With the emergence of innovative applications and technology, the trends in software testing are also on the ride to continuous progression, and inclusion. Now, testing is not performed after the complete software development life cycle but is implemented along with the development process through CI/CD and regression tests. More companies have started adopting an Agile and DevOps testing methodology to detect errors initially, rather than right before deployment. As mentioned in the beginning, the adoption of digitalization has increased considerably over the last couple of years. Especially with the emergence of the COVID-19 pandemic, more people are depending on software solutions for daily activities. From contactless payments to remote work and education, virtualization has started to play a pivotal role. Therefore, it is imperative that more software solutions and applications are rolled out every day. Also, newer updates and modifications to existing applications must be done without affecting the functionality of the application. For these regression tests and automation, tests are conducted by QA analysts. To ensure smooth automation, manual testers rely on AI and ML-based tools, algorithms, architecture, etc. These innovative technologies have laid the foundation for the growing trends in software testing and more enterprises are adopting these strategies.
Not only do these trends streamline the experience of everyone with low code testing modules and auto generated test scripts, but it also ensures that the application is 99% reliable and error free. For those enterprises that are quick in realizing these trends, the future holds excellent opportunities to differentiate them from competitors. With an overall aim of revolutionizing the complete testing experience, it also enables businesses to lean into the difficulties bestowed by COVID-19 and helps identify new strategies that they can integrate and build on.
The software development process is ever changing and always growing with the implementation of new languages and technical skills. Therefore, when we look at the trends in testing from the perspective of quality assurance, the need to optimize the procedure and make it more easily understandable by non testers as well becomes much more relevant. Employees who are working on the software development process must also be capable of testing the codes to ensure that requirements are precisely met. Also, having a streamlined quality analysis function removes the bottlenecks that may otherwise prevent on-time code releases into production, therefore, resulting in an improved satisfaction ratio among the software development, DevOps and QA teams. By staying updated and implementing the latest testing trends can also benefit from the release of higher quality codes with much fewer defects. Developers can program Artificial Intelligence (AI) based scripts to identify errors and solve them with very little human intervention. Adapting to these growing trends can deliver faster software solutions, with little to no errors, hence significantly increasing user experience and customer satisfaction. It not only increases business ROI but can enhance business reputation through the deployment of high quality software solutions.
Now, let us look at the emerging trends that will enhance software testing and QA in the coming year and beyond.
Over the past few years, Test automation services have received critical and worldwide acclaim due to their many benefits in testing. Automated testing was considered a progression over manual testing and was adopted by several product manufacturers globally. has been one of the top software testing trends for the past few years. But with the increase in the adoption ratio, another severe challenge that organizations faced was the unavailability of expert test automation resources or service providers. This significantly affected the adoption of test automation until the arrival of Scriptless test automation. Scriptless test automation enabled businesses to solve this difficulty and still have efficient test cases for automating software testing. This was mainly because scriptless was a flexible test automation framework that considerably decreased the number of manual interventions needed in creating and maintaining test cases. Manual testers could plainly designate the actions rather than writing pages of the actual testing code. Which decreased the time taken to generate test scripts and significantly enhanced the complete testing scenario.
Sometimes the manual testers will have difficulty in identifying the failure results from previous tests and creating new tests based on the test history. This can be time consuming as testers must identify previous errors, rectify them and create new test scripts to ensure that these errors are properly resolved. By introducing artificial intelligence and machine learning into these challenges, testers can solve the need for creating test scripts or identifying errors. AI and ML have the capability to quickly identify errors in the previous test results. These technologies can learn from these results by themselves without any human intervention and create new test cases to ensure previous errors are not repeating again. AI and ML can also prioritize the tests based on these results and give more significance to codes that had defects in them earlier. This saves a ton of money and time for manual testers as they will not have to follow the steps of traditional testing and build new scripts as the application evolves.
With traditional testing practices, regression testing or CI/CD methods were not applicable. This means that the tester had to wait until the complete software development life cycle was complete in order to test the final product. This method would be significantly time consuming and expensive because the product will have to go back and forth between development and testing. By embracing an Agile and DevOps based approach, businesses were able to tremendously improve the code quality and decrease the testing time. This was mainly because tests were conducted in parallel to the development process. This means each day the software would undergo several tests, the results from these tests were updated into the existing solution, Because errors were proactively identified and solved, developers did not have to work on fixing the entire product before deployment but could solve errors module by module. Such tests proved to be exceptionally advantageous for web development and mobile app developments because such software applications required quick deployment with fewer errors.
There is no doubt that there will be more software testing trends in the upcoming future. The enterprises that adopt these trends are the ones that can overcome competition and stay relevant to customer demands or growing market requirements. Artificial intelligence and machine learning are being widely accepted across all domains throughout businesses and have proven to be beneficial in all industries. Integrating these technologies into testing will also relieve testers and QA teams from performing repetitive time-consuming tasks. Automating the testing process can reduce human intervention, enhance software quality and deliver solutions with faster time to market.