Software testing began to pace in recent years since companies emphasized launching quality products by adopting the latest technologies. Organizations need to become aware of certain branches of QA that are predicted to flourish in the future, so there'll be room for improvement.
- AI in software testing: According to Gartner's prediction, seventy-five per cent of organizations will operationalize AI by the end of 2024. Organizations will increasingly use artificial intelligence to automate testing in the coming years as we move away from manual testing to machine-driven testing. Incorporating artificial intelligence into the testing process could result in more intelligent testing because using AI tools results in automatically generated scripts. These test scripts will be based on the inputs and results of similar previous projects. Therefore, testing AI solutions may improve software technology's reasoning and problem-solving capability by speeding up time-consuming manual procedures. The time invested in early device testing helps teams develop more resilient test cases to overcome flaky tests and detect trends in random test failures. AI can only be beneficial if fed with enough data sets, which requires the proper quality assurance and testing practices.
- Selenium 4: Many testing scenarios can be automated using Selenium 4. It is a popular open-source framework for writing JavaScript tests for web apps, mobile apps, and desktop applications. Selenium 4 is also easy to learn, so it's no wonder that developers are becoming increasingly interested in it. As much as selenium benefits developers, it has a lot to contribute to the testing field for test automation. Selenium 4 lets you perform test cases on different browsers and operating systems and helps with cross-browser testing.
- Big Data: Businesses and technology experts have realized the importance of data. They have leveraged it over the years to improve customer service and meet business goals in healthcare, manufacturing, telecommunications, and many other industries. Data completeness and productive transformations based on the correct exchange of data are the core objectives of big data. However, yielding the advantage of big data for businesses requires testing, ensuring diverse datasets are used to generate profit. Testing can bring Quality Assured solutions across industries for big data into the light by incorporating the proper testing approach considering the market data and consumer information. Functional testing is performed to learn more about the framework and components of the application by validating the data on the results generated by the application's front end. Next, performance testing helps to evaluate the application for the variety and storage efficiency of the data sets. Data migration testing can be helpful when an application moves to new technology or server, confirming that no data is lost and downtime occurs. These are the use of big data testing techniques.
- Shift left Trend: Shift left testing highlights the importance of testing early during the development phase. A project can decrease the number of bugs and improve code quality through frequent and early testing. The objective is to avoid discovering any significant defects that call for code patching during deployment. 85% of the code faults are introduced during the coding phase. Stabilizing the product will take a lot of time and money if a business thinks testing should wait until after the development phase. Additionally, the cost of uncovering a bug differs depending on the stage of the software development cycle. The cost is five to ten times higher when a bug is discovered during system testing and higher when a product is released. The shift-left trend has caused significant changes in the software testing sector. This trend will still be relevant in 2023 since firms need to acquire qualified personnel with expertise in the development process to remain competitive.
- IoT: It is predicted that the global population of IoT devices will reach 125 billion by 2025. Several consumer brands are offering IoT capabilities to innovate their business models today, leading to the proliferation of IoT technology coupled with robust 5G networks. Testing IoT software is essential, especially when most consumer brands offer IoT capabilities to innovate their business models. Early detection of any vulnerabilities in the system may provide quick software and IoT device correction. Performance monitoring of every device is necessary to identify any areas of failure in the networked system. Performance testing, security testing, compatibility testing, functionality & usability testing are the use cases of testing for IoT devices.?
With the advent of the latest technology, testing will eventually grow and become an essential part of what these technologies offer organizations. Companies can keep up with trends by maintaining awareness of the same and implementing the right testing strategies with a professional team like QAonCloud. We can always keep up with future updates to provide high-quality products.
