Best practices for designing scalable and maintainable Robot Framework test suites

Designing scalable and maintainable test suites is essential in the world of automated testing. Robot Framework test suites allow teams to achieve this goal with ease and flexibility. Learn key best practices, tips, and tricks to help your team design optimal test suites that are both performant and maintainable.

Definition of Robot Framework

Robot Framework is an open source test automation framework used for acceptance testing and acceptance test-driven development (ATDD). It has a keyword-driven approach and utilizes the tabular test data syntax. It is platform and application independent and can be extended with Python, Java, .NET, or any other programming language.

Robot Framework is extremely easy to set up, use and modify to get both Android and iOS apps tested. The test syntax that it uses is based on keywords and these keywords are quick to edit and further configure to make a match with the application under test.

Furthermore, testing capabilities provided by Robot Framework can be easily extended with the test libraries which can be implemented using Python, Java and even some other languages are supported. The nifty thing with Robot Framework is how those mentioned keywords work. Users can quickly create new keywords, either using the existing example ones or by writing everything from scratch. If you look for more generic information about Robot Framework, there are plenty of great examples and online documentation on GitHub.

Overview of Benefits of Robot Framework

Robot Framework is an open -source test automation framework for acceptance testing and acceptance test-driven development. It is a keyword-driven testing framework that uses tabular test data syntax. It has easy-to-use tabular test data syntax and it utilizes the keyword-driven testing approach. It has a simple architecture that makes it easy to extend with custom test libraries. It also supports data-driven testing, meaning that scripts can be run with different input and verification values. It can be used for both unit and acceptance testing, making it a versatile tool for automating tests. Benefits of using Robot Framework include:

  • Easy-to-use tabular test data syntax
  • Keyword-driven testing approach
  • Simple architecture, making it easy to extend with custom test libraries
  • Supports data-driven testing
  • Can be used for both unit and acceptance testing
  • Easy integration with other tools and frameworks

Best Practices for Designing Scalable and Maintainable Robot Framework Test Suites

When it comes to designing scalable and maintainable Robot Framework test suites, there are several best practices to follow that can help ensure the success of your testing project. Here are some key best practices to consider:

  1. Keep test cases atomic and reusable: Create test cases that are independent of each other, so they can be run in any order without affecting the outcome. Also, make sure to reuse test cases in multiple suites to avoid code duplication.
  2. Use descriptive names and comments: Give your test cases and suites meaningful names and add comments to explain the purpose and functionality of each one. This will help other team members understand your test cases and make it easier to maintain them.
  3. Implement a clear folder and file structure: Organize your test cases and suites in a clear and consistent folder and file structure. This will make it easier to navigate and find specific test cases and suites, especially as your test suite grows over time.
  4. Define test data separately: Separate your test data from your test cases, so you can reuse the same data in multiple test cases. This will reduce the amount of duplicate code and make it easier to maintain your test suite.
  5. Use variables and resource files: Use variables to define values that are used repeatedly in your test cases, and create resource files to store common keywords and functionality that can be reused across multiple test cases.
  6. Incorporate continuous integration and version control: Use continuous integration tools like Jenkins or Travis CI to automate your testing process, and version control tools like Git to keep track of changes to your test suite over time.

By following these best practices, you can create a scalable and maintainable Robot Framework test suite that is easy to understand, maintain, and scale. You will save time and resources, reduce errors and testing costs, and improve the overall quality of your products.

a. Define Your Test Architecture

Robot framework has a highly modular architecture as seen in the figure below. It is a technology-independent framework that uses keyword-driven testing. Users can create higher-level keywords from the existing keywords. Along with the generation of keywords, users can also create test libraries in different programming languages.

b. Use Structure and Design Patterns

Structural design patterns are concerned with how classes and objects can be composed, to form larger structures. The structural design patterns simplifies the structure by identifying the relationships. These patterns focus on, how the classes inherit from each other and how they are composed from other classes.

Types of structural design patterns

There are following 7 types of structural design patterns.

  • Adapter Pattern: Adapting an interface into another according to client expectation.
  • Bridge Pattern: Separating abstraction (interface) from implementation.
  • Composite Pattern: Allowing clients to operate on hierarchy of objects.
  • Decorator Pattern: Adding functionality to an object dynamically.
  • Facade Pattern: Providing an interface to a set of interfaces.
  • Flyweight Pattern: Reusing an object by sharing it.
  • proxy Pattern: Representing another object.

c. Create Reusable Keywords

Keyword sections are used to create new higher-level keywords by combining existing keywords together. These keywords are called user keywords to differentiate them from lowest level library keywords that are implemented in test libraries. The syntax for creating user keywords is very close to the syntax for creating test cases, which makes it easy to learn.

Basic syntax

In many ways, the overall user keyword syntax is identical to the test case syntax. User keywords are created in Keyword sections which differ from Test Case sections only by the name that is used to identify them. User keyword names are in the first column similarly as test cases names. Also user keywords are created from keywords, either from keywords in test libraries or other user keywords. Keyword names are normally in the second column, but when setting variables from keyword return values, they are in the subsequent columns.

Settings in the Keyword section

User keywords can have similar settings as test cases, and they have the same square bracket syntax separating them from keyword names.

User keyword name and documentation

The user keyword name is defined in the first column of the Keyword section. Of course, the name should be descriptive, and it is acceptable to have quite long keyword names. Actually, when creating use-case-like test cases, the highest-level keywords are often formulated as sentences or even paragraphs.

User keywords can have a documentation that is set with the [Documentation] setting. It supports same formatting, splitting to multiple lines, and other features as test case documentation. This setting documents the user keyword in the test data. It is also shown in a more formal keyword documentation, which the Libdoc tool can create from resource files. Finally, the first logical row of the documentation, until the first empty row, is shown as a keyword documentation in test logs.

Sometimes keywords need to be removed, replaced with new ones, or deprecated for other reasons. User keywords can be marked deprecated by starting the documentation with *DEPRECATED*, which will cause a warning when the keyword is used. For more information, see the Deprecating keywords section.

User keyword tags

Both user keywords and library keywords can have tags. Similarly as when tagging test cases, there are two settings affecting user keyword tags:

Keyword Tags in the Setting section

All keywords in a file with this setting always get specified tags.

[Tags] with each keyword
Keywords get these tags in addition to possible tags specified using the Keyword Tags setting.

User keyword arguments

Most user keywords need to take some arguments. The syntax for specifying them is probably the most complicated feature normally needed with Robot Framework, but even that is relatively easy, particularly in most common cases. Arguments are normally specified with the [Arguments] setting, and argument names use the same syntax as variables, for example ${arg}.

d. Separate Test Data and Test Cases

Test data is an integral part of the testing process for a tester. It provides information to the tester to facilitate finding defects and corrective actions. Test engineers load the application with data or stress it with huge amounts of invalid data to check breakpoints and other aspects of the application’s performance. While executing test cases, test engineers need to input some data into the application to get the expected output.

Test data is a production-like set of data used by test cases to determine whether an application is working correctly. Test data is usually collected into a document called a test data document that helps organize it so testers can easily access it when they run their tests.

A Test Case is a set of conditions used to evaluate a software product and determine whether it complies with business requirements. A poorly constructed test case can result in significant flaw leakage. This can be time and money-consuming. As a result, writing effective test cases is critical to the success of any software project.


In conclusion, designing scalable and maintainable Robot Framework test suites is essential for ensuring the success of any testing project. The best practices outlined in this topic provide a solid foundation for building high-quality and effective test suites that can handle changes in the system under test and continue to deliver reliable results over time. By following these practices, such as keeping test cases atomic and reusable, using descriptive names and comments, and implementing a clear folder and file structure, teams can create test suites that are easy to understand, maintain, and scale. Additionally, incorporating continuous integration and version control tools can help to streamline the testing process and ensure that test suites remain up to date and effective. Ultimately, by adhering to these best practices, teams can save time and resources, reduce errors and testing costs, and improve the overall quality of their products.


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