ShivaniIn the software quality assurance (QA) process, one of the critical components is the test automation. Test automation traditionally is performed by writing scripts that run predefined actions to verify the behaviour or a functionality of a particular feature or a component.
This scripted test automation required expertise in the scripting language, and as the scripts got more complex, they became unable to maintain. Then came the era of artificial intelligence (AI) and subsequently Generative AI. Using generative AI, the test automation scope has widened significantly and has also opened up new possibilities in test automation. With Generative AI, QA professionals can find innovative ways to enhance the coverage of testing activities, and also the effectiveness and efficiency of the test automation.
In this article, we will explore the five popular generative AI-based test automation tools that define the new innovative era of automation testing.
Generative AI Capabilities to Leverage in Test Automation
Generative AI includes machine learning (ML) models and techniques using which new data is generated that is identical to training data. The ML models and techniques include:
- Natural Language Processing (NLP): NLP generates and understands human-like text.
- Generative Adversarial Networks (GANs): GANs are used to create realistic images or for data augmentation.
- Reinforcement Learning (RL): RL is used for decision-making and strategy optimization.
All these ML models/techniques can be used in test automation to perform various tasks that are shown in the following figure.
- Automatic Test Case Generation: Diverse and comprehensive test scenarios can be generated by leveraging usage patterns and application data.
- Test Data generation: Generative AI models can also create realistic and diverse datasets for testing purposes. These are especially useful when the actual data available is scarce, sensitive, and difficult to collect. Synthetic data used for user inputs and database records is of this type.
- Screen/Image testing: Generative AI can compare visual elements in an application across various screen sizes, versions, and environments to identify defects in computer vision algorithms.
- Self-Heal Test Scripts: As application interfaces evolve, AI can adapt test scripts in real time, thus reducing maintenance efforts.
- Analyse Test Results: Test outcomes can be analyzed by AI and it can provide insights into the test output, identify patterns and suggest optimizations.
- Optimize Test Execution: AI makes efficient use of resources available for test execution by prioritizing tests based on risk and likelihood of failures.
Generative AI-based Automation Testing Tools
There are several testing tools that use generative AI that provide either commercial or open-source software. These tools transform the way the tests are conducted. Various capabilities that these generative AI-based tools support are test scenario and test case generation, test automation generation, test suite prioritization and optimization, test effort estimation, defect prediction, and test analysis.
Using generative AI-based testing tools enhances the test efficiency, test coverage, and robustness of the testing system. In this section, we present a brief introduction to the five most popular generative AI-based testing tools in the market.
testRigor
testRigor is a generative AI-powered intelligent no-code test automation tool. testRigor’s features make it stand out from the rest of the AI-based tools. Using testRigor, manual testers can create test scripts faster than automation testers do with traditional automation tools. With its many features, testRigor drastically reduces maintenance costs to a minimum.
It is designed to help manual testers, business users, and developers automate complex test scenarios without writing any code.
It eliminates test flakiness, automatically adapts to UI changes, and integrates seamlessly with CI/CD workflows.
Though testRigor is a paid tool, it offers free plans, too. Let us look into the key features of testRigor.
Features:
- Natural Language Automation: testRigor allows you to write test scripts in plain English, making it accessible to non-technical team members like manual testers, management, and business analysts. This broadens participation in test creation, increasing test coverage and addressing more scenarios.
- Visual Testing: testRigor, with the support of Vision AI, helps you perform visual testing. You can do this in one step, “compare screen”. Another option is to take a screenshot of the screen and then save that as test data. You can compare every new run with the saved screenshot to ensure there are no visual changes on the application pages. This is very helpful as it covers an extra step in validation. Read in detail how to perform Visual Testing in plain English with testRigor.
- Comprehensive Testing: testRigor handles a wide range of testing needs, including web, mobile apps, desktop apps, APIs, visual, accessibility, mainframe, graph, chatbots, LLMs, images, AI features, Flutter apps, all within a single tool.
- Automatic Element Detection: Vision AI allows testRigor to automatically detect UI elements based on their visual appearance. This is particularly useful in dynamic environments where elements frequently change position, size, or styling. You can mention the element name or its position in plain English, and that’s all. testRigor identifies the element using AI context and performs the requested action. To know more, you can read this blog: testRigor locators.
- Self-Healing Tests: Vision AI in testRigor helps create self-healing tests that automatically adapt to minor changes in the UI. When a change in the application’s visual elements is detected, testRigor can adjust the test scripts dynamically, reducing the need for manual updates and minimizing test maintenance efforts.
- Easy Migration: If you have your manual tests in TestRail, Zephyr, or other test management tools or in SpecFlow, it is extremely easy to turn your manual tests into automation scripts directly using generative AI and reusable rules.
Pros and Cons:
| Pros | Cons |
| Non-technical users can write and maintain test cases as they are written in plain English | Requires stable internet connection for cloud execution |
| Testing support across desktop, web, mobiles, mainframes, and API | Not suitable for game testing |
| Self-healing capability reduces test maintenance and flakiness | |
| Allows seamless integration with modern CI/CD pipelines | |
| Can test user intent, true/false statements, chatbots, LLMs, Flutter Apps, mainframes, and more. |
ACCELQ
ACCELQ is a cloud-based continuous testing platform and provides automation capabilities for AI and web testing. It expedites the testing procedure by automating crucial lifecycle components including test design, planning, generation, and test execution.
ACCELQ also offers codeless natural language functionality and API automation. This is a browser-based product and eliminates the need for an IDE.
Features:
- AI-powered No Code Test Automation: Using ACCELQ, anyone can intuitively create and maintain automated tests on the cloud without coding. Teams can easily carry out cross-browser tests, bringing down test execution time considerably.
- Fastest Test Automation Development with Lowest Maintenance: ACCELQ helps teams eliminate the manual testing approaches. It helps with the test automation so that teams can detect defects early in the development cycle.
- ACCELQ automates all aspects of the quality lifecycle: From test design to test planning and execution, making it one of the fastest test automation tools.
- Web, API, Mobile, and Desktop Automated in the Same Flow: ACCELQ makes testing across different platforms possible in one central place. It seamlessly integrates with existing tools and offers a unified platform for the entire enterprise stack.
- In-sprint Automation to Align with DevOps and Agile: ACCELQ enables in-sprint automation with industry-first visualized abstraction for functional testing. Such early and continuous automation at agile speed ensures testing happens in parallel with development and not as an afterthought.
- Zero Programming: ACCELQ is a powerful tool that allows testers to handle real-world testing complexities while being extraordinarily intuitive and scalable. It also enables manual testers to automate testing without writing a single line of code.
Pros and Cons:
| Pros | Cons |
| AI-powered No-Code Test Automation | Limited customization for complex scenarios in mobile testing |
| Zero programming | Automation of desktop-based applications is difficult |
| Top-notch support | |
| Ease of test case creation | |
| Easy script scheduling and report generation |
Functionize
Functionize is an enterprise-level, generative AI-based cloud-based platform design to test highly complex web applications. By using AI and deep learning technologies, Functionize digital workers act as extensions of the QA team to accelerate the delivery of high-quality tests.
Features:
- Cloud Scale: The Functionize Automation Cloud is an all-in-one unified SaaS platform that eliminates infrastructure overhead and maintenance. Functional and visual automation can be integrated into a single, cohesive platform, saving time and costs while scaling effortlessly.
- Cross-browser: Hundreds of workflows can be executed concurrently across various platforms, ensuring comprehensive automation coverage.
- End-to-End Automation Beyond the Interface: Offers a suite of web-based tools to automate beyond just the interface, including databases, file uploads and downloads, APIs and DBs, text messages, emails, and more, ensuring full operational coverage.
- Every device scenario covered: Complex environments are emulated using cloud-based virtualization. The need to maintain costly on-premises infrastructure is eliminated. Workflows can be automated across diverse platforms seamlessly without the overhead of managing physical hardware or multiple environments.
- Visual validation with human-like perception: Every aspect of UI can be inspected using computer vision.
Pros and Cons:
| Pros | Cons |
| Basic and simple language is used for automation scripts | Environment issues and UI breakage |
| Improve Test Reliability and Speed with Functionize’s AI-Powered Tech | More features can be incorporated, like automation of API calls and product-specific testing. |
| Implementation was easy and very user-friendly, but it needs code stability | |
| The AI-driven approach has significantly reduced test maintenance, improved execution speed, and enhanced overall test reliability. |
Katalon
Katalon TestOps is a modern, comprehensive quality management platform that enables teams to easily and efficiently test, launch, and optimize the best digital experiences. It provides capabilities that allow test automation teams to collaborate, manage, scale, and continuously improve testing operations.
Katalon helps users test any type of app with a single, all-in-one platform that is easy for tester beginners, yet powerful for pros and development teams.
Features:
- Image-based Testing: Katalon can find and interact with image objects. This feature is helpful when objects retain the same appearance even if the underlying structure has changed.
- Record and Playback with Debugging Options: Test failures can be corrected quickly on the newly recorded test.
- Combine Multiple Data Files: Input values can be read from the scripts for multiple data file combinations.
- Data-driven Testing in Dynamic Test Suites: Data binding can be conducted in the dynamic test suite.
- Parallel Execution: Multiple test suites can be executed at the same time, thus reducing execution time.
Pros and Cons:
| Pros | Cons |
| Integrated with CI/DevOps workflow and other tools | Lack of scripting languages
|
| Intuitive analytics dashboard and reports | Small community |
| Supports several types of testing | Performance issues |
| User-friendly GUI | |
| Mild learning curve + learning materials |
BrowserStack
BrowserStack is a cloud-based testing platform. It can be used to perform automated and manual testing of native and hybrid mobile and web applications across a wide range of browsers and devices.
Features:
- Real-time testing on a cloud-based infrastructure: Developers and testers can perform real-time testing on a cloud-based infrastructure, which allows them to test their applications on a wide range of devices and browsers simultaneously.
- Integration with Popular Test Automation Frameworks: BrowserStack integrates seamlessly with popular test automation frameworks such as Selenium, Appium, and Espresso.
- Support for over 2,000 Real Browsers and Devices: BrowserStack supports over 2,000 real browsers and devices, including mobile emulators and simulators. Thus, developers can test their applications on virtually any device or browser combination.
- Video Recordings and Screenshots of Test Runs: BrowserStack automatically records videos and takes screenshots of test runs, and also provides real-time device logs.
- Collaboration and Testing Capabilities for Remote Teams: BrowserStack makes it easy for developers and testers spread across the world to work together on testing projects and share feedback in real-time.
- Localization Testing: BrowserStack provides localization testing capabilities that allow developers and testers to test their applications in different languages and locales.
Pros and Cons:
| Pros | Cons |
| Comprehensive Device and Browser Coverage | BrowserStack can be expensive |
| Integration with Popular Test Automation Frameworks | Offers limited customization |
| Collaboration and Sharing Capabilities | Requires a stable and reliable internet connection to function properly |
| Offers Localization Testing | |
| User-Friendly Interface |
Conclusion
Generative AI is a transformative opportunity for test automation and offers solutions to longstanding challenges in QA. With the generative AI-based test automation tools we have discussed in this article, it is clear that there is a considerable improvement in automation with improved efficiency and software quality.
Teams can now focus on developing more effective test cases and delivering robust applications faster and quickly.
