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In software development projects, ensuring that the application meets both functional and performance standards is crucial for providing a high-quality user experience. A key aspect of this process is the use of test automation and performance testing. Test automation helps ensure that an application behaves as expected and is functionally sound, while performance testing helps detect issues related to speed, scalability, and overall responsiveness. They test the same applications, but the scope and the goal of testing is different. In many cases, test automation uncovers system slowness, which prompts the need for performance testing.
The Role of Test Automation in Detecting Slowness
In my project we had a situation where we added performance testing to the project’s scope, after consulting with the customer. This was initially initiated by the test automation team.
Our team has been working with the client for many years now and have quite a bit of tests and test suites created for the client. Currently the client is in a big ERP migration and integration project, where they add different departments to a centralized ERP solution.
What we have observed in the client’s system is that it has felt increasingly slow. Specifically, this has been evident in the test automation scripts, where we have been forced to add increasing amounts of waits, refreshes, and rechecks to the automation functions.
Together with the automation team, we concluded that the system’s slowness was affecting execution time and causing so many defects that we raised the issue with the client. Initially, we added some measurements and report timers in the automation tests. However, we also informed the client that our functional automation testing tool is not inherently designed for performance testing. Therefore, to achieve the best results, we advised the client to use a dedicated performance testing tool, as test automation tools are not designed for performance testing. As test automation tools are not really designed to be able to do performance testing.
The client did not have well-defined performance testing requirements and therefore not much of a scope, as they haven’t done or needed performance testing in a bigger scale before. Previously, it was sufficient to check that the application did not ‘feel slow.
However, as we have executed test automation over a long period of time, we had the data to showcase to client that there was a gradual decrease in performance evident in the test automation run reports. We highlighted this as a red flag, indicating that the system’s performance was deteriorating over time. Over the course of the investigation, it was found out that we had also revealed performance issues that were not anticipated earlier in the architecture. From our findings, several underlying performance bottlenecks were identified.
Performance Testing: Addressing Slowness and Ensuring System Scalability
Performance testing evaluates an application’s responsiveness, stability, and scalability under various conditions. It is an essential process for detecting issues such as slow response times, memory leaks, and bottlenecks that automated functional tests may not identify.
Performance testing focuses on simulating real-world load conditions to evaluate the system’s ability to handle user traffic and various levels of stress. By using tools to simulate high traffic, large amounts of data, or prolonged use, performance testing uncovers weaknesses that could impact the user experience. Something that test automation is not well-suited to test.
Performance testing helps identify issues such as:
- Slow response times: When system resources (e.g., CPU, memory) are strained, the system’s response time may increase, causing delays in processing requests.
- Bottlenecks: Poorly optimized code or architecture may lead to traffic congestion at specific points in the system, reducing its ability to process data efficiently.
- Scalability limitations: As the number of users increases, the system may struggle to handle the load, which can lead to downtime or crashes.
In the modern era of cloud-based services and microservices architecture, scalability is particularly important. Performance testing ensures that the system can grow without compromising its ability to deliver a quality experience to users.
Why Both Test Automation and Performance Testing Are Needed
While both test automation and performance testing have distinct roles, they are both essential for ensuring quality control in a software development project. The test automation team focuses on ensuring the system’s functional integrity. It ensures that the application behaves as expected in business requirement sense and helps identify functional issues early in the development process.
On the other hand, performance testing ensures that the system remains responsive and scalable under various loads. Automated tests might uncover slowness, but performance testing is necessary to fully analyze the system’s capacity to handle stress, user traffic, and scalability concerns. Additionally, functional automation cannot generate the concurrent user loads required for stress tests.
Combining both test automation and performance testing allows client to get a much better overview of the applications state. Automated tests ensure that functional requirements are met quickly and consistently, while performance tests provide deeper insights into the system’s scalability and stability. Together, they provide a holistic approach to quality control that balances both functionality and performance.
Conclusion
In onboarding a performance testing team to the client project, we discovered that test automation and performance testing play complementary roles in maintaining quality control within a software project. While test automation detects functional issues and can uncover potential performance problems, performance testing dives deeper to ensure that the system can scale and perform well under load. Both are needed for ensuring high-quality delivery, and their combination ensures that the application not only works as intended but also provides a seamless user experience to the end user even during peak user hours. By integrating both practices into the development cycle, teams can identify and address issues early, improving both the quality and performance of their applications. It is also important to highlight the need for continuous test execution and report storage. Without having data from test automation executions over long period of time, the downward trend in performance might have been missed.