elemes/test/LOAD_TESTING.md

Load Testing Documentation for C Programming Learning Management System

Overview

This document describes how to perform load testing on the C Programming Learning Management System to ensure it can handle at least 50 concurrent students accessing the application.

Requirements

• Python 3.7+
• Locust (installed via pip)
• The LMS application running on your local machine or a test server

Setup

1. Install Locust

pip install locust

Alternatively, install from the requirements file in the test directory:

cd /path/to/lms-c/test
pip install -r requirements.txt

2. Ensure the LMS Application is Running

Start your LMS application:

cd /path/to/lms-c
./start.sh

Or if running directly:

python app.py

By default, the application runs on http://localhost:5000.

Running the Load Test

Basic Load Test

To run a load test simulating 50 users with a hatch rate of 2 users per second:

cd /path/to/lms-c/test
locust -f load_test.py --host=http://localhost:5000

Then open your browser and go to http://localhost:8089 to configure the load test.

Command Line Load Test

To run the load test directly from the command line without the web interface:

locust -f load_test.py --host=http://localhost:5000 --users=50 --spawn-rate=2 --run-time=5m --headless

This command will:

• Simulate 50 users (--users=50)
• Spawn 2 users per second (--spawn-rate=2)
• Run for 5 minutes (--run-time=5m)
• Run in headless mode without the web interface (--headless)

Test Scenarios

The load test script simulates the following student behaviors:

1. Viewing the homepage (30% of requests) - Students browsing available lessons
2. Viewing lesson pages (40% of requests) - Students reading lesson content
3. Compiling code (20% of requests) - Students submitting C code for compilation
4. Logging in (10% of requests) - Students authenticating with tokens
5. Validating tokens (10% of requests) - Students validating their access tokens
6. Tracking progress (10% of requests) - Students saving their lesson progress

Monitoring and Metrics

During the load test, Locust provides the following metrics:

• Users: Number of concurrent users
• Failures: Number of failed requests
• Requests per second: Average request rate
• Average response time: Mean response time across all requests
• 95th percentile response time: Response time below which 95% of requests complete
• 99th percentile response time: Response time below which 99% of requests complete
• Total requests: Total number of requests made during the test

Performance Benchmarks

For the application to be considered capable of handling 50 students simultaneously, it should meet these benchmarks:

• Less than 1% failure rate
• Average response time under 2 seconds
• 95th percentile response time under 5 seconds
• No significant degradation in performance as user count increases

Customizing the Load Test

You can modify the load_test.py file to adjust:

• The number of users simulated
• The distribution of different types of requests
• The wait time between requests
• The sample code used for compilation tests
• The tokens used for authentication

Troubleshooting

Common Issues:

1. Connection Refused: Ensure the LMS application is running on the specified host/port
2. High Failure Rate: Check application logs for errors during the load test
3. Memory Issues: Monitor system resources during the test
4. GCC Compilation Errors: The application compiles C code, which may consume resources

Resource Monitoring:

Consider monitoring system resources (CPU, memory, disk I/O) during the test using tools like htop, iostat, or vmstat.

Conclusion

This load testing setup allows you to verify that the C Programming Learning Management System can handle at least 50 concurrent students. Regular load testing should be performed, especially after major updates, to ensure the application continues to meet performance requirements.