The QA testing landscape is in constant motion, but artificial intelligence (AI) and machine learning (ML) are speeding up the evolution of QA processes and best practices at breath-taking speed. Automated test development tools are coming into their own niche with codeless and low-code options. AI and ML technology enable automated testing tools to offer more value with options like user-friendly interfaces and helpful AI/ML support. These options make tools more usable for QA testers and other development team members with little to no coding experience.
Codeless test automation enables companies to generate useful, valid, and efficient test automation without supplementing existing resources. Codeless tools use standard UI actions like dragging and dropping to create tests without having to edit or write scripted code. Early automation relied on record & playback functionality that failed to handle complex test scenarios without coding intervention but the addition of AI and ML, QA testers now have more options to create tests without needing to code.
These tools allow application providers to take advantage of the shift left testing approach, or test effectively as soon as development begins and throughout the SDLC. Agile development teams can better leverage test automation for faster and more thorough test coverage during iterations, sprints, or continuously to support CI/CD.
This guide describes codeless automation, the difference between codeless and low-code tools, and provides a roundup of 10 popular automated testing tools using AI/ML technology.
What is Codeless Test Automation?
Codeless test automation tools are special testing technology designed so that users are not required to view or edit code when creating test cases. Users without coding experience or knowledge can create useful automated tests. Codeless automation solves the common problem of coded test automation development taking too long between creation, execution, maintenance, and failure analysis.
A set of scripted automation tests within a framework like Nightwatch or Cypress is still the undisputed champion and ideal setup to manage the automation solution for a complex web app or SaaS product - you will find the greatest flexibility and ease of maintenance when a properly designed and implemented solution is in place. But agile teams must accomplish their tasks in short sprints and frequent releases, and there simply may not be the time to both perform manual sprint testing and script automation needed to keep up with the test requirements during your software development life cycle (SDLC), and the budget may not allow for dedicated QA automation engineers.
Some organizations cope with the time delay by automating tests after a release when the code stabilizes. However, for application providers that want to take advantage of test automation across the SDLC, codeless or low-code test automation tools are an excellent option. The difference is the assistance of AI and ML technology to speed up test development and reduce the time it takes to perform failure analysis and test maintenance. AI technology often repairs scripts automatically. AI also provides full reporting and analytics to measure testing effectiveness, coverage, and execution status on request.
Codeless vs. Low Code Test Automation
Codeless test tools differ from low-code test automation tools — codeless tools hide the coding behind the scenes, and test development occurs using tools in the UI. There’s no editing of code or script. Many codeless tools are truly low-code tools. Low-code test automation tools enable users to create codeless test cases but also allow users to edit the test scripts to handle complex scenarios or add other coded elements.
Codeless tools apply codeless architecture principles to decouple the business logic from the technical plumbing so that users can create codeless test automation without digging into syntax. Edits for maintenance or other changes occur through the interface. Codeless tools enable test creation through UI tools like drag and drop, visual interfaces, and improved record & playback options.
Keep in mind codeless tools abstract the coding work by using visual interfaces to replace coding scripts. However, in the back end, code is created but hidden from users. Regardless of the test automation tools used, QA testing teams need to still plan time for test maintenance and failure analysis.
Benefits of Codeless Testing Tools
The biggest benefit of codeless testing tools is that anyone can create quick and effective automated tests. Other benefits of codeless testing tools include:
- AI/ML technology to assist in test development
- AI/ML technology to provide on-request reporting and analytics
- AI/ML technology to improve test maintenance and failure analysis
- Teams can create reusable test automation any time during the SDLC
- Reducing the cost of automated test development and maintenance
- A complimentary automation suite to existing automation
- Cloud-based tools allow for creating, sharing, and refreshing test data
- Reduces the cost and complexity of building effective test automation
Codeless and low-code test automation tools are not perfect — test development still requires proper planning to ensure full coverage and value. Additionally, test execution is followed by failure analysis, and ongoing maintenance is required to ensure tests remain aligned with the application. Codeless and low-code tools do allow testing teams to ensure application quality remains high. The list below is a small sampling of tools. More high-quality codeless testing tools are available. Search the internet for additional tools to fit the team's needs.
10 Popular Codeless or Low-Code Testing Tools with AI/ML Technology
1. accelQ:
Super-AI powered codeless tool that pairs with Selenium. Used for automating tests for desktops, web, and mainframe-based applications, accelQ features self-healing technology to reduce or eliminate test maintenance. accelQ also uses natural language processing in English to create tests from manually written test cases. Other features include automated test generation, extendible and open source aligned, automated visual test design, and intelligent element explorer for fewer issues finding code objects.
2. Applitools
Applitools is a cloud-based codeless automation platform that automates visual UI tests across browsers, devices, and screen settings. AI/ML technology assists in defect identification in layouts and other visual changes between code builds. Testers generate test automation for visual testing by configuring and setting criteria. Provides test automation to guarantee visual accuracy within an application regardless of access point.
3. Katalon
Katalon Studio is a test automation tool that offers codeless and low-code testing options. Katalon enables automated testing for desktop, mobile, web, and APIs. Features drag-and-drop commands or record with playback options to create codeless test automation. The tool includes built-in libraries, project templates, keywords, and object repositories so teams can start quickly.
Leapwork is a cloud-based codeless test automation supporting testing applications built with Windows, web, or desktop. Includes predefined building blocks and default libraries to get QA testers working productively in less time. Leapwork supports cross-browser testing and parallel testing as well. Use the smart recorder tool for capturing steps or use the visual drag-and-drop tool. Integrates with LambdaTest.
5. Mabl
Mabl is a codeless and low-code test automation tool. Built for CI/CD, Mabl generates end-to-end test automation during the SDLC. Support web browser automation for Selenium WebDriver and IDE. Cloud-based test development, data creation, and test execution for increased ease of use and testing flexibility. Mabl features AI/ML technology that trains the system to generate application functional tests. Mabl integrates with BigQuery, JIRA, Jenkins, Slack, and Bamboo.
6. Perfecto
Perfecto offers different codeless tools for developing and automating testing. Perfecto tools Include testing for biometrics, geolocation, secondary authentication, voice assistance, and barcode scanning. Create visual tests using the scriptless flow chart builder tool and leverage AI-based test maintenance to keep tests updated from release to release. Use to support defect detection, parallel testing, and cross-browser support.
7. Telerik TestStudio
Codeless testing automation for both web and applications, as well as API and Load testing. AI-powered test recording tools to create tests that are reliable and nearly maintenance-free. Use the dashboard to track and monitor quality and generate AI/ML-infused reports and test results. TestStudio includes a built-in scheduling feature for creating various test suites or for continuous testing.
8. Testim.io
Testim’s popularity comes from its simple and easy-to-use interface for QA testers. Testers can build, generate, and automate tests completely codeless AI-powered test creation using drag-and-drop tooling. AI input helps testers identify defects before testing begins. Testim works to test APIs, Web, and Mobile.
9. Testsigma
Testsigma is another cloud-based codeless test automation tool enhanced with AI/ML technology. QA testers use Testsigma to automatically generate and execute tests. Works for mobile and web applications. Testsigma comes with built-in integrations for CI/CD tools and testing frameworks, and allows QA testers to execute tests in parallel and save significant time. Consider using the advanced analytics for reporting and measuring performance.
10. Tricentis Tosca
Tricentis Tosca provides end-to-end test automation and supports codeless test automation for web, desktop, mobile, and mainframe applications. Tosca features separate test creation tools for functional, performance, and regression testing and uses AI technology to support test development issues, defect identification, and test result reporting.
Most tools offer free trials anywhere from seven to 30 days. Consider trying several tools to discover which ones best suit the team’s testing needs. Codeless test automation provides extensive benefits, and testing teams can get up and running quickly, however, plan time for training and experimentation for best results. Training and experimentation allow testers to become familiar with a tool and use it to optimize and maximize testing value and efficiency. Codeless test automation allows anyone on the Agile team to create effective test automation quickly. Leverage the AI/ML technology to reduce test maintenance and failure analysis time while identifying more defects throughout the SDLC.