AI Powered Test Automation: Advantages and Tools
In this digital era, software development life-cycle has become more and more complex. Most of the IT companies are faced with the challenge of delivering projects with accuracy and high speed, creating a restless and high-pressure environment for the project team.
Clients’ requirements are limiting the sky and there are never enough employees to make all the things perfectly in a given timeline. Continuous testing is really a big headache for the project teams.
Currently, the main aim of IT firms is to run more tests, detect bugs quickly and deliver the project faster. Thus, it is very clear that Artificial Intelligence is the key to streamlining software testing and making it smarter and more efficient.
AI-Powered Test Automation:
Artificial Intelligence means to make businesses much more efficient. Almost all the multi-national companies are using AI technology to enhance client interactions and customer satisfaction.
Algorithmic advances and massive data collection are vastly extending the scope of software testing automation, making it possible for non-technical team members to characterize and scale tests with levels of capability and modernity equivalent to or much more than developers.
The search for alternative and advanced testing methods such as automation and Artificial Intelligence now needs to accelerate and equip Quality Analyst and testing teams with enhanced capabilities. It is a fact that AI shows great potential in detecting test errors quickly without any human intervention.
Such advances have offered the ability to determine how the product works at both data-server level and machine-level. Artificial Intelligence, like automation tools, helps with the whole testing effort.
While CI / CD, DevOps, integration and constant testing are preferred in the present era, AI helps greatly in speed up these procedures and make them increasingly efficient.
Now, let’s have a look at the some amazing benefits of using Artificial Intelligence in testing.
Advantages of AI in Software Testing:
#1. Improved Accuracy–
Humans only make mistakes. True, even a careful software tester will sometimes make mistakes when running a monotonous manual test. Sometimes even highly skilled and experienced software testers make mistakes. This is the main reason why AI-powered testing is becoming popular.
Unlike human beings, AI constantly performs important tasks precisely according to plan, effectively completing the same repetitive tasks, and over time. While AI works on repeated tasks, testing team can do complex tasks that can be completed by humans only and also concentrate on creating more effective automated AI solutions for testing.
#2. Goes Beyond the Limitations of Manual Testing –
Running a controlled web application test with over 1,000 clients is not possible for most Quality Analysts / Software department. With AI software testing, virtual sets of tens, 100s or 1000s of clients that can communicate with a system, product, or web-based apps can be redone.
#3. Helps Both Testers and Developers –
Designers and developers can use shared automated testing to resolve issues quickly before moving on to Quality Assurance. If source code modifications are checked in, software tests will run automatically and notify the developer team if not successful. Such features save developers valuable time and boost their confidence levels.
#4. Increase in Overall Test Coverage –
The overall scope and depth of testing can be improved with AI-powered automated testing, improving the software quality. The AI testing program can investigate memory, states, and data tables and file contents to determine if the software product is performing as expected. All over test automation can make 1000+ unique cases in each trial, offering coverage beyond imagination with manual testing.
#5. Performing Visual Testing-
Image and pattern recognition allows AI technology to detect visual errors by performing visual testing of applications and seeing to it that all visual elements look and work correctly. AI can separate dynamic UI controls despite their size and shape, estimating them at the pixel level.
#6. Saved Money+ Time = Faster time to Market –
Since the software test is constantly repeated, the source code is changed; it’s time-consuming to repeat those tests manually. In contrast, AI automated tests will be run again and again, from low price to zero at high speed with no additional cost. The duration of the software test can also be reduced from days to just hours, which leads to cost reduction.
Now, we are providing some of the best AI-powered test automation tools that help software developers to test and detect errors.
5 Best AI Based Test Automation Tool Ideas
Functionize is a cloud-based tool which is useful for performance, function and load testing purpose. This one-stop solution like tool uses artificial intelligence and machine learning to accelerate test creation, diagnosis and also management.
The best thing is that you no need to think much before taking the test; you just type what you want in English and natural language processing will automatically create the functional test cases. Surprisingly, it executes hundreds of tests in just minutes from all mobile and desktop browsers.
Appvance is one the best utilizes AI technology to create test cases depending on customer behavior. The test portfolio describes what real systems will do on the production systems. Therefore, this tool makes it 100% consumer centric.
AppTools is used for a visual UI testing, visual management and software monitoring. This tool scans application screens and analyzes them just like the humans brain, but with machine intelligence. This tool can be majorly used by experts in the test automation, Devops, manual QA, and digital transformation teams.
Testcraft is one of the best test automation platforms for continuous and regression testing on selenium. It can also be used to monitor website applications. AI plays a crucial role in avoiding management cost and time by automatically defeating changes in the app.
AI is completely transforming the landscape of testing. It is clear that tech giants continue to cross boundaries and innovate with Artificial Intelligence and Machine Learning.
As QA teams embrace automation and welcome AI technology into their software testing methods, the results contribute to new solutions and ways of working, rediscovering where possible.
I hope you satisfied with above provided information about Artificial Intelligence in testing.
Are you looking to build any of these above listed AI Powered Tool ideas then please feel free to contact us.