Scripting Challenges in JMeter with Coding Solutions

Scripting Challenges in JMeter with Coding Solutions

Scripting is necessary in order to mimic advanced user behavior in JMeter. Handling dynamic data, applying custom logic, and error handling could be a challenge for newcomers. Here you have scripting challenges in JMeter with solutions based on Groovy or JavaScript for hands-on practice, assisting you in overcoming simple test plans. By understanding these, you will be in a position to design realistic and solid performance tests. Explore our JMeter course syllabus.

Scripting Challenges in JMeter

Here are the various JMeter Scripting Challenges and Solutions:

Dynamic Request Body

Challenge: Make a test that sends a variable JSON payload in every loop, like a varying product ID or user name. This is important for load testing APIs when data is not static.

Solution: Utilize the JSR223 Sampler using Groovy. Create the data dynamically and make it the request body.

import groovy.json.JsonBuilder

// Generate dynamic product ID

def productId = new Random().nextInt(1000) + 1;

// Create a map for the JSON object

def data = [

    productId: productId,

    productName: “Product-” + productId

]

// Build the JSON string and set it as the request body

sampler.setPostBody(new JsonBuilder(data).toPrettyString());

Real-time Example: For an e-commerce application, a performance test must mimic users adding different items to their carts, not the same item over and over.

Custom User Login

Challenge: Mimic a user login where the password and username are read from a CSV file. The script must read the credentials, make a login request, and store a unique session token to be used for other requests.

Solution:

• Use a CSV Data Set Config to extract username and password.
• Use a JSR223 Sampler for the login request.
• Use a JSON Extractor or a Regular Expression Extractor to extract the session token from the response.
• Store the token in a JMeter variable (e.g., ${token}).

// Use variables from CSV Data Set Config

def username = vars.get(“username”);

def password = vars.get(“password”);

// Assume a login function exists that returns a token

// This part is illustrative; you’d replace with your actual login logic.

def loginResponse = “{\”token\”: \”abc” + username + “\”}”

// Capture the token and store it

def token = new groovy.json.JsonSlurper().parseText(loginResponse).token;

vars.put(“authToken”, token);

Real-time Example: Testing the performance of a secure application where each user has to authenticate before the protected resources can be accessed.

Recommended: JMeter Course Online.

Generate a Unique Timestamp

Challenge: Most APIs need a special nonce or timestamp to avoid replay attacks and maintain request uniqueness. Create a Unix timestamp in milliseconds per request.

Solution: Utilize Groovy’s native System.currentTimeMillis() within a JSR223 PreProcessor.

// Generate a unique timestamp and store it in a variable

vars.put(“timestamp”, String.valueOf(System.currentTimeMillis()));

Real-time Example: Utilized in API calls for financial transactions or secure messaging apps where every request needs to be time-stamped uniquely for integrity.

Custom Error Handling

Challenge: Introduce a custom check to cause a request to fail if a particular error message is included in the response body, even if the HTTP status code is 200 (OK).

Solution: Employ a JSR223 Assertion. This enables you to create custom validation logic.

def response = prev.getResponseDataAsString();

// Check for a specific error message

if (response.contains(“INVALID_DATA”)) {

    AssertionResult.setFailure(true);

    AssertionResult.setFailureMessage(“Response contained ‘INVALID_DATA’ error.”);

}

Real-time Example: An API could respond with a 200 status code but a “User Not Found” message within the JSON body. A custom assertion makes this logical error trigger during the test.

Recommended: JMeter Tutorial for Beginners.

Loop with Custom Logic

Challenge: Implement a loop that runs based on a condition, such as processing all items in a list of results from an earlier request.

Solution: Utilize a While Controller. The loop condition can be a JMeter variable that is modified inside the loop.

// In a JSR223 PostProcessor after the request that returns the list

def items = new groovy.json.JsonSlurper().parseText(prev.getResponseDataAsString());

vars.put(“itemCount”, items.size().toString());

vars.put(“currentIndex”, “0”);

• • While Controller Condition: Integer.parseInt(vars.get(“currentIndex”)) < Integer.parseInt(vars.get(“itemCount”))

• Within the loop (e.g., JSR223 Sampler):

// Get the current item from the list

def index = Integer.parseInt(vars.get(“currentIndex”));

// Process item

// …

// Increment the index for the next loop iteration

vars.put(“currentIndex”, (index + 1).toString());

Real-time Example: A performance test that fetches a list of tasks for a user and then loops through every task to update its status.

Dynamic Path and URL Generation

Challenge: Create a distinct URL path for every request, such as incorporating a booking_id that was generated in an earlier step.

Solution: Utilize a Regular Expression Extractor to extract the ID of the previous request’s response and place it into a variable. Then utilize that variable for the subsequent HTTP Request sampler.

// In a Regular Expression Extractor after the booking creation request

// Field to check: Body

// Regular Expression: “booking_id”: “([^”]+)”

// Template: $1$

// Match No.: 1

// Variable Name: bookingId

// The next request path will be:

// /bookings/${bookingId}/details

Real-time Example: When a user successfully books a flight, the subsequent request to view flight details must employ the generated unique booking ID.

Recommended: JMeter Interview Questions and Answers.

Conditional Request Execution

Challenge: Perform a particular request (e.g., credit card payment) only if a particular condition is fulfilled in an earlier response (e.g., cart value exceeds $100).

Solution: Employ an If Controller. The condition may be a boolean expression on a JMeter variable.

// In a JSR223 PostProcessor after fetching cart details

def cartTotal = new groovy.json.JsonSlurper().parseText(prev.getResponseDataAsString()).total;

if (cartTotal > 100) {

    vars.put(“isPaymentNeeded”, “true”);

} else {

    vars.put(“isPaymentNeeded”, “false”);

}

If Controller Condition: ${isPaymentNeeded}

Real-time Example: A sample scenario to send a payment request only if a user has placed sufficient products to invoke the payment gateway, which is a similar behavior of a real user.

Custom Logging for Debugging

Challenge: Include custom log messages in the JMeter console or log file for sophisticated debugging during test execution.

Solution: Employ the JSR223 Sampler or PostProcessor and the log object.

log.info(“Starting user login for username: ” + vars.get(“username”));

// … some logic

log.warn(“Login failed for user ” + vars.get(“username”) + “. Status code: ” + prev.getResponseCode());

Real-time Example: When a test fails in a complicated situation, custom logs assist in identifying the specific step and data that caused failure without going through an enormous amount of default logs.

Simulate User Think Time

Challenge: Add realistic time delays between requests to simulate how a human user “thinks” or reads a page before clicking the next link.

Solution: There are inherently built-in timers, but a JSR223 Timer with scripting provides greater flexibility.

// Generate a random delay between 500ms and 3000ms

long delay = new Random().nextLong() % 2501 + 500;

Thread.sleep(delay);

Real-time Example: A consumer views a product page for a few seconds before putting an item into the cart. Emulating this with a delay makes the load test more realistic.

Recommended: Software Testing Courses in Chennai.

Process a Large CSV File

Challenge: Read a big CSV file (e.g., 10,000 distinct test cases) and handle each line. The challenge is to do this efficiently without loading the entire file into memory.

Solution: Employ a CSV Data Set Config and make sure it’s properly configured.

Configuration:

• Filename: data.csv
• Variable Names: userId, transactionAmount
• Recycle on EOF?: False (to terminate the test after all the users are processed)
• Stop Thread on EOF?: True (to terminate every thread once it exhausts data)
• Sharing Mode: All threads (to provide a different row to every thread)

Scripting: There is no additional scripting required for the actual process of reading. Just utilize the variables ${userId} and ${transactionAmount} within your request samplers.

Real-time Example: A stress test on a payment gateway with 10,000 distinct credit card numbers and transaction values from a file. This validates whether the system can process a large range of data without fail.

Explore: All Software Courses in Chennai.

Conclusion

Mastering these scripting challenges takes your JMeter skills past a basic level. You’ve now mastered dynamic data handling, using custom logic, and debugging sophisticated scenarios, all of which are vital for realistic performance testing. To further dominate JMeter’s advanced functionality and set yourself up for a career as a performance engineer, sign up for our in-depth JMeter course in Chennai.