Artificial Intelligence has brought in a lot of changes in testing, positively! AI in functional testing, particularly, is playing a crucial role in bringing any app or software more rapidly than before to its users by decreasing the testing time considerably while improving the testing quality. Automated testing has been aiding QA for quite some time. When combining the innovation in testing with the benefits of AI technology, the outcome would be superior QA in any software product. Let’s look at the benefits of AI technology in QA, especially AI in functional testing.
Advantages of Artificial Intelligence in Functional Testing
Software applications should be able to run on a wide variety of devices, platforms, and browsers for them to have a wider acceptance and reach. QA teams generally use cross-browser and cross-platform testing tools into which AI and machine learning has been incorporated. This intelligent innovation in testing helps create a variety of test scripts, improve test analysis, and also reduce maintenance. Some of the major advantages of AI in functional testing are as follows:
1. Accuracy
AI in software testing can help discover new ways to deliver the best user experience by allowing testers to move from traditional manual testing to continuous, automated testing methodologies that are precise, vast, and effective thereby making the testing process more accurate and with more speed. The tedious and monotonous jobs which are prone to errors can be shifted to automated tests where the AI can be used to capture, record, and analyze accurate data with improved efficiency and accuracy.
2. Less time & money
Every time the source code is changed, manual testing involves going through the same repetitive process of testing the whole software. This incurs considerable time and money particularly when the project is huge. One of the benefits of AI technology in testing is that it can considerably reduce the time and money during such events as an AI-based testing procedure can perform these steps without any additional cost and in less period.
3. Enhanced Regression Testing
To test the overall stability and functionality of all the features after certain code changes, updates, or improvements are made to the software, regression testing is used, which is quite a humongous task especially when there is a progressive and rapid deployment. AI in software testing can perform this regression testing with ease and accuracy. AI in functional testing such as user interface change can scan for any overlaps and validate the alterations which are difficult in manual testing.
4. Enhanced Visual AI Testing
Visual AI testing can help visual validation of web pages and can test different contents on the user interface. As today’s software has grown more complex, applications have more content to evaluate and continuously for faster releases, and using a traditional, linear method of testing would not be feasible. Visual AI testing can help take the screenshots, measure the load time, validate the whole page, and update the Document Object Model and framework building.
5. Enhanced Bug Tracing
Bugs that escape unnoticed during manual testing can be caught using AI due to the innovation in testing. One of the benefits of AI technology in testing is that it can trace any flaws and bugs spontaneously. AI in software testing can be particularly useful when the software and data are growing huge day by day and can help identify bugs quickly and automatically so that these can be attended to without wasting time.
6. Enhanced Prognosis
With AI-based automated testing, the existing customer data can be used to examine the change in user demands and browsing behaviors which in turn helps businesses to be one step ahead in identifying users’ demands and fulfilling them. This enhanced prognosis with AI-based testing will help achieve better service and improved predictions on growing user needs.Various tested modules pertaining to the new Software are integrated into a single unit and is released in a test environment called UAT, User Acceptance Testing. Based on the feedback received, improvements were made and fine-tuned. The product is thus implemented and is now available for the end-users.
7. Enhanced Test Cases
The traditional testing methods don’t allow additional possibilities for test cases. AI will help create new approaches to test cases and this will enhance the quality of the test cases that are quick to operate and control.
How does AI helps in Testing?
We have seen the advantages of using AI for testing. But how exactly does AI help in testing? Artificial Intelligence, to a large extent, can mimic human behavior and intelligence. By extracting patterns quickly and accurately one can learn from the data. To perform continuous and tedious tasks without getting tired. AI in software testing can detect more intricate patterns of the data and the relation between them than humans. It can arrive at a decision more accurately than their human counterparts.
As AI-powered tests take less time, decisions can be arrived at in a short period. This saves both time, money, and the final product will be a superior and efficient one! AI can create machine learning algorithms using large data which predict various outcomes. This can be further used to arrive at a decision. In simple terms, AI in testing helps to do a robust job in a short period. It also envisages certain complications that may arise that a human may not identify.
Why Testing is automated using AI?
Testing is automated using AI for two basic reasons. One is to stop unnecessary tests and the other is to save more time. When you automate a test using AI, it is easy for you to analyze the overall performance of the system without repeating certain test processes that are not required. This, together with the speed at which the automated AI tests are done saves a lot of time. By using AI in test automation, you can achieve accurate results and superior test results.
