Check Out These Awesome Testing Tools
As the world of software development continues to evolve at breakneck speed, one thing is clear: artificial intelligence is leading the charge. In a recent column, Digital Pilgrims argued that its applications have sparked digital industrialization. Now we are starting to notice its effects. With the “automation testing market” set to grow from 24.7 billion to over 56.7 billion by 2027, according to a report by Markets and Markets, it’s clear that AI-driven development is no longer just in our dreams.
GitHub Copilot and its impressive code-generation capabilities got more and more developers turning to AI to save time and money. ChatGPT innovations have expanded what people can produce in their work hours by understanding, suggesting, debugging and even explaining code. But the potential applications for AI and large language models (LLM) go far beyond just code generation. For example, in testing, things are changing really fast.
CodiumAI, a company that has developed testing tools, assures that errors in software code cost U.S. businesses $2.08 trillion in 2020 alone. From self-healing tests to visual locators and AI analytics, AI-based automation testing is revolutionizing the field of software development, offering immediate and impactful opportunities for growth and innovation. So it is happening: the AI revolution has unlocked a world of endless possibilities in software development and testing. And we have put together a few of the more recent advances on AI based software testing to get you in the loop.
1. Browser Stack’s Selenium
Selenium is an open-source tool for web browser automation by Bowser Stack. By providing a single interface for writing test scripts in various programming languages, Selenium democratizes the process of ensuring web applications function correctly and meet user requirements. Its core component, WebDriver, executes test scripts through browser-specific drivers. This allows for greater flexibility and portability of test cases across different browsers and devices. Furthermore, Selenium’s integration with natural or programming language test frameworks, such as Cucumber or TestNG, provides developers with additional tools to create robust and reliable automated tests.
However, Selenium is not without its challenges. Maintaining and updating test scripts can be a complex and time-consuming task, and compatibility issues with newer browser versions or operating systems can arise. However, it counts with the support of a community of developers and it is committed to open-source principles, so it will continue to evolve.
2. CodiumAI’s TestGPT
TestGPT is an artificial intelligence model created by CodiumAI and based on OpenAI’s GPT-4 large language model, it works as an extension of the integrated development environment (IDE) that allows developers to iteratively create tests and fine-tune code based on the results of those tests. It uses generative AI models to compare code to the required specifications and determine its accuracy. Codium is available as an add-on in popular IDEs like VS Code and PyCharm, and additional IDEs and programming languages will be covered, as well as support for additional features and collaborations.
Still in development, this company was created recently and claimed to have raised 11m in march. CodiumAI says it is planning to expand and incorporate TestGPT into additional phases of the software development lifecycle to further empower test-driven development and component test information and test management, CI/CD integration, automated debugging, code optimization, and automated troubleshooting.
3. testRigor
testRigor is a software testing platform that utilizes AI technology to simplify test creation and improve software quality. With its AI-driven capabilities, testRigor can recognize text, images, and image inscriptions, as well as classify types of images such as arrows, download buttons, and dropdowns. It can also classify types of images and convert code into human-readable and executable test cases.
The platform also offers a record-and-playback tool that can convert code into human-readable and executable test cases. This feature helps bridge the gap between developers and testers. However, some potential shortcomings of the tool may include limited language support and the need for manual test case validation.
4. Appium
Appium is an open-source automation tool designed for testing mobile, web, and hybrid applications on iOS, Android, and Windows platforms. One of the key features is its cross-platform capability, allowing developers to write tests using the same API for multiple platforms. It is based on four main tenets: automating without modifying the app, being language and framework agnostic, using existing automation APIs, and being open-source.
Appium operates using a client/server architecture, with the server exposing a REST API and the client initiating sessions and sending commands to the server. Automation is performed in the context of a session, and the desired capabilities object is used to tell the server what type of automation session is needed. While Appium offers many benefits for mobile app testing, there are some limitations to consider, such as the learning curve for developers new to the tool, limitations with certain mobile web browsers, and the need for separate tests for each platform-specific feature.
5. Smart Bear’s Cucumber
If you’re looking for a tool that supports Behaviour-Driven Development (BDD), Cucumber is the answer. BDD is an agile software development process that encourages collaboration among developers, quality assurance experts and customer representatives in a software project and Cucumber is able to read executable specifications written in plain text and validates that the software does what those specifications say.
This tool works on Gherkin language, a set of grammar rules that makes plain text structured enough for Cucumber to understand. Gherkin encourages unambiguous executable specifications, automated testing, and documentation. Overall, the Cucumber grammar exists in different flavors for many spoken languages so that teams can use keywords in their own language.
