Software testing is one of the most important and strongest pillars that is holding the massive modern tech world. Preflight and many other popular no-code test automation tools have always been pushing their limits to reach new heights in terms of ease in software testing.
And, we must say the revolutionary technology that has picked up and continues to pick up some steam in the no-code automated software testing tools, is Artificial Intelligence or AI Testing.
It is helping the world explore new dimensions in extremely efficient test creation, maintenance, and achieving shockingly impressive results.
It is certainly doing an amazing part in redefining the set of truly useful and efficient software testing tools.
However, Preflight always thinks a lot ahead of others. We focus on building an automated software testing platform that enables every member of the product team to work together irrespective of their coding knowledge.
The users just need to set up the tests once by following a few basic steps and then those tests can be run repeatedly along with the features like analyzing the tests with their auto-recorded versions.
But, as the users do not need to use complex coding concepts, Preflight must use efficient technologies to provide ease in operation and our team does that remarkably well.
Preflight uses game-changing AI Testing technologies to justify the tag of describing it as a user-centric efficient software testing tool.
Our users experience immense ease in using our tools because of the massive AI Testing functionalities like -
We are going to talk about how each no-code tool tries to solve this problem and why Preflight excels.
We got a nice idea about what importance AI carries in the domain of efficient software testing.
Now, it's time to check out the revolutionary AI technologies that are pushing Preflight over the heights.
DOM might be known as something more concerned with the fundamentals of a UI but, it has much greater importance.
It focuses on the HTML structure of an application and contains crucial information like HTML, body, head, H1, etc. Its objective is to provide a good structure to the product as well as to its content.
However, any HTML code cannot be called the DOM. Only when the HTML code is associated with other important parts like JavaScript, CSS, etc., and is given a proper structure, then it can be treated as DOM. Hence, to be called the DOM, the HTML code must get loaded in the browser and show the designed elements when it is parsed.
The DOM can be manipulated using various kinds of selectors or locators.
The regular selectors perform mostly depending on the elements' properties such as name, ID, tag name, etc. For example, one common and widely used locator used in JavaScript is querySelector which lets the user find an element by its unique ID or any other unique property.
Also, the users can find an element by using attribute-based locators like link text, partial link text, and class name. But, these attribute-based locators work only when the users know part of the text of a link within an anchor tag.
Other than these, there are some more complex locators such as XPath and CSS selectors which are used for many crucial DOM manipulation operations.
Preflight is one of the most renowned names among modern software testing tools. And, our efficient DOM testing methods play a crucial role in achieving remarkable results.
We always ensure updating the DOM testing methodologies in our tools to provide an amazing testing experience to our users. Also, many other popular tools like Mabl, Testim, Functionize, Reflect, Rainforest are focusing on using this awesome method to achieve better performance.
However, Preflight uses so many advanced AI functionalities in our overall operations that eventually our DOM testing level easily surpasses all other players out there. Let's dive in to find out more.
Every web product is designed and developed by following a design flow. A web page is divided into some major components that are further divided into smaller elements. This way, the design becomes more dynamic and easily accessible at any point.
For example, when we know which “div” tag contains the buttons, headings, or links, it becomes much easier to make any changes for improving the quality and performance of the entire application.
Then if the user needs to work on a small independent element, locating it becomes easier by using locators that target its placeholder's attributes. So, this is the hierarchical structure that helps in developing and even testing any web product.
Now, when AI functionalities focus on executing the test operations according to the hierarchy, the detection of bugs or faulty elements becomes even easier.
Though widely used software testing tools like Mabl, Testim, etc. use the hierarchical pattern in the tests, Preflight's well-strategized test methods make us stand out in the market.
Besides improving our AI capabilities to identify the hierarchy of elements on a webpage, Preflight follows the most popular and effective hierarchy of test suites and test cases in our tests.
A test suite consists of multiple small test cases that primarily focus on one small objective each and aim to achieve a greater goal collaboratively.
For example, one small case is developed for each of the small steps like entering the username, entering the password, matching the password with previously set data, clicking the “Login” button, etc. And, all these test cases together build the greater test suite of testing a complete “Login” page.
Preflight emphasizes maintaining the most effective test flow among the test cases so that the test hierarchy solves a greater purpose within little time and uses very less resources.
Hence, PreFlight secures a significantly high position among software testing tools that use the test hierarchy pattern in their operations.
Previously, we noticed that regular selectors are not always enough to identify every element on a webpage. That's where the world feels the need for dynamic locators that use multiple attributes associated with any element to identify it with a more holistic approach.
These locators identify an element with its unique attributes such as customized classes, ID, names, texts, etc. Hence, the chances of locating a specific element become higher due to the use of dynamic locators.
However, using dynamic locators is not always full-proof. In most cases, due to any feature update in the application, the attributes of the elements get modified and as a result, the locators become unable to identify them.
That's why even after developing custom smart locators, Testim cannot always identify the elements after any change in the application.
On the other hand, Preflight uses more advanced AI methodologies like context awareness, self-healing scripts, OCR, etc. to efficiently identify every smaller than the smallest bit of the web page and execute planned test operations on them.
Let's explore more about these highly effective AI methodologies.
It's time to explore what makes Preflight hold a special place among the most popular no-code test automation tools. As we already saw, other tools mostly focus on improving the conventional testing methods by the use of AI.
But, Preflight works with the objective of understanding the product and how a user will interact with it.
Every web product is built with a specific objective and depends on a number of factors to achieve its best performance.
For example, nowadays, smartphones have multiple sensors installed in them and each one of those sensors provides some formats of data that is used by web products.
So, the point is that if any tool is going to test the applications, it must know the complete context behind it. And, that's where Preflight does its magic.
Our tools do not bother about the complete code that is meaninglessly time-consuming to test. Preflight observes and analyzes an application from users' point of view, and understands why it is developed.
Then it becomes easier for the test automation tool to look at every component while knowing what it actually does. Another specialty of Preflight is that our tool digs up the cause behind any operation or any test failure from its root and sets up an example of a next-level Root Cause Analysis.
So, this next-level use of artificial intelligence is called context awareness and Preflight is proudly executing smooth software testing operations by exclusively using this blessing of AI.
Also, our users can stay relaxed during any change in the application. Preflight always looks for the change first and adapts to it rather than stopping or breaking the running tests.
Hence, we proudly say that our test scripts that are working in the backend are absolutely self-healing.
Our users can set up the test once and whatever further changes are made to the application, our tool will adapt to them by itself.
Moving on to more of the visual analysis part in testing. If any tool needs to test a web product from users' point of view, the testing tool must identify the elements from their visual aspects.
That's where computer vision comes in. It is the technology by which a computer looks at and identifies elements by their visual properties. Computers look at an image and analyze which bits of it are related to each other and proceed through image segmentation.
That means computers identify several still and moving images by breaking down their visual properties and understanding them as a whole.
This is indeed a great method to identify elements on a web product and test them from the users' point of view. Renowned software testing tools like Rainforest, Testim, etc. use this amazing AI-based tool in their operations.
But, it is not always enough to understand complex designs. That's why Preflight prefers OCR or Optical Character Recognition which enables the AI to read the page with all its relevant properties.
So, Preflight always stays on top of the other popular players due to the use of the most advanced AI technologies.
Let's take a look at how Preflight excels in the game by using OCR.
As we previously mentioned, Preflight always thinks ahead of everyone. Though computer vision is amazing, we are digging up more with a greater goal. Optical character recognition is the technology that reads a webpage by the characters or even images on it.
In this process, AI dynamically parses the characters and the graphics on the screen. It helps Preflight understand the motive and planning behind the elements present on the page.
With the conventional working style of AI, the system takes little time to identify the elements on the page that is being tested. But, as PreFlight uses an amazing context awareness, it takes no time to identify and understand the objects.
Our automation testing tool automatically records and saves the tests and constantly takes screenshots of the important steps. Then, based on our efficient context awareness, it parses the screenshots and understands all the elements present in them.
This way, our super fast object identification leads to an unbelievably smooth software testing experience.
Where all other renowned test automation testing tools are struggling to lower the time consumed in understanding the context of a page, Preflight is proud of the remarkably fast context awareness that makes it dominate out there.
Our game-changing packages are waiting to let you experience such amazing AI-based software testing.
AI or Artificial Intelligence is one of the best blessings of technology. It has become our best friend in several of our daily tasks.
For example, we enjoy the immense ease that Google Assistant provides us, we enjoy so many tasks getting completed through voice commands, the world is experiencing a massive increase in productivity because of self-driven vehicles, etc. In short, today, AI is everywhere.
Now, we are going to see what benefits it provides in software functional testing.
Improvement In Visual Identification of Bugs: In conventional performance testing processes, QA engineers develop codes that look for bugs and drawbacks in web products.
But, those codes may overlook or become unable to detect some visual bugs that are crucial from the users' perspective.
On the other hand, AI has numerous long code scripts and test cases set up and working in the back-end. So, it observes every minor to the major aspect of the application.
AI uses its pattern recognition and image recognition capabilities to perform visual testing on the elements.
It looks at the application from the users' perspective, analyzes the UI components at a pixel level, and ensures that they are functioning properly.
Helps In Achieving Better Accuracy: Manual testing means there are always chances of human-prone errors like overlooking some parts, focusing on different parts during repetitive tests, etc.
Using AI demolishes the need for repetitive tests as it minutely checks every smaller than the smallest part in every test run.
And, with Preflight, every test is auto-recorded and saved. Hence, the users are free to check it whenever and as many times they want and analyze everything they need to test.
Also, with AI technologies, Flaky tests do not bother the testing team that much. In manual tests or with conventional test automation technologies, mostly QA engineers find random failures in the tests due to bugs or poorly written test scripts.
But, AI deeply analyzes the reason behind those test failures and helps a lot in overcoming them. So, it's time to get rid of Flaky tests with the best of artificial intelligence.
Better Test Coverage and Efficiency: As we can easily see that complex and time-consuming test steps like checking the file contents, data tables, memories, internal program states become so seamless with AI that users can achieve a much better test coverage within little time and with significantly fewer resources.
Hence, from this observation of much better test coverage, we can conclude that using AI in software automated testing tools genuinely improves the overall test efficiency.
Easier Adaptation To Change, Maintenance, and Faster Time-to-market: As we mentioned earlier, often tiny changes in the UI or UX of any application cause lengthy test cases to break all of a sudden.
And, we know how difficult it gets to detect such a tiny change through conventional testing methodologies. On the other hand, AI and ML algorithm-based technologies are developed with the objective of detecting the smaller than the smallest alterations in the codes and even in the UI & the UX. Hence, AI-based software testing tools like Preflight easily adapt to every change.
Also, AI and ML methodologies are capable of handling numerous operations within a much less time span.
So, they enable the users to perform much better maintenance of the complex test scripts.
These amazing benefits of AI are the reasons behind the smoothest performance of Preflight which prioritizes providing the best experience to its users over everything.
We have discussed a lot about how Preflight uses the set of next-level AI technologies in its tools.
But, without experiencing them practically, no one cannot really understand their superpowers.
Our team is always on the toes for truly using AI and developing numerous wonderful features to provide immense ease and smoothness to our users.
Explore the truly reasonable and easily affordable packages that we are offering, and get started with us.
To know more about Preflight and our products, feel free to contact us. Also, do check out our blog page for more amazing information on various topics.