Welcome to our project where we put the AVL tree and std::map through a series of rigorous tests to determine which data structure reigns supreme in various scenarios. Dive into our testing battlegrounds and see the results for yourself!
We rolled up our sleeves and put these structures to the test on Windows and Linux platforms, challenging them with:
- Correctness of Insertion & Deletion
- Maximum Size Handling
- Load Performance
- Memory Efficiency
- Search Speed (worst case)
Our tests were as tough as they were fair, ensuring that both the AVL tree and std::map had an equal opportunity to showcase their strengths and weaknesses.
Can they add and remove without a hiccup? We used hard-coded data to check their moves!
How much can they handle before crying for mercy? We pushed until std::bad_alloc showed its face.
They say pressure makes diamonds, or in our case, the fastest data structure. We inserted thousands of records with no break!
Using valgrind and macOS's Leaks, we made sure no bytes were left wandering.
Seek and you shall find, but how fast? We looked for the trickiest nodes to find out.
- std::map vs AVL Tree: Which is faster?
- Windows vs Linux: Does the platform change the game?
- Memory Leak: Are we eco-friendly with our memory usage?
Check out the results to see who won each round!
Not content with just Windows, we put on our penguin hats and repeated key tests on Linux. Did the cooler climate help our contenders? Find out!
- Choose your OS:
WindowsorLinux. - Compile the tests:
g++ -o performance_tests PerformanceTests.cpp. - Run and observe:
./performance_tests. - Don't forget to compare with our results!
For more in-depth analysis, you can view the Detailed Performance Testing Report.
Got a question about our methods? Or perhaps you have an idea to make our tests even better? Let us know!
Thank you to everyone who contributed to this project. Your hard work and dedication are greatly appreciated!
- 👤 Tasbi
- 👤 Madhur
- 👤 Mohammad Aeraf Khan
Your collective efforts made this project successful!
After a grueling showdown, the insights are clear. But in the world of data structures, today's victor might be tomorrow's runner-up. So we keep testing, learning, and optimizing!
Want more? Follow us on LinkedIn for more electrifying projects!