Regression testing software can help you make the manual regression testing process automated. It can save a lot of time and effort. But what is regression testing software? What should you look for when you are deciding on the regression testing tool of your choice?...
Times have changed. Technology has advanced rapidly, making systems more complex than ever before. More agile processes and methodologies have come up too, like DevOps, continuous testing, continuous integration and delivery, and mob programming and testing. These approaches have changed the dynamics of how teams work to build and deliver products. Even the tools used for development and testing have become smarter, faster and more complicated.
Testers have to coexist amid all these changes. As this trend continues, how is the role of testers going to change? What skill sets will help them stay relevant in the industry?
Here are three ways testers can adapt their role and skillsets to rapidly changing technology and processes.
Gain more technical knowledge
Until now, there was no need for testers to be technical. Non-technical testers were still able to add value through their critical thinking skills and experience testing multiple applications.
But with systems becoming more complex, testing underneath the hood has become more of a necessity. In addition to testing the UI, other parts of the systems, such as APIs, databases and microservices, also have to be tested. This requires more technical knowledge.
With companies moving toward more automation and focusing on cross-functional teams, it helps testers to have basic programming skills so they can read and write code. This gives the ability to build automation frameworks, write automation scripts, read application code and contribute more to the overall project.
Adapt testing approaches based on technology
Historically, testers have written detailed test plans based on requirements and executed them during the testing phase. They were aware of the expected outcome and tested the application to see if the actual results matched the expectations.
But what if we do not know what the expected outcome could be? What if we have to change our testing approach after interacting with these systems?
New technologies such as AI, blockchain and cryptocurrency have made the job of testing more interesting. There are a lot of interactions and decisions happening in real-time that make it nearly impossible to predict the kind of outcomes generated for different inputs.
For example, AI-based systems are generally a black box. We do not control or understand how the AI model forms different relationships or makes decisions. We provide different training data sets and monitor the system’s learning and progress. We are trying to make predictions on future values based on learning from past examples or trying to discover different patterns from data sets.
A premade test plan is not going to be helpful in this scenario, as the outcomes and decisions of AI-based systems are unclear. The approach to test these systems has to be adapted to focus more on providing diversified data sets and evaluating the decisions made by the AI model against specific evaluation metrics to determine performance.
To get the best results with cutting-edge technologies and architectures, our approach to testing needs to change.
Focus on becoming information brokers
With technologies forcing testers to change their approach, and new methodologies like DevOps and continuous testing emphasizing more collaboration between different teams, there will be more focus on testers becoming information brokers.
Testers will have to collaborate with developers, business representatives, stakeholders and infrastructure teams and act as the glue that holds everything together. Instead of focusing on testing the application through exploratory, scripted and automated testing, they will spend more time giving information about the system to those other teams, while people in different roles actually do most of the testing.
For example, developers will start writing more unit tests and own the effort of writing automation code. At the same time, testers will help the developers by providing the required information to build features. Testers will begin serving as domain experts who help out various other roles.
As the world continues to evolve, testers have to keep an open mind. Their role is crucial and will continue to help teams, but it will be in vastly different ways than what we have seen in the past.
There are many things you can expect when it comes to automated GUI testing such as increased reliability and cost savings.
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