layers in the operating system.
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