Everyone wants to build amazing applications that solve people’s problems, and they even build amazing products with highly useful features. But, the common problem that brings difficulties in their success is that codebases can surely have a lot of bugs. And, if those bugs remain unchecked, they will cause the features of your product to crash. To deal with that highly impactful issue, the best way that can be followed is software testing.
Software testing used to be more hectic than software development due to the only fact that it was completely dependent on human testers, and they had to minutely check every bit of the codebase to ensure that every small to big bug is detected. But, as we have mentioned in most of our articles, with the exponential growth in the number of tech products, it has become almost impossible to cope with the huge demand through manual testing.
That’s where test automation came as the revolution in the tech field, and being one of the most renowned market leaders in low-code test automation, Preflight is always working to bring up new benefits in its products. In our dedicated article on the best AI features in test automation, we have put some light on what it is going towards.
Now, we will take a look at the future of test automation in more detail.
As we mentioned, software testing has reached the modern automation stage through multiple levels of evolution, and you must have a brief idea about them to become more aware of what its future will look like.
During the 1980s, waterfall methodology as well as manual testing was trending. Manual testers were highly important and quality assurance was a hectic thing.
Then by the 1990s, test automation put its step in through bulky, expensive automation tools that were still unstable. That was the same time when software development started seeing new approaches like Scrum, RAD (Rapid Application Development), XP, etc. This gave a great boost to the popularity of Agile practices.
2000 gave a fresh start to some new developments that are open-source frameworks. The high priority of faster release cycles leads towards making Scrum, Kanban, etc., the normal methodologies in software development.
2010 came with the demand for more speed in writing and scaling tests. That was the prime reason why cloud testing became a norm.
Now, by 2020-21, test automation and specially codeless test automation overtook every traditional practice with its amazing benefits. Unimaginably advantageous codeless test automation tools like Preflight revolutionized the domain of test automation, and in this article, we will explore what massive changes you can expect in the future.
Since its inception, test automation systems have been serving the world with numerous benefits, which you must have already checked out in depth in our previous articles.
However, here we will take a brief look at them.
Till now, you saw how test automation evolved through decades and which features they are currently offering. Now, let’s take a look at what the possible trends in this field are.
Advanced test automation tools like Preflight are already using efficient AI functionalities like context awareness, computer vision, OCR, etc. to understand a product from the developers’ perspective and how a user will use it so that it gets a better idea about how & what to test.
And, as AI is drastically changing the tech world, you can certainly expect enormous growth in the advanced AI features used in test automation. To know more about them and how the tools make the best out of them, check out the article “Best AI in Automated Software Testing Tools”.
You have already known about the importance of reports and analytics in test automation. The use of AI significantly increases the ease of providing more in-depth reports and analytics for all your tests. Hence, you can expect remarkable growth in the use of AI in that domain, where the prime advantages are provided as -
Validation testing needs no special introduction for the insane level of importance it holds. It is the process that verifies if the application meets the system requirements, performs the tasks as expected, and achieves the goals that it is intended to.
Now, as the foundation of AI’s work is based on huge sets of data and determining if the real values match with the desired values, such intelligence can remarkably improve the level of validation testing. And, that is called “Smart Validation” in the modern world. As the overall development in the field of technology is growing, you can expect “Smart Validation” to reach new heights with the unstoppable advancement of AI.
You already know how important quality is in DevOps. Now, to maintain a stable quality level, teams often have to shift tests towards different ends of the development life cycle.
The most common practices are either shifting the tests to the left to detect the faults earlier, or adding more quality controls to the right. For the “shift-right” method, crucial practices such as canary deployment, and chaos engineering become essential.
Also, from our article on shift-left testing, you must have gotten the idea about how difficult it is to shift large test suites towards the earlier phase of your workflow. Hence, in the future, the efficient approach to achieve perfection through testing will be maintaining a continuous quality culture collaboratively.
For the past few years, you may have definitely noticed the immense growth in the importance of maintaining a continuous integration and continuous delivery pipeline. Maintaining such a continuous delivery pipeline needs the combined working of multiple high-tech tools, and each one of them produces huge chunks of data while that data has been used at minimal levels.
Now, with the remarkable evolution of the tools in the delivery pipelines, the requirement of using that data is growing exponentially. Hence, in near future, the implementation of smart features in DevOps is going to be effectively data-driven.
For large enterprises or any tech business with large test suites, it is always extremely difficult to cope with the long run times of the test suites. They often struggle with getting quick feedback due to their insanely time-consuming test runs, and as a result, their products get to experience a much higher time-to-market.
That’s why large companies like Google and Facebook have already developed efficient machine learning algorithms that can understand changes being made and predict the tests that are most likely to fail so that you can focus on running them carefully.
This practice significantly reduces the time of the test runs. For example, you can see test suites that normally take 5-6 hours to get completed within an hour or even within 30 minutes. And, it can reduce the small test runs to a matter of a few seconds.
Being such an effective practice for test automation, it will surely trend in near future.
Cloud computing is one of the most popular trends in the present tech world. Though you may already know, we have jotted down the most important advantages of this technology.
Cloud computing provides all its benefits in automating your tests also. Hence, you can surely experience much growth in this super-advantageous part of test automation in the future.
In-sprint automation is somehow a super-important aspect of the presently popular agile methodologies. While agile methodologies focus on running all the necessary steps of a development life cycle in small sprints, in-sprint automation stands for testing and automating in the same sprint.
This practice is so advantageous that it is expected to see a lot of growth in the coming years.
Well, it is the modern world’s most crucial practice as well as our favorite topic. Scriptless or codeless test automation is a phenomenal method that removes the barrier of coding knowledge among product teams.
Preflight has always been a great advocate for codeless test automation and we are always developing amazing AI-based features that can effectively understand your product, its mission, and the actual testing needs, so that your entire product team can easily create, run, and manage complex test cases with just a few clicks and drag & drop actions irrespective of their coding knowledge.
You can definitely stay assured that this method will keep getting remarkable improvements.
Natural Language Processing is like the cherry on the cake of scriptless test automation. It allows anyone to write test cases in just natural language. With NLP, any non-tech person can also write test cases in natural language, make some backend configuration, and the tests are ready to be executed.
And, with the immense improvement of AI, NLP is becoming more interactive with humans. This is indeed going to be a massive future trend in test automation.
This article tells you about how software testing evolved from a very basic stage to the super-advanced stage of present times. Also, we have jotted down all the popular test automation trends that are expected to reach unimaginable heights in the near future. So, you just need to thoroughly go through this article and acknowledge yourself with immense levels of highly useful information.
You must already know that to efficiently perform test automation, you must adapt to using highly efficient codeless test automation tools like Preflight. And, it is much more true than you imagine. This simple browser extension is highly effective in fulfilling all your testing needs. And, the best part is that you can get a glimpse of the amazing testing experience for free.
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