Staying up to date with the future of testing is essential, considering how quickly new trends emerge. Now let’s examine the following test automation trends:

 

1. QA Transformation powered by AI

Artificial Intelligence has evolved from a tool to a fundamental component of Automated Testing. Automation powered by AI is simplifying and improving the accuracy and efficiency of testing procedures. This represents a dramatic departure from the idea of standard automated testing. Teams as a whole will be able to automate the testing process, enabling effective test asset management, thanks to artificial intelligence and related machine learning capabilities. Test-driven development (TDD) automated test planning will be powered by analytical-based algorithms with built-in traceability, guaranteeing maximum coverage and minimal maintenance and upkeep. 

Additionally, it can assist in scanning each line of code to identify areas that could benefit from reworking, improved adherence to coding standards, and expedited handling of security flaws.

 

2. Testing with Explainable AI

In addition to the top test automation trends mentioned above, Explainable AI will be important in utilizing AI solutions that offer clear and intelligible test findings, boosting automated testing procedures’ dependability and trustworthiness. Businesses will have to prioritize explainable AI models by 2024; this will contribute to increased decision-making processes’ transparency and trustworthiness. Meeting client needs for more comprehensible AI-driven results and complying with changing regulatory norms are the main reasons for adopting this change. 

As a result, there will be a rise in knowledge in areas like explainable AI frameworks and tools like TensorFlow, SHAP, and LIME, which will eventually lead to the widespread use of AI.

 

3. The emergence of self-healing instruments

Testing teams will be able to proactively identify and address issues before they arise with the use of self-healing tools. The more tests that these machine learning-based technologies do, the more adept they grow at developing and managing reliable tests because they learn from experience.

 

4. Automating without codes

Powered by codeless automation systems, a significant trend is the democratization of quality assurance. By allowing experts of all stripes to participate in test automation, these creative solutions are bringing new ideas to the table and enhancing the quality of the final product in a way that is more reliable and focused on the needs of the user.

 

Statista reports that “the global low-code platform market is forecast to amount to approximately 65 billion U.S. dollars by 2027.”

 

Without writing a single line of code, testers may construct automated tests with codeless testing, and teams of any ability level can use sophisticated test scripts.

It can expedite test creation while optimizing testing reliability, stability, and efficiency throughout the SDLC (Software Development Life Cycle), relieving testers of the difficult and time-consuming task of writing complex test suites and freeing up testers and developers to concentrate on new product development.

 

5. Innovative integrations

Testers may always have a consistent and updated perspective of the quality lifecycle thanks to state-of-the-art integrations that work with the testing ecosystems that are already in place. Such linkages offer flexibility and enable testers to access the tools at any time, enabling teams to work fluidly with full access to all necessary test infrastructure even as testers continue to work using a hybrid work paradigm. This will feature controlled resources, access-anywhere tools, centralized repositories, and reporting portals.

 

6. Enhanced Data Management for Tests

TDM is changing due to the emergence of advanced data analytics and synthetic data-generating methods. This trend satisfies the increasing demand for compliant, diversified, and high-quality test data—all of which are essential for efficient and realistic quality assurance.

 

7. AI Ethics and Bias Testing

QA will be tasked with testing for ethical implications and biases more and more as AI becomes a mainstream feature of software, particularly in AI-driven decision-making systems.

8. A focus on privacy and security

 QA will be essential in making sure that apps are not only functional but also safe and adhere to privacy laws as cyber dangers and data privacy issues develop.

9. Turn to the Left

The increasing importance of shift-left testing is one of the major themes in Selenium automation testing for 2024. This entails running automated tests early in the software delivery lifecycle, rather than only during pre-production, against code modifications. Shift left makes it possible to identify errors more quickly and early thanks to the integration of the CI/CD workflow. 

 

10. Getting Used to Quantum Information

As quantum computing develops in 2024, quality assurance (QA) may encounter new difficulties in making sure that applications are secure and resistant to quantum errors. This new trend in QA denotes a distinct market that requires certain expertise. Using this technology, quantum computing seeks to improve AI capabilities for high-frequency trading, fraud detection, and risk management.

 

In summary

In 2023, test automation trends saw a significant and continuous expansion of AI/ML in a number of business and technological domains; AI-powered products, such as ChatGPT, are now more widely available. Because of its accessibility and the significant investments made in AI by prominent figures in the industry, firms from a variety of sectors now share a common understanding of the revolutionary potential of AI/ML. Although these trends offer a solid foundation for adapting to the continuous evolution of testing technologies, it is crucial to have a plan and understand how to carry it out. In 2024, if the long-term growth and success of your business are top priorities for testing, speak with our team about using test Automation testing with selenium right away.