Robotic Process Automation (RPA) is an increasingly popular technology that enables businesses to automate mundane, repetitive tasks, thereby increasing efficiency and reducing human error. As with any software, thorough testing is crucial to ensure that the RPA code performs as expected and delivers the intended benefits. In this blog post, we will discuss the importance of testing RPA code, whether to use live data or a test system, how to create a test plan, and how to measure success.
The Importance of Testing RPA Code
Testing RPA code is essential for several reasons:
Ensuring that the automation process is accurate and efficient.
Identifying and addressing any bugs or issues before deployment.
Verifying that the automation code can handle exceptions and edge cases.
Validating the automation code's ability to integrate with other systems.
Minimising the risk of negative impacts on business operations.
Live Data vs. Test System
When testing RPA code, it's crucial to decide whether to use live data or a test system. Each approach has its pros and cons.
Live Data: Using live data provides a realistic environment for testing the automation code, as it involves actual data and processes. However, it can also pose risks, such as data corruption or exposing sensitive information. For clinical processes, we have found this gives a much lower exception rate at the point of go-live and, in my opinion, improves clinical risk and patient safety.
Test System: A test system, also known as a staging or sandbox environment, is a replica of the production environment with simulated data. This approach allows for thorough testing without risking the integrity of the live environment or exposing sensitive data.
In general, it is advisable to use a test system for RPA code testing to minimise potential risks and ensure a controlled environment for identifying and fixing issues. However, in reality, providing there are adequate controls and governance in place for the responsible use of data and test scripts, live systems will result in better outcomes.
Creating a Test Plan
A well-structured test plan is essential for effective automation code testing. Follow these steps to create a comprehensive test plan:
Define the scope: Outline the automated processes, components, and integrations that need to be tested.
Identify test scenarios: List possible test scenarios, including both common use cases and edge cases.
Develop test cases: Create specific test cases for each scenario, detailing the input data, expected outcomes, and validation criteria.
Prioritise test cases: Rank test cases based on their importance, complexity, and potential impact on business operations.
Schedule testing: Allocate time and resources for testing, ensuring that all stakeholders are available and informed.
Assign responsibilities: Designate team members responsible for executing tests, reporting results, and resolving issues.
To measure the success of your automation code testing, consider the following metrics:
Test coverage: The percentage of the RPA process covered by the test cases.
Test execution rate: The number of test cases executed within the allotted time.
Pass/fail rate: The ratio of successful test cases to the total number of test cases.
Defect density: The number of defects identified during testing, relative to the size or complexity of the RPA process.
Mean time to resolution (MTTR): The average time taken to resolve identified defects.
Test automation rate: The percentage of test cases that can be executed automatically, reducing the need for manual intervention.
Testing automation code is a critical step in ensuring that your automation solution delivers the intended benefits and minimises potential risks. By using a test system, creating a comprehensive test plan, and measuring success with relevant metrics, you can optimize your automation code and maximise the return on your automation investment.