Data-driven testing (DDT) is a powerful approach that reportedly helps teams increase test coverage by up to 50% without writing additional test scripts, all while reducing human errors by up to 30% and saving teams up to 40% of testing costs.
What exactly makes data-driven testing so beneficial, and how does it translate to testing in Agile environments? These aspects are widely explored in this article.
Understanding DDT
To gain a deep understanding of the possibilities offered by data-driven testing, it is crucial to start with the definition of this testing approach.
DDT (https://www.executiveautomats.com/resources/articles/data-driven-testing) is a methodology that involves the separation of test data from the test scripts, as opposed to hardcoding, which embeds specific test data into the test scripts. This separation brings great flexibility to the testing process, as it allows the same test scripts to be used with a wide variety of data from different sources, such as databases, spreadsheets, and XML files.
With this method, teams design test scripts with parameters or placeholders, which are then filled with data during execution. At the same time, teams are also required to prepare accurate, relevant, and up-to-date data in an external file or database, which is then connected to the scripts. During test execution, the test runner reads the test data from the source.
Advantages of Adopting DDT by Agile Teams
The benefits of data-driven testing (DDT) extend beyond Agile environments, but Agile development teams, with their emphasis on frequent and thorough testing and the need for regular feedback, find this approach particularly advantageous. Here is a breakdown of the advantages of this methodology:
Reusability
As mentioned earlier, a key aspect of data-driven testing is the reusability of test scripts. With it, there is no need to create multiple scripts to cover similar data sets, as they can be easily fed into reusable scripts during the test execution phase.
Scalability
The reusability of test scripts facilitated by DDT translates into greater scalability. QA teams can easily increase the number of tests using different data without creating separate test scripts.
Increased Test Coverage
Reusability also makes it easier for testers and developers to enhance test coverage. By using the same test scripts, teams can test various input scenarios. Meanwhile, the time saved on creating multiple test scripts for different data can be effectively utilized for other testing tasks, further expanding test coverage.
Simplified Test Maintenance
Test script maintenance, one of the most resource-consuming tasks related to automated testing, becomes significantly easier when test scripts do not include hardcoded data. Instead of rewriting or editing scripts whenever the tested software or data changes, teams only need to edit the data itself.
Enhanced Consistency and Accuracy
When there is no need to create similar test scripts to cover different data, teams are much less likely to make mistakes that could compromise the consistency of the testing process. Since the same test scripts will be used with different data, inconsistencies are less likely to occur.
Not only is the accuracy of test scripts enhanced by DDT, but the quality of the tested software also benefits from this approach. With greater test coverage, reduced manual effort, and more accurate test results, Agile teams can perform more frequent testing and gain better insights into software quality.
Cost Savings
All the DDT benefits discussed above contribute to the cost savings Agile teams can enjoy. Rather than investing in additional manual work, missing quality insights due to insufficient testing and feedback, or facing incorrect test results from script errors, teams can achieve more cost-effective testing.
Enhanced Alignment with Agile Practices
The iterative and incremental nature of Agile development often requires quick adjustments to test scenarios and data, which can be difficult to achieve if test scripts lack high reusability. The data-driven approach, in turn, makes it much easier for teams to align their work with Agile requirements.
Data-Driven Testing Considerations
Agile teams planning to adopt data-driven testing (DDT) should be prepared for potential challenges.
First, DDT requires high-quality test data that is relevant, accurate, and complete. Without this, the testing results may be misleading. Depending on the project, ensuring the availability and accuracy of this data can be a time-consuming and resource-intensive task.
Second, it is crucial to understand that test maintenance will still be necessary. Although DDT simplifies script management, organizing and maintaining data can be challenging, particularly with large data sets and multiple data sources. Inefficient data retrieval or processing can disrupt data-driven testing.
Finally, teams should be aware of the limitations of test automation tools, as not all of them support the DDT approach out of the box. For newly assembled teams, support for DDT should be a crucial criterion when choosing a tool. Meanwhile, teams that have already adopted a tool that lacks support for data-driven testing may need to invest in custom development to adjust the solution to their needs.
Final Thoughts
The main advantage of data-driven testing supported by modern test automation tools like Executive Automats, is the greater reusability of its scripts, which leads to many other benefits. DDT can enhance scalability, increase test coverage, improve the quality of testing, and help teams improve software quality, all while providing financial savings. For Agile teams, DDT is particularly useful as it simplifies the editing of test scripts and modification of test data, which is frequently required for the incremental testing preferred in Agile environments.
However, Agile teams should keep in mind that DDT adoption will require more resources for data management. The effectiveness of data-driven testing will also heavily depend on the test automation tool used and the performance of the data retrieval and processing flow.
