The Future of Selenium Automation Testing with the Rise of AI

Years back, developers rely on manual testing to confirm that their code is bug-free and ready for deployment. While manual testing got the job done, there were significant limitations. For instance, software developers had to test the product from scratch when there was a new update.

This is an inefficient way of product management, especially in an agile environment where continuity is the bedrock. Automation testing came to the rescue about 20 years ago, making the software testing process quicker and more accurate.

Since the widespread adoption of automation testing, the use of Selenium as a tool has spread like wildfire due to some reasons that will be discussed momentarily. But yet again, AI is another revolution looking to sweep every facet of the human domain, without spearing automation testing of course.

Developers are fast looking into ways AI can make automation testing even more efficient. Right now, many of the innovations are not in full-fledge implementation, but one cannot discount the fact that AI may be coming to topple things slightly – and it came faster than we thought. 

Suffice to say, however, that Selenium is still regarded as one of the best tools for automation testing in recent years and is poised to remain so. The question is you may be asking is, what makes Selenium so special for automation testing?

Why is Selenium so Popular for Automation Testing?

Selenium has some exciting perks that make it stand out in the automation testing world. Here are some of the reasons Selenium’s popularity is no fluke. 

  • Selenium is free to use: Selenium is an open-source project and is entirely free to use. It also does not have packages or plans that will be unlocked at some cost. So whether big or small project, side-project, or a project packed with thousands of functionality, you can use Selenium without hassles and at no cost. 
  • Cross-browser support: A major challenge with some automation testing tools is that it does not support many browsers. But this is not the case for Selenium. Selenium allows you to test the functionality of your app on popular browsers such as Chrome, Firefox, Edge, Safari, etc. Thus, you can rest assured that your application will not break irrespective of the browser a user uses. 
  • Support multiple programming languages: You can write Selenium automation test scripts using popular programming languages such as Java, Perl, Python, PHP, Ruby, etc. As a user, you can select the API you want to use to write your test scripts based on the programming language of your choice. This lack of constraint, in particular, makes Selenium a tool of choice by all and sundry. 
  • Multiple platform support: Another reason Selenium is popular is that it supports different operating systems. You do not have to worry about how to test your application for several OS separately. Selenium allows you to perform test cases across other operating systems, such as Mac, Windows, Linux, etc. Making it super convenient for automation testers

These are some of the reasons Selenium testers are highly craved for. In addition, the learning curve of Selenium is not so steep. Hence, prospective learners can jump on a Selenium certification course and become confident automation testers in a matter of months. 

AI as a game-changer?

AI as a game changer

Without a doubt, Selenium does the job when it comes to automation testing. However, AI has started tweaking some of the approaches to Selenium automation testing. It comes as an additional tool to make automation testing even more seamless. Let’s explore two ways AI comes into play in automation testing.

  • Reduced time for test maintenance: One of the added capabilities of AI in automation testing is lower test maintenance. Let’s take some time to understand what test maintenance is. 

When improving on an existing application, there may be situations where the update is incompatible with some part of the old code. Thus breaking it. For example, imagine if the UI designer changes the location of a button that the test clicks. Upon testing the code again, the test will fail even though the functionality is still present, only the location changed. To fix this type of issue, the tester has to tweak his test scripts slightly to accommodate the button’s new location.

Test maintenance is the process of rewriting test scripts or updating test cases. AI is currently being used for test maintenance reduction. It updates the test scripts based on the new changes without any human intervention.  

This would lead to a faster test time, lower cost of performing tests, and a more efficient system. 

  • Automating the process of writing test cases: AI can help the automation tester identify inconsistencies in his code and suggest ways to rectify them. The GPT-3 model is one NLP model that is capable of performing these tasks. Google mentioned that the model could even write codes on its own.

While this may sound unreal, it does not necessarily take the jobs away from automation testers. There would still be a need to write test cases for new scripts. AI comes as a helper; it protects the control path of source codes, identifies parameters that should be used during tests, detects code inconsistencies, and so on. Things that the automation tester may find burdensome.

These new developments are more reasons you need to find a renowned Selenium certification training to stay up to speed with new tools in the automation testing space.  

What does this mean to Selenium Automation Testers?

Even with the advent of AI, Selenium testers are still going to be as relevant as before. AI will only help make automation testing easier by identifying possible bugs, reducing the time for test maintenance, protecting source files control paths, and so on. In summary, selenium testers will still very much be in demand even with AI in the picture. 

Samuel Jim
Samuel Jim

Samuel Jim Nnamdi is the CTO of Foxstate, a platform that powers digital infrastructures for Real estate financing globally. He has over 8 years of Software Engineering and CyberSecurity expertise.

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