Launching software without proper testing is like opening the doors for its failure.
Software testing tends to be an important part of the software development process.
Nowadays, artificial intelligence (AI) is transforming various aspects of software testing, from test case generation and execution to defect prediction and automated bug fixing.
By using machine learning, natural language processing, and advanced analytics, AI tools can find patterns, predict problems, and improve testing processes in amazing ways.
In this blog post, we will look at the top AI-driven software testing tools. Let’s get started!
Top AI-driven Software Testing Tools
1. Testim
Testim was founded in 2016 and it was acquired by Tricentis in 2022. With Testim, you can record user flows and its AI will recognize repeated patterns and offer suggestions. It has a visual editor for easy test creation. Moreover, it focuses on web and mobile projects and includes great reporting and test case management features.
Integrate with your CI/CD process to run tests whenever you check in code, do complete tests for releases to production, or schedule full regression tests.
2. Applitools
Applitools was founded in 2015 and it’s the first-ever company that introduced visualized AI testing. According to their website, it is capable of saving 500 hrs of manual testing every month. It has excellent integration with many test automation tools and its visual AI helps to find design issues on mobile, web or desktop applications. Applitools has a dedicated reporting platform for easy management of test results.
3. askUI
askUI Founded in 2021. With this AI-powered software testing tool, you can automate everything in the testing journey. askUI AI can find any visible element on the device screen and it requires no more selectors. Also, cross-device automation is possible in askUI.
To use askUI, you just need to ask the tool in natural language or just click. Then it will do the necessary processing to create workflow and do the testing on automation.
4. Virtuoso
When using Virtuoso, you just need to use natural language to describe tests. It will take care of the rest of the things. It has AI-powered self-healing features to reduce flakiness in tests. Virtuoso uses artificial intelligence to generate test data and journey summaries and see how AI creates JavaScript extensions from your natural language commands. It has a low-code approach and an easy onboarding process. Besides, you can get a lot of technical integrations and support for scripts.
5. Mabl
Mabl was founded in 2017 and it is one of the best AI-native test automation platforms around the globe. Like most AI testing tools, it is also a low-code test automation solution that offers many useful features such as auto-healing, API testing etc.
It has smart element locators that can be used in different frameworks to build powerful tests. Many brands like Microsoft, Charles Schwab, JetBlue etc. are using Mabl for their testing automation needs.
6. Qyrus
Founded in 2020, Qyrus is an innovative end-to-end testing platform designed to simplify and enhance software testing for web, mobile, and APIs. With its no-code or low-code approach, it’s accessible to testers and developers of all skill levels.
Qyrus uses AI to automatically detect and fix broken tests, significantly reducing manual effort and human error. This speeds up the testing process and ensures more reliable outcomes.
It allows testers to visually map user journeys, helping them understand user traffic and behavior. This feature aids in designing effective test cases and identifying potential usability issues early on.
Qyrus has a strong reporting platform that turns test data into easy-to-understand reports you can act on. It supports third-party integrations, making it simple to add to your current workflows and improve teamwork across different teams.
7. Aqua ALM
Aqua ALM began as a test management platform in 2013 now it amplifies the power of GPT with the context of your project data, requirements, and tests.
Aqua ALM uses natural language processing (NLP) algorithms to convert plain text into tests, simplifying the test creation process and making it more intuitive.
With 40% of AI-generated tests needing no human tweaks, Aqua ALM significantly reduces manual effort and ensures reliable test cases.
It can generate detailed test steps from descriptions, enhancing the quality and consistency of tests.
Benefits of Using AI Software Testing Tools & Techniques
Artificial Intelligence (AI) is changing software testing, bringing many benefits that make testing processes better. Here are some key advantages of using AI in software testing:
Increased Test Coverage
AI tools can look at a lot of data and code, helping them find more test situations and unusual cases that manual testing might miss.
Faster Testing Cycles
AI can make testing faster by automatically creating, running, and analyzing test cases. This helps teams release software more quickly without lowering quality.
Other Benefits
There are numerous advantages of using AI tools for software testing such as cost-effectiveness, continuous improvement, early defect detection, enhanced test reusability and many more.
Wrapping Up…
To sum up, AI tools and methods are changing software testing and making it easy for AI development services providing agencies to do efficient things in less cost and time. They offer more test coverage, better accuracy, faster testing, and cost savings.
These tools find defects early, make tests reusable, improve decisions, and work well in different development setups.
By using AI in testing, organizations can improve their testing, release better software, and stay competitive.