Top 5 Ways AI can enhance UI testing
As a part of scaled test automation, artificial intelligence is changing how we conduct quality assurance for software.
Not only does AI in software testing speed up the whole QA process by automating repetitive tasks, but it also applies reasoning and problem solving to understand emerging patterns. It uses this knowledge to render better quality software with the least number of errors.
In addition, it aids in better test coverage when compared to manual efforts. Currently, AI is a huge part of functional and non-functional testing. However, the question is:
Where does AI stand when it comes to User Interface (UI) testing?
UI testing is the validation of UI elements such as input controls, navigational components, and other informational components for ensuring that they work as expected and deliver the required functionality. UI testing powered by AI is a similar process to manual testing, which identifies UI elements and examines whether they are placed appropriately.
Before digging deeper into UI testing, let us first understand,
What is a User Interface (UI)?
The user interface of a software/website is its point of communication between a human and the computer. This communication usually takes place through interactive devices such as a screen, desktops, consoles, and other I/O devices.
UI is also a part of HTML webpages and applications.
These user interfaces help you control the computer/device that you are using. The characteristics of a well-designed UI include:
a. Intuitiveness
b. Efficiency
c. User-friendliness
A comprehensive UI test will determine how an application handles user inputs and displays all the visual elements correctly.
Applications of Artificial intelligence in UI testing:
UI testing is mainly focused on testing these aspects of an application:
- Visual Design
- Functionality
- Usability
- Performance
- Compliance
When it comes to the use of AI in UI testing, the possibilities are endless.
To start with, these are the latest trends in AI-driven software testing with regard to the user interface.
1. Designs converted to code in real-time
AI-powered applications are now qualified to convert a wireframe into actual code as the design is being created. This helps developers get started early on and highlight possible errors to QA teams in the prototype stage. Thus, speeding up the SDLC and making it easier for UI testers to spot design flaws near the beginning.
2. Intelligent object recognition
The elements in the graphical user interface of an application can be tested and healed automatically. AI-enabled visual recognition tools pick a faulty UI automatically and fix it at that very moment. It takes away the pain of manual testers having to look at test logs and review such simple errors, thereby freeing their time for other essential reviews.
3. Smart recommendation system
Have you ever wondered why Netflix recommends certain titles based on your watch history and Amazon recommends items based on your previous purchase and search?
Enter Machine learning algorithms.
Based on the heaps of available user data, these neural network algorithms use accurate data processing to establish an emerging pattern of likes, dislikes, and favorites. AI is a powerful tool to gauge and measure user preferences. They smartly alter the UI in small yet noticeable ways to help users get to what they want quickly and easily.
4. Human emulators
Chatbots and AI assistants are built into many applications to understand what a user wants explicitly.
These pre-programmed bots help emulate a human customer service representative/sales agent and intelligently recommend the best possible solution for a user’s pain point. Chatbots have become an intrinsic part of the user interface of websites and applications over the years.
While one use of Chatbots can be to provide quick assistance, in the long run, chatbots help in understanding user needs and can be used for R&D purposes.
5. Fixing common flaws like resizing and color adjustments
UI testing sometimes uncovers small yet significant design and visual issues. Smart AI applications spot and fix these errors automatically. It can include anything from a simple tidying-up to maintain coherence, to more complex color scheming, typography, and sticky frame issues.
What are the elements in UI that artificial intelligence can check?
Data type errors — Ensure that users can only enter valid data.
Field widths — Ensure that the data entered does not exceed the specified character limit.
Navigational elements — Ensure that all navigational buttons work correctly and redirect users to the right page or screen.
Progress bars — A progress bar is used to show the user that a process is still running.
Type-ahead — When using drop-down lists, ensure that you include type-ahead in your user interface. To elaborate, in a drop-down menu with many items, typing the first letter should skip the list to items beginning with the first alphabet of your item.
Table scrolling — In case of a large amount of data, especially in tables, the scroll function should allow users to scroll the data but keep all headers intact.
Menu items — Ensure that the application only displays the valid menu items.
Working shortcuts — Some applications use shortcuts; verify whether these shortcuts work correctly on all browsers, platforms, and devices.
Confirm action buttons — Ensure that action buttons such as submit, apply, delete, save, etc., work correctly.
How does this ease the job of the manual tester?
A manual tester is limited by his imagination and creativity to design tactful and comprehensive test cases.
However, an AI-powered tool, such as Qualidex from Qualitest, can design, scan, input, and validate the values of hundreds of test data to identify the resultant failures and discrepancies.
Advantages of having AI in UI testing
Having AI in software testing frees manual testers to allocate their time and efforts to other tasks that require their specialized skills.
Reducing repetitive manual tasks.
Manual testers have a lot on their plate with UI testing adding to their existing workload. AI-driven UI testing can help in taking some load off their shoulders.
Understanding patterns for dynamic UI changes.
Artificial intelligence can make smart recommendations to UI testers based on its learnings derived from the user-processed data. It understands what humans like when it comes to design and what they expect from the UI of an application.
Ensuring standardization, meeting requirements, and compliances.
In apps that need to comply with specific regulations and standards, their UI must also be precise. AI helps solidify a clean, simple, and accurate UI that purely accelerates business.
Key takeaways -
UI testing is a crucial aspect of the exhaustive application and website testing.
With the user interface being such an essential element of a company’s branding, it is imperative that its UI on all platforms is glitch-free. Therefore, the need for AI in testing UI. However, UI testing needs a mix of experienced testers with an eye for creative details.
In such a case, crowd testing is the best option, especially when you need to test your application’s UI out in the real world. You can also hire a team of quality assurance specialists to test your application’s UI and determine the right AI solution for your usability testing.
To put it simply, AI-powered test automation can scale UI testing, leading to faster deployment and better test coverage. This, in turn, will help brands in improving their customer satisfaction and retention levels. After all, it’s the visible UI that allows them to judge an application’s reliability and usability.
