3 July 2024 Leave a comment QA
When working on test code, particularly UI tests, one common challenge is separating test data from test scripts. By test data, we refer to the values that get input into the Application Under Test (AUT). This separation is crucial for scalability and modifiability. Below, we explore various approaches to achieve this, highlighting practical examples and best practices.
Parameterization of Tests
Many test frameworks support the parameterization of tests, allowing you to supply values using a “data provider” method, object, or class. This mechanism typically involves fetching the values from an external source and handing them to the test framework in a grid-like structure (e.g., list of lists or array of arrays). Each row represents the values for one execution of the test.
For instance, in TestNG, this process is straightforward, whereas in JUnit, it may require additional configuration. Storing values in plain text files, like CSV, is advisable as it allows version control alongside the tests. Avoid binary data files, as they do not integrate well with version control systems.
File-Based Approaches
If your tests follow a full user scenario (e.g., log on, perform actions, log out), a file-based structure can be effective. Data-driven harnesses built into most test tools can iterate through a resource, executing tests for each data row. CSV files are particularly useful due to their simplicity and compatibility with version control systems. However, avoid using Excel for editing as it can strip out formatting details.
Additionally, you can include expected results in CSV files to compare against actual outcomes, ensuring validations aren’t hard-coded. This method is easy to manage and scales well for straightforward scenarios.
Database Solutions
For more complex test structures involving multiple parameterized routines, a database solution might be necessary. Storing test data in a database allows for more intricate relationships and easier management of large datasets. However, this approach requires careful versioning and backup strategies.
Creating a front-end for the database, such as an intranet application or a small dedicated tool, can simplify data management and allow non-scripters to contribute new test cases. This method is particularly useful when your test codebase is extensive and maintaining almost identical code in multiple tests is impractical.
Java-Based Approaches
Encoding test data in Java classes can also be a viable solution. This approach allows test scripts to remain agnostic to the original format of test data, as they rely on getter methods of Java beans. You can start with Java-based test data and later map it to other formats (e.g., XML, CSV) if needed.
Using the Builder pattern with a fluent interface can enhance this approach, providing strong IDE support (e.g., autocompletion, syntax highlighting). This method is particularly effective for designing a domain-specific language (DSL) that encapsulates test data creation, making it easier to maintain and scale.
Conclusion
Choosing the right strategy for separating test data from test scripts depends on the complexity of your test scenarios and the scale of your test codebase. Whether you opt for parameterization, file-based approaches, databases, or Java-based solutions, the key is to ensure modifiability, scalability, and ease of maintenance.
For those looking to streamline the process of creating and managing automated tests, consider using Repeato, a no-code test automation tool for iOS and Android. Repeato leverages computer vision and AI to create, run, and maintain automated tests efficiently. Its user-friendly interface and quick setup make it an excellent choice for quality assurance teams looking to enhance their testing processes.
For more information on effective test data management and automation strategies, explore our blog and documentation.
