The Future of Test Automation: Trends to Watch and Adopt
In this week's issue, we delve into the latest and upcoming trends in test automation.
Every day, we hear about new technologies and tools in software development and software testing. The IT sector changes rapidly, and we need to learn new technologies continuously to stay up-to-date and increase our work efficiency. I know, sometimes it can be tiring, but our end goal is to create and maintain an efficient workflow, and new technologies and tools are there to help us.
When I started my career over 10 years ago, the testing industry and profession were different than they are now. The variety of test automation tools wasn't that broad, and therefore more manual effort was required in each company. Then, companies started to use more and more automation in their processes. Java became a popular language for writing automated tests.
It's still one of the most popular languages to use, but we can see that JavaScript-based automation frameworks are taking over the market. And now, we can see news about AI and how it is going to change the entire industry, almost every day. In today's issue, let's discuss the future of test automation, what the current trends are, and what we should watch closely.
Artificial Intelligence (AI) in Test Automation
Almost every day, we read news about AI and its impact on the software industry. ChatGPT, for example, has recently become available, and people are going crazy about it. Rather than fearing new technologies, we should seek ways to utilize them to make ourselves more efficient. AI language models, such as ChatGPT, can be valuable partners in software testing. We can use them as co-pilots to review our test cases, automation code, and much more.
Although it's still an early era, we should closely watch the trends and start experimenting to see if these tools can enhance our testing process. Also, you should always keep in mind that you should check your company policies before sharing any data with AI since it can be used to train their models.
As a note, I personally believe that the use of AI in the software industry will increase the demand for software testers, as more applications with questionable quality will emerge. However, this is a topic for another day.
Shift-Left Testing
Shift-left testing is already widely adopted in many companies. In the past, testers worked in separate teams and became more involved in the process once the software was ready. While this approach may still be efficient in some companies, in many cases, it led to discovering problems too late in the process, making them expensive to fix.
With the adoption of agile methodologies, testers began to work as part of a team and started to be involved in the process from the beginning. Testers' feedback at each step helps the team detect problems earlier, which makes them easier to fix and ultimately increases the project's success rate.
Also, with shift-left testing, we can see the trend of using a similar tech stack throughout the project. For example, if a product is written with JavaScript, it does make sense to use JavaScript-based testing frameworks for its test automation. This helps everyone in the team understand the automation code better and become involved when necessary. Automated Testing becomes more of a team effort rather than an individual endeavor, which helps teams deliver software faster.
No code / low code Automation
If you had asked me a couple of years ago, I would have said, "No-code automation is not a good choice; it creates more problems than it solves." However, my view on this has changed recently. As I mentioned earlier, our industry is changing rapidly, and companies are trying to make time-consuming processes faster. Automation is a crucial and often expensive part of the testing process. Coding automated test cases and maintaining them can be time-consuming.
In recent years, I've seen significant investment and innovation in no-code / low-code tools. Almost every day, we can see a new player in the market. I've tried a couple of the tools, and the results are surprisingly good. You can set up a basic automation project within hours and run some test cases. I believe that in the near future, we will see more and more usage of no-code / low-code automation tools.
Test Automation for Mobile Applications
The demand for mobile applications is higher than ever, and as a result, the need for efficient test automation for mobile apps has become crucial. Mobile test automation tools will continue to evolve, focusing on cross-platform compatibility, better integration with CI/CD pipelines, and improved performance testing capabilities. In our next article, we will discuss in detail how we can start testing and automating a new mobile product.
Conclusion
We can observe new trends and technologies every day. As engineers, we should always look for better and more efficient ways to perform our duties. This involves continuous learning and improvement. As individuals, it's impossible for us to learn every tool and technology available for software testing. However, it's important to keep ourselves updated with new technologies and conduct research in this area.
Happy testing! ✌️