Over the years, Selenium technology has managed to capture the attention of the entire software and web testing industry. Thanks to its open-source platform and extensive support on automation testing that has created solid benchmarks for quality.

The automation that started with Selenium has now taken a new turn with the introduction of AI and Machine Learning. The idea of incorporating these futuristic technologies into the testing process has not only simplified things but has laid the foundation for digital transformations.

Though it may look like a random statement, the entire software testing industry is making speculations on the expected change that AI technology might bring into the business. Even if Selenium test automation has shown extensive performance capabilities for all these recent years, the possibility for change through AI technologies is something that cannot be overlooked.

What Makes Selenium So Special?

In spite of being an open-source testing tool, Selenium has managed to be the most preferred automation testing tool for software testing services providers. The only reason that made people switch from the licensed tools to Selenium was a ready-to-use portable framework that supported automation on application tests. The key features of the Selenium that made the tool more highlighted include:

Flexibility: Selenium is a tool that is widely used for its flexibility when need to perform functionality tests or rapid regression testing. Language Support: Selenium allows users to test codes written in C++, Java, Python, and Ruby, offering extensive language support. Compatibility: Selenium enables its users to check for compatibility across different browsers with effective test case implementation.

Selenium & The Future of Software Testing

Over the years, software testing has gone through an evolution of technologies. Either websites, applications, or software technologies, the use of test tools that have automated the process has helped the testers to take down many testing challenges.

Moreover, the use of tools like selenium has allowed improving the approach towards manual testing, consuming no time on repetitive test cases.

Since the open-source innovation, DevOps, and agile methodologies have been the major contributory factors for the changed approach towards testing, selenium has built its reputation as an automation tool by sticking to these factors.

Especially, when the first-ever selenium survey showed 59.5 percent of respondents to use selenium for browser management and 61 percent of users stick to the selenium framework, it becomes even more important to keep a check.

The ease of continuous development and delivery has helped the testing communities experience cost-effectiveness, rapidity, compatibility, and many other benefits. As long as it is concerned to Selenium being the widely adopted and most-preferred automation testing tool, we have a few reasons that could justify the statement:

Free To Use: Selenium is an open-source testing tool that makes it a free-to-use platform for testing requirements. It does not include any recurring fees making the entire task of development hassle-free and cost-effective. Whether you are a large organization or a small development company, selenium has the potential to carry all kinds of quality analyses. Extended Support: Another good reason why testers prefer using Selenium for all their test automation requirements is the support for different operating systems and browsers. This makes it convenient to measure the performance of the software across different platforms such as Android, iOS, Mac, Linux, Windows, or other operating systems. Apart from this, Selenium supports all your test practices made on popular browser extensions like Chrome, Firefox, opera, safari, and others. Programming Languages: Selenium allows testers to write scripts in multiple languages as per their choice. Either Java, C#, PHP, Ruby, Python, Perl, and more. Moreover, selenium even makes users select the API based on the programming language. Selenium IDE: when you need to record, edit, or debug any test cases, selenium IDE comes in handy with powerful tools to perform such actions.

Nevertheless, even after gaining so much popularity, the automated testing on Selenium is likely to create an impact on the future of testing leading the world towards bigger things sticking to the words of Steve Jobs, “Be a yardstick of quality. Some people aren’t used to an environment where excellence is expected.”

The AI Intervention

At present, AI technology has just started to make its space into the world of automation testing. However, there is still nothing like pure or 100 percent automation limiting the use of AI technology to SDLC.

Nevertheless, there are still many ways in which AI technology is being used by automation platforms. Most of these are oriented to offer added capabilities to testers improving the tasks with repetition. Besides this, test maintenance is another important aspect of AI-based automation that is likely to create an impact on the testing industry.

Test Maintenance Reduction

When running automated tests, one thing that creates maximum impact on the test process is test maintenance. Since test maintenance could create a hindrance to the entire test initiative, AI technology is being widely used to address the issue. For instance, AI and ML technologies are frequently put together to overcome application changes without human intervention.

Besides this, ML for test maintenance could aid testers by removing the need for manual efforts to detect the changes and work on test flow. In short, AI could lead to a more resilient testing environment saving time, money, and other resources spent on the process.

Above all, AI, with its limited reach to super-intelligence, is never a threat to manual testing operations but rather an approach to simplify the testing process for added productivity.

Shortcomings of Selenium Testing

Even though selenium is a popular tool that offers a highly stable environment for automation testing, there are still many shortcomings of using the platform that is making way for technologies like AI and ML to overtake. Some of these include:

The hassle of creating test cases sometimes makes it difficult for testers to achieve their goals on time. Secondly, using selenium testing involves a difficult test environment setup in comparison to vendor tools. It offers limited support for image testing with no test tool integration for test management. Selenium only supports web-based applications and that too without reporting facility. And of course, there is no reliable technical support and only community assistance is available to get over any features that are not working.

AI in Testing

AI technology has redefined the entire testing process with its ability to take over any repetitive and monotonous tasks. This could help to add value to time and simplify development tasks like writing, execution, and code-testing. Also, the process could help streamline routine development functions having human input.

Applications of AI: The Future of Software Testing

AI technology in the near future would be seen prominently used across all testing scenarios for the identification of test errors and early resolution. Some of the more advanced capabilities of AI in the testing operations include:

Automation of Test Case Writing
AI enables software testing service providers to avoid any inconsistencies with the test process. AI can help users in: Detecting code that is not covered within current suites To protect the source code’s control path Define parameters that should be addressed under test This ultimately leads to better unit test results and improved overall development API Test Generation Automation
Another significant challenge that developers have to face is related to APIs that demand repetitive actions. However, AI technologies could help users in: Identify traffic patterns Create data model of given parameters Generate efficiency through needle tests Visual Validation
At present, selenium has become a highly valuable tool for addressing the visual validation process. There are certain claims which state visual validation cannot be worked without the use of selenium. However, there are certain limitations of using selenium technology related to maintenance, and AI has the potential to improve the healing process and overcome any maintainability issues. Self-Healing
Selenium is the most commonly used tool for UI testing, but still, the performance it draws is full of limitations. With self-healing techniques that come through AI, developers could experience a higher standard of stability and maintainability. Moreover, the technology could even learn from manual interventions for delivering more sophisticated end solutions.

Key Testing Trends Associated With AI

Since AI solutions in testing are developed around problem scenarios, AI technology could assist in testing scripts that have maintenance issues. We are repetitively focusing on creating and maintaining automation test cases using AI because these are the most common challenges involved in testing.

Most of the time, test cases are likely to fail with the application feature upgrades. But AI technology could assist in updating test element’s IDs that are not updated with automated scripts. All in all, with every change made to the UI or the app features, the test process can be revised by the AI tool to self-correct the path.

Non-Selenium Tools

Selenium for years has been used to automate tests through the browsers making it the top choice of commercial vendors. However, there is another truth that says automation is not just limited to selenium, and therefore it would be necessary to have access to the right tools at the right time when needed to improve the development process.

Though this doesn’t mean replacing selenium with AI-based automation testing, the testing teams are more likely to opt for different tools based on test preferences and needs.

With the likeliness of this trend to grow, the non-selenium tool developers will have to understand that selenium is a free-to-use tool and thus have more commercial space to cater to than paid solutions. Moreover, companies that need to grow benefit from AI-based non-selenium tools to will have to offer something extra to overrule selenium.

Self-Healing Tools

Running a test needs a quick compilation of large volumes of data. It might include HTML information, screenshots of the execution stage, images, and browser errors.

Such data can be fed into the AI tool’s algorithms and can be used and revised every time an application is put on the test. Also, this can even aid in the identification of any deviations from the likely behavior and help take corrective actions to streamline things.

For instance, when a test is under execution and is found missing any expected field element, the system could use some other replaceable element to test the product to avoid test breakage. At present, certain AI-based tools can identify change elements or broken ends to make the code heal, adding maximum value to the tests.

Time-Saving Testing Through AI

Testing can be a consuming process, especially when the testers have to deal with frequent failures. Using an AI-based test approach could help you practice innovation. Moreover, it can even be used to check on log files and locate any chances of failure to create a perfect end solution.

The modern-day AI tools can eliminate the hassle of consuming tests and scale the entire process by rapid testing of server logs and as well as other potential issues associated with the system.

In a nutshell, these AI-based solutions have the capacity to perform hard work and help lead the decision that is right and valuable.

Record & Playback Features

With growing popularity for record and playback features, it is likely to return to the era of Selenium IDE. However, this also creates space for AI tools that are made to simplify the entire task of recording and playback functions, enhancing the overall reliability of the system. Since it can help aid in the runtime capabilities of the system, the upcoming updates of Selenium IDE are likely to introduce machine-learning integrations in the system.

Testing in Continuity

Last but not least, with rigorous app development models, one thing that is likely to increase is the leaning of software developers towards continuous testing. The term “continuous testing” is already gaining popularity across forums, and its ability to do a quick evaluation of new products or changes can therefore change the industry.

It can even help the users to look for unexpected behavior and reduce the cost of overall development. Since continuous testing is a process that flows along with the project at all stages of SDLC, it can help meet the quality goals through early, quick, and timely automation testing.

The Crux

Concluding it all, if there is some area where Selenium testing has frequently been found failing, it is when any changes are made to the system. Even when these changes are simple as renaming an element, selenium-based solutions often fail to recognize such changes leading to failed test results.

On the other hand, AI-based automation testing has the potential to recognize any changes made to the elements, or maybe the field could be interpreted to avoid collapse. This can help in making tests more reliable and easier to maintain.

Nevertheless, any kind of technology used in testing has some significant scope of improvement. And therefore, crafting them for perfection would need optimal accuracy through AI and frequent human intervention.

Though the present situation signals a brighter future for AI, if selenium tools could manage to accommodate the correction for existing flaws, the future of testing can be the best. Moreover, the present case needs both AI and selenium automation to work together to deliver the most productive test results. Rest, only time has the ability to show what the future landscape of testing is going to be? But whatever it will be, it is going to be more promising for the testing community across the world.