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Writer's pictureCraig Risi

The Pros and Cons of different UI automation test tools - Robot Framework



The last few open-source testing tools that I’ve looked at have been primarily built around Java or Node.JS-related technologies – even if they themselves could work with any programming language. Today we’re going to look at another popular open-source testing tool, that is this time based around Python and perfectly suited for robotic process automation (RPA).


And while we refer to the Robot Framework as a testing tool, it does suitably gain its name as the tool is based on a prebuilt automation framework which allows testing teams to get automating quickly by making use of its many pre-built functions and commands while the framework itself is quite robust limiting a lot of the flakiness you would expect from any tool with a heavy abstraction layer.


What makes Robot Framework so popular is that it is very readable and easy for non-coders to get into. It follows a very specific key-word driven approach that allows testers to insert simple commands, easily parameterize their test data and let the tool do the rest. For this reason, it is quite popular amongst many testing teams where testers are perhaps not very technical but have some basic knowledge of coding and they can then easily get tests automated without too much complexity.


On the flip side, however, as with any similar sort of framework-based tool, you need to make use of its framework, which locks you into the tool and makes it difficult to migrate scripts across to other tools should you ever need them. Additionally, many of the pre-built commands work a certain way and are not easy to customize, plus add a layer of maintenance should you ever wish to try customizing it. The tool does allow users to create their own methods and commands – which can come in handy, but then you miss out on arguably its biggest benefit which is the wide array of pre-existing commands.



Another big benefit of the tool is that it can execute on most applications and platforms. It can do this by leveraging modules from other automation tools (like the Selenium library and AutoIT) and using the benefits of those tools to help expand what can be achieved while also adding its own features too.


As a test framework, Robot Framework balances the idea of simplicity for non-technical users while offering a fair amount of customization fairly well. And while it might not be the framework of choice for those more technically inclined, for companies with large testing teams that perhaps aren’t strong coders, it can still allow them to contribute to the automation effort.


History of Robot Framework

Below is a brief history of the Robot Framework and how it has grown from its foundation to one of the more popular testing frameworks in use today:

  • Development Beginnings (2005-2008): The Robot Framework project was initiated by Pekka Klärck in 2005. Originally, it was developed as an internal test automation framework at Nokia Networks (formerly known as Nokia Siemens Networks). Klärck, along with other developers, worked on creating a tool that could address the shortcomings of existing test automation frameworks.

  • Open Sourcing (2008): In 2008, Nokia Networks released the Robot Framework as an open-source project under Apache License 2.0. This allowed the framework to gain wider adoption and benefit from contributions from the open-source community.

  • Growth and Community Contributions (2008-2011): After the open sourcing, the Robot Framework gained popularity and started attracting contributors from various organizations. The community grew, and several libraries and plugins were developed to extend the framework's capabilities.

  • Version 2.0 Release (2011): In 2011, Robot Framework 2.0 was released, introducing significant improvements and new features. This release included enhancements to the core framework, support for Python 2.6 and 2.7, and better integration with external tools.

  • Further Enhancements and Adoption (2012-2015): Over the next few years, the framework continued to evolve, with regular updates and new releases. The community actively contributed to the project, expanding the available libraries, tools, and integrations. The Robot Framework gained popularity across industries and became widely adopted for test automation.

  • Python 3 Support (2016): In 2016, the Robot Framework introduced support for Python 3, enabling users to take advantage of the latest Python features and improvements.

  • Recent Updates (2017-Present): The Robot Framework has continued to receive updates and improvements, addressing bug fixes, introducing new features, and enhancing the overall usability and extensibility. The community has played a crucial role in providing feedback, contributing code, and maintaining the project.

Pros:

  • Easy syntax: Robot Framework uses a keyword-driven approach that is easy to read and write, even for non-programmers. It has a simple tabular syntax using plain English keywords, making it accessible for testers and business users.

  • Extensibility: The framework supports extensibility through libraries and custom keywords, allowing users to integrate it with other tools and technologies. It has a rich ecosystem of libraries and plugins for various functionalities and integrations.

  • Test data-driven approach: Robot Framework supports a data-driven approach, enabling users to create data tables and iterate through different test cases using variables and data-driven test templates. This makes it efficient for testing multiple scenarios with different inputs.

  • Platform and language independence: Robot Framework is platform-independent and can run on different operating systems such as Windows, macOS, and Linux. It also supports multiple programming languages, including Python and Java, for implementing custom libraries and keywords.

  • Built-in reports and logs: The framework generates detailed reports and logs automatically, providing visibility into test execution results and enabling easy debugging and analysis of test failures.

Cons:

  • Limited programming capabilities: While Robot Framework is designed to be user-friendly, its simplicity comes with limitations in terms of programming capabilities. It may not offer the same level of flexibility and advanced programming techniques as more complex frameworks.

  • Steeper learning curve for complex scenarios: While the syntax is easy to grasp for basic test cases, handling more complex scenarios may require additional knowledge and experience. Users may need to learn how to implement custom libraries or keywords to handle specific functionalities.

  • Lack of integrated development environment (IDE): Although there are several IDEs and plugins available for Robot Framework, it doesn't have an official, dedicated IDE. Users may need to rely on third-party tools or text editors for development and debugging.

  • Limited community support for certain libraries: While the Robot Framework has a wide range of libraries available, some specific or niche libraries may have limited community support. This could pose challenges when trying to find solutions or troubleshoot issues.

  • Slow pipeline execution speed: The Robot Framework is a little slow in execution to be included in traditional CI/CD pipelines

When to select Robot Framework:

  • If you have a large team of testers who aren’t strong coders but still need to get them involved in the automation effort.

  • You want to get started quickly with your test automation without needing to develop a framework from scratch

  • You don’t need your automated tests to operate extensively in the CI/CD pipeline.

Operating as both a tool and a framework, Robot Framework is a great option for companies wanting to get started with test automation and see quick results. It lacks the robustness and speed of more modern tools, but its ease of use allows more members of a team to contribute to the automation effort which can make up for it.

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