Future of Automated Testing: 4 Trends to Watch

Future of Automated Testing: 4 Trends to Watch

Even though many companies have shown interest in switching to automation testing, most enterprises still need to employ it. Lack of testing companies spends a lot of time fixing the issues as soon as they are brought to their attention by customers. Businesses of today need to comprehend the need for test automation. 

Organizations realize that they have to invest in testing to deliver quality results, then their top concern is that they will be able to deliver the product as per the timelines. They tend to analyze the costs involved in setting up and running test automation to see if there will be any long-term return on investment.

Organizations today, more than ever, need to include new features frequently before their competitors continuously. As a result, they cannot risk the chance of investing a lot of time in going through each testing process when there is a release.

As a result, in the future, companies will be one of many who must deploy a test automation solution per their requirements; the test automation tools will also need to be created with a return on investment in mind.

The following are two test automation-related issues that will undoubtedly require attention in the future:

  • Maximizing the amount of test coverage that automation is capable of achieving.
  • The testing automation process should be streamlined and simpler to save time and effort.

QA’s history:

It is generally acknowledged that the emergence of testing as an autonomous process began around the beginning of the 1980s. Then the Waterfall model was in development which is now out-of-date, and nobody uses it. As a result, the quality assurance procedures are connected to the current approach, and its efficacy was effectively equal to zero. The most severe mistakes become apparent in the last stages of development. You can easily imagine your difficulties when making changes to an almost-finished product.

First Experiments:

After 1990, the quality assurance sector started utilizing specialized technology, making testing more challenging. Their capabilities were limited, and they rarely matched up with the assigned tasks. The decade encourages experimentation with new software development and quality assurance methods, such as RAD, Scrum, or XP.

Flexibility in the development of information technology:

The “Agile” development methodology initially appeared at the start of the 2000s and has remained popular. This was when IT professionals were experimenting with different methods and setting up new guidelines for developing new IT products. We can conclude now that their efforts were fruitful. After 2010, when IT started to rule the online world, another step was taken. Since then, many online apps have employed cloud services as their backbone, and automated testing has started to emphasize new platforms. The Selenium tool is one example of innovation. They have gained new functionalities and become more powerful every day.

Automation Testing and its Future

It is easy to imagine what automation testing will be like in 2023. Quality assurance received a powerful jolt at the start of the second decade that forced it to change course. In addition to automatic scripts, industry-recognized manual testing is also offered. They move forward simultaneously with the development process, manual, and regression testing. It decreases the time required for performing quality checks. 

Most of the bugs can be accurately tracked by quality assurance teams using sprints, and they can quickly send reports to programmers to fix the errors. It is quite advantageous for the development process and has received positive results. Projects are finished on time as a direct result of this.

Quality assurance experts are experimenting with new testing approaches, like characterizing instances using dictionaries. Codeless testing will cut entrance barriers, and businesses will gain from the inflow of fresh talent. Without a QA background and creative thinking, any individual is never limited to conventional logic, so they can try to implement new ideas for testing software interfaces and functionalities. 

People are urged to use new procedures because the process has been made more efficient. Natural language processing (NLP) is another development in the quality assurance sector that will last far into the next ten years and beyond. It is believed to be the technology testing automation in the future.

ML and AI in Quality Assurance

Information technology professionals have been concerned about the potential use of AI in their work for a long time. Now and then, attempts are made that don’t work out. The attempts, to be more precise, have proven successful, but they are unrelated to artificial intelligence. Artificial intelligence must execute algorithms, grow and learn independently, and develop IT products. 

AI will make test automation processes more straightforward and effective. Machine learning (ML) and artificial intelligence (AI) will be crucial in the future of automation testing, along with non-linear testing (NLT) and no-code development.

Selenium 4 will be the heart of Automation Testing.

In October 2021, Selenium’s fourth major version, which had been much anticipated, was eventually released. Since Selenium 3 had been made available to the public for five years, technological advancements were significant. The functionality of Selenium 4 has undergone several improvements, including better command formatting to access the Selenium Grid, robust Docker support, the ability to recognize the parent frame, and more.

One of the new features added to Selenium 4 is support for relative locators, enhanced tab and window management for web browsers, a built-in Chromedriver for the Microsoft Edge browser, and many other advancements. Since its debut, Selenium has received much positive feedback and acceptance as an improved version. This is one of the test automation-related improvements we should be looking for in 2023.

Top Trends to Watch for Automated Testing

Here are the best trends to watch for automated testing, have a look:

1. Codeless Automation Testing is predicted to grow again:

Codeless automation testing solutions are created using AI technology. The visual modeling speeds up the creation of test cases specifically suited for automation testing. With the help of these tools, testers can develop test scenarios without having any programming experience, which will cut down on time spent on tiresome test cases.

Below we have listed some of the benefits of codeless testing:

  • Not technically savvy users can study the test cases quickly because they are generated without using any code.
  • Even folks unfamiliar with computer languages or coding can build and construct test cases.
  • Developing test cases and automating them is accelerated since the learning curve tends to be shorter.

The greater use of non-coding solutions is one of the test automation trends that will take off in 2023. The year will see an increasing demand for test automation platforms like LambdaTest. It’s the best time for you to become one of the essential parts of these trends. In case you have been using the platforms such as LambdaTest, then you can opt to perform seamless manual and automated testing for your mobile and web application across devices, real browsers, and other OS combinations.

2. Self-healing Test Automation 

Machine Learning (ML) and Artificial Intelligence (AI) are frequently used to solve specific problems and boost the effectiveness of the testing and development processes. AI is used in testing to shorten the test life cycle in all aspects of testing, such as regression testing, automation testing, functional testing, performance testing, and so on.

To achieve the aim of automation testing, AI must become a key part of software testing tools. Massive amounts of data are generated during each testing cycle, which can be used to identify and correct any test failures. The data and insights learned from each test iteration can be fed into the AI and ML algorithms.

This data will be used to train the algorithm, and the learning it experiences will help the testing tool determine the “expected behavior” for the different tests. Since the device can flag a test as “failed” if there is even the slightest deviation from the predicted behavior.

Such situations typically occur in automated browser testing when Selenium scripts are created to interact with a specific element (on a web page) identified by XPath or ElementID. But the test’s failure can be due to that element not being present on the page. To continue automatic browser testing, the tool employs AI-based learning to locate an “alternative” element on the page that may be used in place of the common element. The creation of test tools is increasingly utilizing AI and ML; as a result, the tools may now self-heal as they are being used. Self-healing testing will be included as one of the test automation industry’s most important trends in 2023.

3. Exploratory Testing

Because of technological advancements, one of our objectives is to automate the testing procedure. However, there will always be a demand for effective, non-automated testing. The following advantages come with choosing exploratory testing, which has the potential to fundamentally change the testing landscape in the future if teams effectively implement it:

  • Project owners can receive insights by incorporating testing methods that are impossible to achieve through other types of testing.
  • Working under tight timelines enables testing teams to find UI faults rapidly and accomplish more.
  • It involves less preparation time and offers a quick method for finding faults at any point in the software development life cycle.
  • It enables testers to identify edge cases and apply them in future testing.

However, it would help if you didn’t rely only on exploratory testing while testing your software product. Until you combine exploratory testing with other forms of testing, you won’t get the most out of your testing efforts or notice changes in the quality of the outcomes.

4. In-Sprint Testing

With in-sprint automation, the Business Analysts, Product managers, Development Teams, Quality Assurance Teams, Project managers, and other team members are jointly responsible for ensuring that the program fulfills quality standards. Combining all the essential testing tasks is intended to reduce the complete testing procedure into a single sprint. Additionally, it aids in achieving many advantages, some of which are as follows:

  • Completing code tests and the execution of tests simultaneously enable the detection and correction of problems at a much earlier stage in the software development life cycle.
  • It offers better test coverage, quicker release cycles, and shorter test cycles than its rivals.
  • It improves and elevates the team’s capacity for cooperation.

Automation aims to eliminate the need for manual testing, but machines cannot work independently. We need a human’s help to operate a device. Although the enormous progress automation testing has made in recent years, manual testers are still greatly needed. An experienced manual tester can write test cases so that they require fewer automation scripts while still providing comprehensive coverage.

Even today, manual intervention is still necessary to configure the AI processes, even if ML and AI strive toward codeless automation. Additionally, there are still some testing disciplines where automation falls short of a manual tester’s keen observation and intuition, such as user acceptability testing or user experience testing. Only a company with a well-thought-out strategy to use both manual and automation, where both are required, will effectively create a product of the best quality.


The future of automated testing looks promising, with several emerging trends set to transform the testing landscape. The increasing adoption of AI and machine learning, the rise of test automation-as-a-service, the shift towards open-source tools, and the focus on continuous testing are some key trends expected to shape the future of automated testing. As organizations embrace these trends, they will be able to achieve faster and more accurate testing, reduced costs, and improved overall quality.

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