2023 is already halfway over, which is a great time to look at the test automation trends of the year!
Can you believe that we’re already halfway through 2023? That’s right, folks, it’s June already! Technology evolves more and more rapidly with each year that passes. For example, one of the most popular advances in mainstream technology in 2022 was the release of ChatGPT by OpenAI. This sophisticated AI content generator and chatbot is only one instance of the incredible technology that was developed last year. As the world progresses further into 2023 and technology moves faster, it is vital to stay up-to-date on the top testing trends. GMI predicted that the test automation market will grow to 80 billion USD by 2032, making this a hot industry to follow. From the latest buzzwords to processes that have had a slow burn, these are the top test automation trends we’re seeing in 2023.
The driving principle behind QAOps is maintaining software quality with a DevOps mindset. DevOps’ goal is to streamline the Software Development Lifecycle (SDLC) through the implementation of a Continuous Integration/ Continuous Deployment (CI/CD) cycle, so QAOps aims to add testing into the CI/CD with Continuous Testing. Through closer collaboration between Quality Assurance and DevOps, automated testing can shift further left and be implemented at any point in the development of the application.
This also increases transparency between the two teams, as DevOps gets a better understanding of testing efforts and QA gains a deeper knowledge of the product. This collaboration can result in a higher quality product, as earlier testing reduces the number of bugs that make it into production. When DevOps and QA eliminate silos by working closely together, each release can also go to market faster, shortening the delivery cycle.
This type of testing is something that has been done for a long time, but as there are more and more online stores and services, it has become even more critical. In the UK, the percentage of retail sales carried out online jumped from approximately 20% to nearly 35% in the first Covid-19 lockdown in 2020 and climbed even higher during the second lockdown of 2021. Online shopping did decrease once lockdowns were lifted, but averages are still above where they were pre-pandemic.
Still, there are instances where websites cannot handle large amounts of sign-on or activity. A recent example is the January crash of D&D Beyond’s account management system when many subscribers were canceling their subscriptions. Load testing ensures that an application can handle a large number of users and activity at once, which is especially important for online retailers around Black Friday or the holiday season.
Real user data is complex and can be difficult to reproduce manually, especially in large quantities. And, of course, you shouldn't use real data, because that would be a security risk and breach of confidentiality. Synthetic data is a great option for training Machine Learning algorithms (like Virtuoso!). The most robust synthetic data is generated by Artificial Intelligence, ensuring that the data is as accurate and real-world as possible so algorithms trained with it don't form bad habits.
This may seem a little silly since software testing is all done on computers, but "digital" goes deeper than just the use of technology. During the age of Digital Transformation (in which the goal is to adapt technology to your current processes to streamline your work), testing teams can improve their quality and testing efficiency by adopting testing tools. Whether they're switching from manual testing to a tool or trading up to a more efficient automation tool, staying abreast of current testing tech is essential to not getting left behind.
As the SDLC moves faster and faster and the push for a short time-to-market grows, the testing process must not become a bottleneck or an optional step in the software industry's development process. According to the American Society of Quality, ideally, a business should be devoting 10-15% of their operating costs to Quality Assurance. If quality is neglected, this number can get up to 40%. QA will not only ensure that you're saving on costs, but also that you're turning out high-quality products.
Shift-left testing has been around for a while, but it's gaining a lot of traction recently. Shift-left testing encompasses various practices and techniques, such as Test-Driven Development (TDD), Behavior-Driven Development (BDD), and Continuous Integration (CI). These practices encourage a proactive mindset, where testing is not seen as a separate phase but as an ongoing activity integrated into the development process. By focusing on prevention rather than detection, shift-left testing helps identify issues early, enabling developers to address them promptly and iteratively.
Implementing a shift-left approach testing requires a cultural shift within organizations. It involves breaking down silos between developers and testers, fostering collaboration and knowledge-sharing, and embracing a mindset of quality ownership across the entire team. This approach promotes a holistic view of quality that meshes well with agile methodologies and encourages teams to take responsibility for delivering reliable, bug-free and high-quality software.
If you're looking for a test automation tool that can keep up-to-date with the current trends in software testing, then look no further than Virtuoso! Between shift-left testing, a partnership with Mostly.ai for synthetic data, and natural integration with the development cycle and Continuous Testing, Virtuoso is the ultimate low-code no-code test automation tool. Easy to use for tech and non-technical users alike, Virtuoso uses Natural Language Programming to make your testing more streamlined and powerful. Try out our two-week free trial for yourself to see how it works!
