Test Automation: Paving the Way for IT Modernization

What is test automation?

Before exploring the future of test automation, it‘s essential to first understand what test automation entails and the benefits it brings to the table.

According to the ISTQB Glossary “Test automation is the use of software to perform or support test activities”.

How can test automation be beneficial?

Test automation aims to simplify test execution and analysis, saving time and costs while ensuring consistent results. It expands code coverage, allowing for thorough examination of functionalities, especially in early development stages, leading to better software quality. Unlike manual testing, which consumes significant time and resources, test automation provides quick results and immediate feedback, enabling developers and testers to promptly act on the findings. By automating repetitive tasks, resources are freed up, allowing testers to focus on exploratory testing, enhancing their ability to find defects. Although initially requiring an investment in training and tool setup, test automation ultimately reduces costs, particularly for regression tests, as automated tests are much faster than manual ones. This results in improved software quality and lower maintenance costs.

How to choose the right test automation tool?

Before diving into the opportunities and challenges that meet any organization shifting to test automation, let’s discuss first how to choose the right test automation tool.

There are many open-source software test automation frameworks, such as Selenium, Appium, Watir, Mocha, Cucumber and Galen Framework.

New testing tools are being developed all the time, and it can get complicated to choose a suitable tool, especially with the new tools emerging every day. There is no one-size tool that fits all. There are important questions that need to be asked before using or purchasing a new tool.

• What will the tool be used for?
• Does it solve a current problem you have?
• Will it improve your work?
• Is your team already trained to use this tool or training will be needed?
• What is the ROI for using this tool?

Every team is different and you need to understand your team’s needs and skills before utilizing any tool. Take your time and implement a pilot project before purchasing any tool and also don’t forget that you can take advantage of open-source tools.

Challenges and opportunities

Challenges

The selection process for a test automation tool can be a difficult task for organizations. Selecting the suitable tool depends on project requirements, scalability needs, team’s skills, and existing projects and integration of the test automation tool with other tools. Maintaining the test automation framework with diverse platforms and configurations is another challenge that requires a lot of attention to details. Furthermore, training and adapting teams to new automation technologies are necessary. There is also the burden of script maintenance, with the continuous updates and new features added to the software all the time. New challenges might be added constantly, especially if organizations are changing to Agile and DevOps practices.

Opportunities

Even though there are many challenges, there are even more opportunities for organizations embracing test automation modernization. New automation frameworks and libraries provide better support to specific testing needs, offering solutions for CI/CD pipeline integration and parallel test executions. Today artificial intelligence and machine learning technologies, cloud-based testing platforms and shift-left testing practices are creating a new era for test automation, with AI-driven testing and test case generation, finding bugs earlier and helping with predicting them, improving communication and increasing test coverage. All those opportunities are leading to faster feedback and improved overall software quality. With good understanding of the current market and tools, organizations can overcome challenges and unlock the full potential of test automation.

Emerging trends and innovations

Some trends and innovations were already mentioned in the previous paragraph but I would like to dive deeper into these aspects and explain in more detail those new technologies and strategies.

There are many emerging trends that are aiming at changing and reshaping the testing practices for the better. Firstly, artificial intelligence is of course one of the leading trends at the moment along with machine learning technologies. Integrating those technologies into test automation frameworks offers better and faster test case generation which leads to faster testing process, prediction of issues which helps in saving costs, and more advanced and detailed reports. Secondly, shift-left testing practices are becoming more popular. Shift-left testing is an approach to software testing in which testing is performed earlier in the software development lifecycle, thereby offering faster feedback loops and improved software quality. Thirdly, microservices testing strategy is a method that involves breaking down an application into smaller, independent services and testing each one separately. This approach focuses on testing the APIs and communication between these microservices to ensure they integrate properly. Fourthly, DevOps practices promise continuous development, testing, integration, delivery, deployment and monitoring which leads to better and faster product delivery and also a more stable operating environment.

By following these trends, staying updated, and adapting to change, organizations can open new opportunities for effectiveness, agility and quality assurance in their test automation techniques.   

Test Automation: Past, Present and Future

Before taking a peek into the future of test automation, it is important to understand its past and how much test automation has already developed. Software testing began as a completely manual process, performed entirely by people without the use of external tools. This approach, known as manual testing, is still in use today. While manual testing was sufficient for simpler software, the increasing complexity of software required more advanced testing methods. This led to the introduction of using computers to automate tests. Software testers began writing test scripts, providing instructions for computers to execute. This automation proved to be effective in finding bugs and saving time. Since then test automation started to really take shape. Record and playback tools started to emerge, then as software became more complex, software testers started automating functional and regression tests to save time. The process needed to be faster so separating test data from test scripts became necessary and data-driven and keyword-driven testing appeared, making the process of test creation much faster. As test automation needed to be more scalable and easier to manage, the need for test automation frameworks to help organize and structure tests in a better way came up. As the software development cycle has accelerated with the adoption of agile methodologies and DevOps, test automation has also had to evolve to keep pace with development. Adapting to the current landscape, which includes CI/CD, agile practices, and complex applications, necessitates both shift-left and shift-right testing. This approach integrates testing earlier in the development process and extends it into the post-deployment phase to ensure software behaves correctly in real-world scenarios. Given this rapid progress, artificial intelligence and machine learning are poised to play a leading role in the future, ensuring that software testing continues to match the speed and complexity of development.

Conclusion

In the ever-evolving landscape of software testing, the journey towards test automation modernization is not a destination but a continuous evolution and determination of organizations striving to stay ahead. As challenges, opportunities and innovations of test automation were discussed in the article, we can clearly see that the future of test automation is packed with potential. It is a future where artificial intelligence improves the software test process, cloud-based testing platforms enhance communication and shift-left testing becomes the norm and not the exception.

As we close this chapter, remember that test automation is here to stay and that the future holds more surprises and that this is just the beginning of a long, ever-evolving journey of modernization.