AI in Software Testing : Top 5 Artificial Intelligence Tools
The software development process has changed drastically over the years, and modern development teams are increasingly relying on AI-based test automation platforms to ensure their software is of the highest quality. These platforms use AI to automate tests, improve test selection, prioritize tests, and detect visual imperfections. Let’s take a look at five top artificial intelligence testing tools and understand more about the use cases of AI in software testing.
- Synthesis is a powerful resource that aids in the generation of synthetic data specifically designed for computer vision and perception AI. It enables the creation of labeled training data on-demand, facilitating the development of ethical, accurate, and high-performing AI models. By leveraging this tool, researchers and developers can access a vast array of synthetic data that closely resembles real-world scenarios, allowing them to train their models effectively.
- Launchable is another popular AI-based test automation platform that helps teams optimize their testing processes with Predictive Test Selection. This powerful feature uses AI algorithms to identify high-value tests to run first, ensuring that teams get the most accurate results in the shortest amount of time. With Launchable, teams can also increase their release confidence by running fewer unnecessary tests and lessening the risk of introducing new bugs into their codebase.
- Sealights provides an innovative solution for automated testing with its Test Impact Analysis feature. By analyzing each individual test and assessing how it affects system performance, Sealights eliminates redundant tests and reduces overall testing time. The platform also auto-prioritizes tests based on how critical they are for successful application deployment so developers can focus on tasks with higher impact first.
- Applitools provides a comprehensive suite of AI-based tools designed to help developers accelerate application development while maintaining high standards of quality assurance. Applitools’ Visual Imperfection Detection feature uses advanced image comparison algorithms to detect subtle differences between different versions of an application or website quickly and accurately without manual intervention or scripting knowledge required. It also has Parallel Test Automation at Scale capabilities which allow users to run multiple parallel tests simultaneously across multiple browsers in order to speed up the entire testing process significantly.
- DiffBlue offers Automated Unit Test Generation which helps developers improve their unit test coverage with minimal effort required from them. This reduces the cost of quality as teams no longer need to spend time writing unit tests manually or spend money hiring specialized testers for this task. In addition to this, it also provides rich analytics and reporting capabilities so developers can get an understanding of their codebase quickly without having to dig through complex reports or set up dashboards manually themselves
As software development continues to evolve, so do the tools available for functional testing and automation. By leveraging artificial intelligence testing tools such as Functionize, Launchable, Sealights, and Applitools, development teams can ensure their applications are of the highest quality while accelerating delivery times significantly—allowing them to stay competitive in today’s rapidly changing market landscape.