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Approval Testing | Benefits, How to Perform & Tools

Testing is a crucial part of the software development process to ensure the quality and performance of the software. In traditional testing, you typically create detailed test cases with expected outcomes. However, if you rely solely on assertions, your code can get really long. Every time you need new sets of assertions, it can become really confusing for you to test, especially complex objects or frameworks. This makes standard unit tests a bit tricky to handle, especially in dynamic environments.

That is where approval testing comes in. It provides a different way of testing that makes things simpler. Approval testing captures and approves system outputs instead of dealing with complex assertions, making the testing process simpler.

In this blog, we will understand what approval testing exactly is, the benefits of approval testing, how you can write approval testing, and what the best approval testing tools are. Let’s dive in deep and start with the approval testing definition.

What is Approval Testing?

Approval testing is a way of testing where you capture the output of a software, system, or program and then compare it with the previously approved version to quickly verify that the current output matches the expected output. This can be beneficial in Agile development environments where frequent changes are expected.

This testing is mostly helpful where the expected output is complex or not easy to determine in a precise manner, such as graphical or large datasets. Hence, approval testing becomes efficient and offers more flexibility in adapting to changes while providing a clear way to validate results.

When Is It Appropriate to Use Approval Testing?

Approval testing comes with its own benefits where in several scenarios, manual or visible inspection is valuable, especially when the expected output is not predictable or varies over time.

Here are some of the scenarios where it is appropriate to use approval testing.

1. Stable Output: Approval testing is particularly suitable when dealing with stable outputs, providing a reliable method to verify and validate expected results against a predefined reference standard.

2. Data Transformation Processes: In data transformation processes, approval testing can be used to confirm that the transformation logic is producing the expected output as the data evolves.

3. Test Legacy Systems: It is challenging to write traditional unit tests in legacy systems due to complex dependencies or lack of proper architecture. Hence, approval testing can ensure that changes don’t introduce unintended side effects.

4. Third-party Integration Testing: When dealing with third-party APIs or systems where the expected output is not under your control, approval testing can help capture and verify the responses.

5. Rapid Prototyping: During the prototyping phase, the system is expected to evolve quickly. In such cases, approval testing can help quickly adapt to changes and ensure the new versions produce the expected results.

When Not to Use Approval Testing?

Even though approval testing is one of the best choices for testers in scenarios with well-defined and stable expected outputs, it may not be the optimal solution in highly dynamic environments or systems with non-deterministic behavior.

Let’s discuss some of the scenarios when it is not appropriate to use approval testing.

1. Mobile App Responsiveness: Mobile app responsiveness testing involves evaluating performance across various devices and network conditions. Approval testing may not adapt well to the diverse and dynamic nature of mobile environments.

2. Strict Compliance Requirements: In cases where strict compliance or regulatory requirements demand specific testing methodologies, you must go for other testing methods, which may be supplemented with approval testing to meet these standards.

3. Complex Business Logic: If your system has intricate business logic where the output depends on a multitude of factors, traditional unit testing or behavior-driven testing might offer more precise validation instead of approval testing.

4. Critical Path Testing: Identifying and testing critical paths and dependencies require a dynamic testing approach that reacts to changes in the system’s flow. Approval testing, focused on static reference outputs, may not address the dynamic nature of critical path scenarios.

5. Real-time System: Approval testing is not ideal for real-time systems that need immediate responses, as the potential delays in the validation process and the overhead of updating reference outputs can hinder performance.

What are the Benefits of Approval Tests?

Explore various benefits of approval testing in this section, gaining insights into how this methodology enhances testing efficiency, fosters collaboration, and contributes to the reliability of software development processes.

1. Reduced Time for Writing Tests

Approval testing significantly reduces the time spent on writing tests by eliminating the manual updating of test cases with new expected outputs. Once an output is verified and approved, future test runs automatically compare results. However, you need to take precautions while updating approved files to prevent introducing incorrect results into the testing process.

2. Adaptable Output Verification and Clear Presentation

Approval testing proves to be beneficial for systems generating non-deterministic outputs, such as those involving graphical interfaces or complex data structures. It offers flexibility in output verification and ensures clarity in presenting test results.

3. Enhanced Collaboration

Approval testing facilitates seamless collaboration between developers and testers. By capturing and approving actual outputs, developers can endorse correct results, while testers can efficiently investigate and address any discrepancies that arise.

4. Efficient Handling of Large Data Structures

This testing is particularly beneficial for applications dealing with large and complex data structures. Approval tests simplify the whole validation process. Their ability to handle extensive output data makes them well-suited for scenarios where traditional testing methods may become difficult to execute.

How to Write Approval Tests?

Writing approval tests is all about ensuring the stability and reliability of software functionalities. Hence, this process involves creating a baseline or “approved” version of the output and subsequently comparing any changes against this baseline. The following steps provide a clear and structured approach for writing approval tests.

Step 1. Identify the Test Scenario: You have to figure out the functionality or the feature of the software that you want to test.

Step 2. Generate Initial Output: Run the test scenario and capture the output. Save this as the initial or “approved” version.

Step 3. Write Approval Test Code: You need to create a test script that executes the same scenario and generates the output. Then implement the logic to compare the new output with the approved version.

Step 4. Run the Approval Test: Execute the approval test to compare the current output with the approved version.

Step 5. Manual Review and Approval: The tester can manually review the results. If the output is as expected, then they can manually approve it. If the output has changed intentionally, update the approved version.

6. Iterate and Maintain: Testers need to rerun approval tests regularly as your software evolves. This is to ensure that the updated approved versions reflect intentional changes and are compatible enough with the ongoing changes.

Approval Testing Process

Approval testing involves a systemic and straightforward process with the following steps:

1. Record the Approved Output

Start by manually testing the system or component and noting down the expected output in a designated file, commonly a text file known as the “approved file.” This file acts as the reference point for subsequent tests.

2. Automate the Test

Develop an automated test script that runs the system or component with specific inputs, capturing the output generated during the test execution. This automation streamlines the testing process and ensures consistency.

3. Compare the Result with the Approved Output

After the automated test runs, you can compare the obtained output with the content stored in the approved file. A match indicates a successful test, while a mismatch signals a failure, suggesting a change in the system that needs immediate attention.

4. Review and Update the Approved File as Needed

In case of a test failure with expected changes, update the approved file to align with the new correct output. If the alterations are unexpected or incorrect, thorough investigation and corrective actions for the system or test are necessary.

By following these steps, approval testing provides a systematic and efficient way to validate outputs, ensuring the reliability of your software components.

How to Automate Approval Testing?

If you are looking to automate approval testing, Testsigma can help you to achieve this. As Testsigma comes with various products specially designed to suit your custom testing needs, it becomes easy to set up initial approval tests and seamlessly integrate automation into your workflow for efficient and collaborative testing processes.

1. Choose Testsigma Products

Testsigma offers various products for your testing requirements. Carefully begin the process by selecting solutions, such as – Testsigma Cloud for scalable and cloud-based testing, Testsigma Community for collaborative testing efforts, and Testsigma Enterprise for handling larger-scale projects with enterprise-level automation needs.

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2. Set Up Initial Approval Tests

Initiate the process by manually recording and establishing expected outputs within Testsigma. These initial approval tests serve as the foundation for subsequent automated testing.

3. Automate with Testsigma Features

Leverage the automation capabilities of Testsigma Cloud or Testsigma Enterprise to create robust automated test scripts. 

Assertions can be setup to approve the tests automated. Or visual testing can be used to approve tests according to the visual baselines created.

Execute these scripts to perform systematic testing of your system or software, capturing and comparing outputs efficiently.

4. Integrate with CI/CD

Seamlessly integrate Testsigma into your Continuous Integration/Continuous Delivery (CI/CD) pipeline. This ensures that approval tests are automatically triggered with each code change, providing continuous validation and early detection of potential issues.

5. Document and Share Practices

Document best practices for maintaining and updating approved files within your team. Share guidelines that facilitate effective collaboration, ensuring that team members are aligned on procedures and practices for seamless integration of Testsigma into the testing workflow. Regularly update this documentation to keep the team informed of any evolving practices or features.

You can automate your approval tests for
web, mobile, desktop applications and APIs,

from the same place, with Testsigma

Check out Testsigma

Approval Testing Tools

Approval testing tools streamline the verification process of software outputs by comparing actual results to approved baselines. In addition to Testsigma, below are some tools that help with approval testing.

1. TextTest

TextTest is a free tool designed for testing the functionality of text-based programs. It operates by running a program in various ways through the command line and uses the text output to control the application’s behavior.

Unlike many current acceptance testing frameworks that rely on manually written assertions, TextTest compares the plain text output generated by programs with a predefined ‘gold standard.’ For Python and Java GUI testing, StoryText, an open-source tool, complements TextTest seamlessly.

2. Jest

Jest, created by Facebook, is an open JavaScript testing tool ideal for React projects. It is more convenient for ensuring that your UI does not change abruptly. 

In a typical snapshot test for a mobile app, Jest renders a UI component, captures a screenshot, and checks it against a stored reference image. If the images differ, it signals either an unexpected change or the need to update the screenshot to match the new version of the UI component.

3. Diffblue Cover

Diffblue Cover is an advanced tool that automates unit testing for Java applications, utilizing artificial intelligence to generate comprehensive test cases. 

While not a conventional approval testing tool, its automated approach aligns with approval testing principles by validating code behavior and integrating seamlessly into CI/CD pipelines, contributing to code reliability and minimizing the manual effort required for testing.

Conclusion

Through this blog, we have learned that approval testing emerges as a powerful and flexible approach, offering a streamlined alternative to traditional testing methodologies. As we’ve explored the benefits, scenarios, and how-to aspects of approval testing, it is evident that this methodology enhances testing efficiency and adapts well to scenarios where expected outputs are challenging to define precisely.

For seamless automation and integration into your testing workflow, consider exploring Testsigma, a comprehensive testing solution tailored to your custom needs. Elevate your testing practices and embrace the efficiency and collaboration that approval testing brings to the forefront. Make your testing journey smoother with Testsigma today.



Frequently Asked Questions

What is the difference between a unit test and an approval test?

The main difference between a unit test and an approval test lies in their focus and testing approach. Whereas a unit test is designed to validate the functionality of a unit or component of code in isolation, approval tests are broader and focus on the overall behavior of a system or component, capturing and validating its output.

In short, unit tests are commonly used during the development phase to verify individual code units. Approval tests are particularly beneficial for complex or non-deterministic scenarios where precise output expectations are challenging to define in advance.

How is approval testing different from assertion-based testing?

The choice between these approaches depends on the testing scenario and the nature of the software being tested. Approval testing is often used for scenarios where a tester needs to validate the output or behavior of the software. It is like looking at the output of a system and deciding if it is okay based on a saved example.

On the other hand, assertion-based testing is more automated and focuses on verifying specific conditions within the code, making it suitable for automated testing in various scenarios, especially in the context of software development. Assertion-based testing is like having a checklist that the computer follows automatically to make sure everything is working as expected, without needing a person to check each time.


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