Load testing in Rest API - Time & Space Complexity

Time Complexity: Load testing

O(n)

Understanding Time Complexity

Load testing checks how a system handles many requests at once.

We want to know how the system's work grows as more users send requests.

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

// Simulate handling multiple API requests
function handleRequests(requests) {
  requests.forEach(request => {
    processRequest(request);
  });
}

function processRequest(request) {
  // Process each request (fixed time)
}
    

This code processes each incoming request one by one.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Loop over all requests.
• How many times: Once for each request received.

How Execution Grows With Input

As the number of requests grows, the work grows in the same way.

Input Size (n)	Approx. Operations
10	10 processRequest calls
100	100 processRequest calls
1000	1000 processRequest calls

Pattern observation: Doubling requests doubles the work.

Final Time Complexity

Time Complexity: O(n)

This means the time to handle requests grows directly with the number of requests.

Common Mistake

[X] Wrong: "Handling more requests takes the same time as handling one."

[OK] Correct: Each request needs its own processing, so more requests mean more total work.

Interview Connect

Understanding how work grows with users helps you design systems that stay fast under pressure.

Self-Check

"What if processRequest took longer for some requests? How would that affect the time complexity?"

Practice

1. What is the main purpose of load testing in REST APIs?

easy

A. To check how many users the API can handle at once

B. To find syntax errors in the API code

C. To improve the API's user interface design

D. To add new features to the API

Solution

1. Step 1: Understand load testing goal

   Load testing is done to see how many users or requests an API can handle simultaneously without failing.

2. Step 2: Compare options with load testing purpose

   Only To check how many users the API can handle at once talks about handling many users at once, which matches load testing's main goal.

3. Final Answer:

   To check how many users the API can handle at once -> Option A

4. Quick Check:

   Load testing = check user load [OK]

Hint: Load testing measures user capacity, not code errors [OK]

Common Mistakes:

• Confusing load testing with debugging
• Thinking load testing improves UI
• Assuming load testing adds features

2. Which of the following is the correct way to start a basic Locust load test script?

easy

A. from locust import User

class MyUser(User):
def run():
get('/')

B. import locust

class MyUser:
def task():
client.get('/')

C. from locust import HttpUser, task

class MyUser(HttpUser):
@task
def load(self):
self.client.get('/')

D. from locust import HttpUser

class MyUser(HttpUser):
def test():
self.get('/')

Solution

1. Step 1: Identify correct Locust import and class

   The Locust library uses HttpUser and @task decorator to define user behavior.

2. Step 2: Check method and client usage

   from locust import HttpUser, task class MyUser(HttpUser): @task def load(self): self.client.get('/') correctly uses HttpUser, @task, and self.client.get('/'). Other options miss correct imports or method calls.

3. Final Answer:

   from locust import HttpUser, task class MyUser(HttpUser): @task def load(self): self.client.get('/') -> Option C

4. Quick Check:

   Use HttpUser and @task decorator [OK]

Hint: Look for HttpUser and @task decorator to spot correct syntax [OK]

Common Mistakes:

• Missing @task decorator
• Using wrong class name like User instead of HttpUser
• Calling get() without self.client

3. What will be the output when running this Locust test snippet?

from locust import HttpUser, task

class MyUser(HttpUser):
    @task
    def index(self):
        self.client.get("/home")

# Simulate 10 users making requests concurrently

medium

A. No requests will be sent because task is missing

B. 10 users will send GET requests to /home concurrently

C. Syntax error due to missing main function

D. Only 1 user will send a GET request to /home

Solution

1. Step 1: Understand Locust user simulation

   Locust simulates multiple users running the tasks concurrently when configured to do so.

2. Step 2: Analyze the code behavior

   The class defines a task sending GET requests to /home. If run with 10 users, all will send requests concurrently.

3. Final Answer:

   10 users will send GET requests to /home concurrently -> Option B

4. Quick Check:

   Locust simulates multiple users running tasks [OK]

Hint: Tasks run concurrently for all simulated users [OK]

Common Mistakes:

• Thinking only one user runs the task
• Assuming missing main causes syntax error
• Believing tasks won't run without explicit start

4. Identify the error in this Locust test code:

from locust import HttpUser, task

class MyUser(HttpUser):
    def index(self):
        self.client.get("/")

medium

A. Class name should be lowercase

B. HttpUser class should be imported from requests

C. self.client.get should be self.get

D. Missing @task decorator before index method

Solution

1. Step 1: Check for task decorator usage

   Locust requires the @task decorator on methods to mark them as tasks to run.

2. Step 2: Verify other parts of the code

   HttpUser is correctly imported, self.client.get is correct, and class names are capitalized by convention.

3. Final Answer:

   Missing @task decorator before index method -> Option D

4. Quick Check:

   Tasks need @task decorator [OK]

Hint: Always add @task decorator to methods to run as tasks [OK]

Common Mistakes:

• Forgetting @task decorator
• Importing HttpUser from wrong module
• Using self.get instead of self.client.get

5. You want to test your REST API's login endpoint under heavy load using Locust. Which approach best simulates realistic user behavior?

hard

A. Create a task that sends POST requests with different user credentials and add wait times between requests

B. Send continuous GET requests to the login endpoint without any delay

C. Run a single user sending POST requests in a tight loop

D. Only test the API with one user to avoid server overload

Solution

1. Step 1: Understand realistic load testing

   Realistic load testing simulates many users with varied data and natural pauses between actions.

2. Step 2: Evaluate options for realism

   Create a task that sends POST requests with different user credentials and add wait times between requests uses different credentials and wait times, mimicking real user behavior. Others either overload or under-test the API.

3. Final Answer:

   Create a task that sends POST requests with different user credentials and add wait times between requests -> Option A

4. Quick Check:

   Use varied data and wait times for realism [OK]

Hint: Add wait times and varied data for realistic load [OK]

Common Mistakes:

• Sending requests nonstop without delay
• Testing with only one user
• Using only GET requests for login