Running a Test Suite with Over a Million Test Cases

Running a Test Suite with Over a Million Test Cases

21 May 2024 Stephan Petzl Leave a comment Tech-Help

Managing a distributed test environment can be challenging, especially when dealing with a large number of test cases. In this guide, we will explore effective strategies to run a test suite with over a million test cases without overwhelming your system resources.

Understanding the Problem

When running extensive test suites, you may encounter issues such as high memory usage and system slowdowns. This is particularly true if your testing framework, such as Robot Framework with pybot, blocks significant amounts of RAM, leading to performance degradation and eventual freezing.

Proposed Solution: Using Separate Processes

An effective approach to managing memory usage and maintaining performance is to spin up each test case as a separate process. This method allows the memory allocated to each process to be released upon completion, thereby preventing memory bloat.

Steps to Implement the Solution

  • Isolate Test Cases: Separate each test case into individual processes. This isolation ensures that memory is freed after each test case completes.
  • Process Management: Utilize a process management tool or script to handle the creation and termination of processes. This can be achieved through Python’s multiprocessing module or similar tools in other programming languages.
  • Distributed Execution: Consider distributing the test cases across multiple machines using remote shell (rsh) commands. This not only helps in managing memory but also reduces the load on a single machine.

Implementing Inter-Process Communication

When separating test cases into different processes, it is crucial to maintain communication between them. This can be achieved through shared memory or inter-process communication (IPC) mechanisms.

Using Shared Memory

Shared memory allows multiple processes to access common data. In Python, this can be implemented using the multiprocessing.shared_memory module. Here is a simple example:

from multiprocessing import Process, shared_memory

def test_case_1(shm_name):
    existing_shm = shared_memory.SharedMemory(name=shm_name)
    # Perform test operations and update shared memory

def main():
    shm = shared_memory.SharedMemory(create=True, size=1024)
    process = Process(target=test_case_1, args=(,))
if __name__ == "__main__":


By isolating test cases into separate processes and utilizing shared memory for communication, you can efficiently run large test suites without overwhelming your system resources. This approach not only improves performance but also enhances the reliability of your testing process.

Enhancing Your Testing with Repeato

If you are looking for a more streamlined and efficient way to manage your automated tests, consider using Repeato. Repeato is a No-code test automation tool designed for iOS and Android applications. It leverages computer vision and AI to create, run, and maintain automated tests quickly and easily.

With its intuitive test recorder and scripting interface, Repeato allows both novice and advanced testers to automate complex use cases. Additionally, Repeato supports testing websites inside Android emulators or devices, with explicit web testing support coming soon. To learn more about Repeato and how it can help you manage large test suites effectively, visit our blog or check out our documentation.

For more information and to get started with Repeato, visit our download page.

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