Switching software testing to automated algorithms has been a major trend for testers for quite a while. This level of optimization can reach an incredible height with the introduction of Artificial Intelligence. AI performs repetitive mundane work, provides reports on code quality and helps organize the process. Artificial Intelligence can also help teams to learn and cooperate, with plenty of business applications – the possibilities are limitless. Let’s take a look at how AI can transform software testing, and how companies can adopt this technology to their QA teams.

What’s the role of AI in software testing?

AI in Quality Assurance doesn’t work by itself. It can’t substitute manual work or be an all-in-one solution to previously available testing tools. Right now, the main application of AI in software testing is to improve automated testing tools. Existing automation software for QA specialists helps automate repetitive test cases, get statistics on their work, detect bugs, tech debt, and dependencies, and even make decisions. However, it has many limitations. Automated tools require a long configuration: testers and architects need to improve the tool’s functionality, show needed scenarios manually, and control its performance.

Artificial Intelligence can embrace the responsibility of configuring automated tools, overseeing their performance, and assuring correct results. It will also create detailed reports that provide a big outlook on the team’s transition from manual testing – similarly to how a person would analyse the process. So, AI can improve the speed, transparency, and time-efficiency of automated testing.

Let’s take a pointwise look at how AI can optimize the efficiency of automated testing:

Automating Test Case Writing

Artificial Intelligence can improve the quality of your test cases for automated testing. Instead of running a large test suite just to detect a minor bug, AI will offer precise test cases that are fast to run and easy to control.

When developers write test cases, they often have no time to analyse additional possibilities for test cases. Instead of going for the most efficient option that will generate the least redundant data, they prepare a case that they already know how to write. For AI, analysing project data takes a couple of seconds, which is why it’s so good at finding new approaches to test cases.

AI allows running the minimal number of tests to figure out if the code change had a positive or negative impact. No redundant data, bottlenecks, or manual involvement.

Automating API Test Generation

API evaluation allows measuring the quality of interactions between different programs that communicate with databases, servers, and use various protocols, etc. Testing assures that the connection is stable, requests are processed correctly, and an end-user will be able to get a correct output after a particular interaction.

API testing automation allows users to come up with multiple test cases for API QA and evaluate the functionality of multiple third-party tools. Some services use hundreds of APIs, in which case, automation is a must.

Artificial Intelligence analyses the functionality of connected applications, detects potentially risky areas, and helps to create test cases. Designed to quickly analyse large data volumes, it can quickly assess if API is performing correctly, and come up with precise test cases.

Self-healing the Execution of Selenium Tests

Selenium has been one of the best-automated testing frameworks. Selenium tests, however, aren’t perfect – they are too complex, take a long time to execute, and even a small technical issue can lead to the loss of all test case progress. It’s not a flexible solution: if a requirement for automated testing wasn’t made correctly, the test case wouldn’t be complete.

Artificial Intelligence identifies such broken tests and repairs them. If the execution was stopped due to a technical issue, AI will identify it and find a solution. AI heals Selenium tests automatically and provides smart insights on improving the cases. Let’s find out more details below:

AI heuristics define the cause of Selenium’s test failure. Once the reason is defined, the test is healed during its execution without stopping.

Smart Recommendations

If a feature often displays an issue, the software will evaluate its behaviour and offer a smart solution, derived from collected system data.

Visual Validation Automation Testing

Visual validation testing is a part of Quality Assurance where tests evaluate if the UI is displayed properly to an end-user. The goal of the test is not to make sure that the solution delivers the expected performance, but check that each UI element appears in a correct position, size, shape, and colour.

Automating visual testing is difficult because there are countless scenarios of possible bugs. Testers need to imagine users’ mind-set and view the UI with their eyes. It’s challenging even for a human tester, much less for an automated program. This is why switching visual testing to automated solutions is connected to reductant details and specifications – testers aim to set the condition precisely, but end up with a cluttered file – which is practically impossible to execute.

AI analyses the environment in which the application runs – hardware requirements, operating systems, browsers, and determines which UI standards are applicable. Unlike regular automated visual validation tests, AI-based scenarios adapt to users’ needs.

Predictive Analysis

Artificial Intelligence can use existing customer and analytics data to determine how users’ needs and browsing habits will evolve. This allows testers and developers to be ahead of growing users’ standards and offer better service quality. With Machine Learning, AI platform will get better with each use case of analysed user behaviour and provide increasingly more precise predictions.

Conclusion

Artificial Intelligence offers assistance in automating more sensitive testing areas, such as UI testing and visual validation. AppleTech provides quality assurance and artificial intelligence based development services to assist you in leveraging these technologies to the utmost of its capabilities for your dream project. Contact us today.

We're Here To Help!

11 + 13 =

Office

A-FF/02 Mayfair Corporate Park
Vadodara, Gujarat
India

Call Us

India: (+91)-972-572-1717
USA: (+1)-203-987-2021