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JMeter Interview Questions
Apache JMeter is an open-source software tool developed by the Apache Software Foundation. It is a Java-based desktop application primarily used for performance testing of web applications.

JMeter allows users to simulate heavy loads on servers, networks, or objects to test their performance under various conditions. It can also be used to analyze overall performance, functional behavior, and measure response times.
Key features of Apache JMeter :

Load Testing : JMeter can simulate a large number of users accessing a web server, application, or network to measure its performance under heavy load.

Stress Testing : It can stress test a system to its maximum capacity to identify its breaking point or to check how it performs under extreme conditions.

Performance Testing : JMeter measures the performance of an application by analyzing its response time, throughput, and resource utilization under different scenarios.

Functional Testing : It can simulate real user behavior by sending requests to web servers, databases, and other services to test their functionality.

Distributed Testing : JMeter supports distributed testing where multiple JMeter instances can be used to simulate a large number of users accessing the system simultaneously.

Protocol Support : It supports various protocols including HTTP, HTTPS, JDBC, FTP, SOAP, JMS, LDAP, TCP, and more, making it versatile for testing different types of applications and services.
Apache JMeter works as a load testing tool by simulating user behavior to test the performance of web applications, APIs, and other server-based services.

Here's a detailed explanation of how JMeter operates :

* Test Plan Creation
* Thread Groups
* Samplers
* Configuration Elements
* Timers
* Assertions
* Listeners
* Execution
* Monitoring and Analysis
* Reporting
In JMeter, a Test Plan is the top-level organizational component that serves as the starting point for building and executing performance tests.

It acts as a container for all the elements and components necessary to define and execute a performance test scenario.

Here's a more detailed explanation of what a Test Plan is in JMeter:

* Container
* Hierarchical Structure
* Scenarios Definition
* Thread Groups
* Execution Settings
* Variables and Properties
* Listeners and Reporting
5 .
What is a Thread Group?
In JMeter, a Thread Group is a fundamental element used to simulate a group of users (or virtual users) executing a set of test scenarios concurrently. Thread Groups play a crucial role in defining the workload and concurrency of a performance test.
In JMeter, Samplers are components responsible for generating various types of requests to the target server or application being tested. They simulate the actions performed by real users, such as accessing web pages, submitting forms, or calling APIs. Samplers play a crucial role in performance testing as they are the ones that generate the load on the target system and collect response data for analysis. Here's a more detailed explanation of what Samplers are in JMeter:

Request Generation : Samplers generate different types of requests to interact with the target server or application. This includes sending HTTP requests (GET, POST, PUT, DELETE, etc.), FTP requests, JDBC requests, SOAP/XML-RPC requests, JMS requests, and more.

Protocols Supported : JMeter provides a wide range of samplers that support various protocols and technologies, allowing users to test different types of applications and services. For example, the HTTP Request sampler is used to simulate interactions with web servers over HTTP or HTTPS protocols, while the JDBC Request sampler is used to execute SQL queries against a database.

Configuration : Samplers allow users to configure request parameters such as URL, method, parameters, headers, body data, and authentication details. Users can customize the sampler settings to simulate different types of user interactions and scenarios.

Response Handling : After sending a request, samplers collect the response from the target server or application. This includes response data, status codes, headers, and cookies. Samplers capture this information and pass it on to other elements in the test plan for further processing or analysis.

Assertion and Validation : Samplers often work in conjunction with assertions to validate the correctness of the server's responses. Users can add assertions to samplers to verify response data against expected criteria, ensuring that the server behaves as expected under load.

Execution : During test execution, samplers are executed concurrently by multiple threads within the thread groups defined in the test plan. Each sampler simulates the actions of a virtual user, generating requests and collecting responses as per the specified configuration.
There are certain activities that are generally performed during this task and they are :

* Testing tool selection
* Performance test execution
* Performance test planning
* Analysis of test requirements
* Analysis of test results
* Script implementation
* These activities are pretty common and can simply be performed.
Performance testing is examining server responses in multiple formats before delivering them to the client. As a sampler component of JMeter is implemented, listeners give a graphical representation of data gathered by JMeter regarding those test cases. The user can view sampler results in the form of tables, graphs, trees, or plain text in a log file.

Listeners can be changed at any point during the test, including within the test plan. JMeter provides roughly 15 listeners, but the most commonly used ones are table, tree, and graph. In short, Listeners are used to storing the results of load testing execution in various formats, such as a table, tree, graph or any other appropriate format that may be given to the client. JMeter comes with a variety of built-in listeners, and many more can be added through plugins, depending on your needs. The following are a few of the inbuilt listeners: View Results in Table,  Graph Results, Aggregate Report, Aggregate Graph, Response Time Graph and Assertion Results.
Distributed testing in JMeter refers to the capability of running performance tests on multiple machines simultaneously, coordinated by a single JMeter instance. This approach allows testers to generate a larger load on the target system, distribute the load across multiple machines, and achieve higher scalability and performance testing capacity. Here's how distributed testing works in JMeter:

* Master-Slave Architecture : In distributed testing, there is a master-slave architecture where one JMeter instance acts as the master and coordinates the test execution, while multiple JMeter instances act as slaves and execute the test scenarios.

* Setup : To set up distributed testing, users need to install JMeter on all the machines that will act as slaves. The master machine controls the test execution and sends test scripts and configurations to the slave machines.

* Network Configuration : The master and slave machines must be connected to the same network, either locally or over a network. They communicate with each other using the Java RMI (Remote Method Invocation) protocol.

* Test Plan Configuration : Users configure the test plan in the master JMeter instance as they would for a single-machine test. The test plan includes thread groups, samplers, listeners, and other elements that define the test scenarios.

* Distribution of Threads : In the test plan, users specify the distribution of threads across the slave machines by configuring the number of threads allocated to each slave. This determines how the load will be distributed among the different machines.

* Execution : Once the test plan is configured, users start the test execution from the master JMeter instance. The master distributes the test scripts and configurations to the slave machines, and each slave starts executing the test scenarios concurrently based on the allocated threads.

* Data Collection : During the test execution, each slave collects performance data and metrics locally. The collected data is then sent back to the master machine periodically or at the end of the test for aggregation and analysis.

* Aggregation and Analysis : The master JMeter instance aggregates the performance data collected from all the slave machines and presents it in a unified view using listeners and reporting tools. Users can analyze the combined test results to evaluate the performance, scalability, and reliability of the target system.
In JMeter, a Timer is a test element used to introduce delays between requests or samplers in a Thread Group. Timers play a crucial role in simulating realistic user behavior and controlling the pacing of the test execution. Here's a detailed explanation of what a Timer is in JMeter:

Delay Introducer : Timers are used to introduce delays or think times between consecutive requests or samplers executed within a Thread Group. These delays simulate the time taken by real users to perform actions or interact with the target system.

Realistic User Behavior : By adding delays between requests, Timers help simulate realistic user behavior and avoid overwhelming the target system with an unrealistic flood of requests. This is especially important in performance testing to accurately assess the system's behavior under load.

Types of Timers : JMeter provides various types of Timers to cater to different testing scenarios and requirements. Some of the commonly used Timers include Constant Timer, Gaussian Random Timer, Uniform Random Timer, Synchronizing Timer, etc.

Configuration Options : Timers offer configuration options that allow users to customize the delay introduced between requests. Users can specify fixed delays, random delays within a range, or synchronization points to coordinate the timing of multiple threads.

Scope : Timers can be added at different levels within the Test Plan hierarchy, including at the Test Plan level, Thread Group level, or individual Sampler level. This allows users to control the timing and pacing of the test execution at various granularities.

Pre-Processing : Timers are executed before the associated request or sampler is executed. They do not affect the execution time of the request itself but introduce a delay before the request is sent to the target system.

Usage : Timers are commonly used in scenarios where users perform actions with varying inter-request intervals, such as browsing web pages, filling out forms, or interacting with web applications. By adding Timers, users can emulate such behavior and generate more realistic load profiles.
A master-slave configuration is a type of distributed testing in which multiple machines are used to load test a single server.

It's critical that all machines are connected to the same network and have the same JMeter version. In distributed testing, one machine is designated as the master, while the others are designated as slaves.

The procedure is as follows :

* Edit the JMeter.properties file on the master system and add the IP addresses of slave machines to the remote host column.
* Save the file and then reopen JMeter.
* Select Remote Start from the RUN menu in JMeter and enter the IP address of the system to be invoked.
* To start all the slave machines for testing, go to the RUN menu and select Remote Start all.
12 .
How can we record performance test scripts in JMeter?
JMeter has HTTP(S) Test Script Recorder using which we can perform operations on a browser and the HTTP requests get recorder in JMeter.
The different kinds of applications that can be tested using JMeter are-

* Websites
* Web services – REST and SOAP
* Databases(JDBC)
* Shell scripts
* FTP
* LDAP
* TCP
* SMTP, POP3, IMAP
Parameterization is the process of parameterizing the user input or other test inputs. So as to use different values for different users and loop iterations.

For instance, an external CSV file can be created with multiple login credentials and then passed to the load test script in order to fetch different credentials for each iteration.
A Workbench in JMeter is a temporary area of storage for the test elements. It also contains non-test elements like HTTP Proxy Server, which can be configured to record scripts via browser in JMeter. Any element placed in the workbench doesn’t get saved after with the test plan’s JMX script.
It is basically a Java-based tool that is meant to test the performance of apps. Its open-source nature makes it simply the best for this task. A number of testing related to the performance of the apps can simply be handled with this tool. It really doesn’t matter whether it's web services or web-based apps. Moreover, it is capable to handle databases as well as FTP servers.
Assertions in JMeter are components used to validate and verify the correctness of the server's response during performance tests. They play a crucial role in ensuring that the target system behaves as expected under load. Assertions allow testers to define specific criteria or conditions that the response data must meet, and if the criteria are not met, the assertion will fail, indicating a potential issue or error.

Here's a more detailed explanation of Assertions in JMeter:

* Response Validation
* Types of Assertions
* Configuration Options
* Scope
* Assertion Results
* Multiple Assertions
* Pre-Processing
Samplers – Sampler generates one or more sample results. These sample results have many attributes like elapsed time, data size, etc. It allows JMeter to send specific types of requests to the server, through samplers, thread group decides which type of request it need to make. Some of the useful samplers are HTTP request, FTP request, JDBC request etc.

Thread Groups – JMeter is the beginning part of thread group elements. It is an important element of JMeter, where you can set number of users and time to load all the users given in the thread group.
A JMeter thread by default will send requests continuously without any pause. Timers are used to get a pause between the request.

The different types of Timer in JMeter are :

Constant Timer : This element delays each request in a Thread Group for the same amount of time.
Gaussian Timer : This element is used to delay each user request for a random period of time.
Synchronizing Timer : This element is used to release number of threads at given point.
Uniform Random Timer : This element is used to delay each request for a random period of time.
Pattern-based regular expressions are used to find and manipulate text in Jmeter. JMeter uses the pattern matching software Apache Jakarta ORO to parse regular expressions or patterns used throughout a JMeter test plan.

We can save a lot of time and have more flexibility when creating or improving a Test Plan by using regular expressions. When it's impossible or very difficult to predict an outcome, regular expressions provide an easy way to acquire information from sites. Regular Expressions are used to dynamically extract values from responses. These values can be kept for reporting purposes or used in a subsequent request. Both Pre-Processors and Post-Processors make use of regular expressions.

The distinction between contains and matches, as used on the Response Assertion test element, is worth mentioning.

* The term “contains” indicates that at least some of the target was matched by the regular expression. Consider the string ‘alphabet’ and the regular expression ‘ph.b.’. Because the regular expression matches the substring 'phabe', we can say that 'alphabet' contains 'ph.b.'.

* The term "matches" refers to the regular expression matching the entire target. As a result, 'alphabet' and 'al.*t' are "matched."
In JMeter, there are two types of processors: the Pre-Processor and the Post-Processor.

Pre-Processors run before the main sampler and have the ability to change the scope of the sampler. PreProcessors are JMeter elements that are used to perform actions prior to the execution of sampler requests in a test scenario. PreProcessors can be used for a variety of performance testing tasks, such as retrieving data from a database, setting a timeout between sampler operations, or generating test data.

Post Processors run after the main sampler and apply to all samplers in the same Test Plan scope. They're useful for extracting fields from server responses and storing them in variables. The Post Processors are test plan elements that are used to do certain activities after a sampler request has been processed. These post processors are typically used to extract specific data from a sampling request's response, for example, we can extract the value of session variables from an HTTP request and send the value of the session variable to subsequent requests.
The execution order of the test plan elements is -

Configuration elements : The Configuration Element allows us to declare variables that Samplers can utilise to access data.

Pre-processors : PreProcessors are JMeter elements that are used to perform actions prior to the execution of sampler queries in a test scenario.

Timers : A JMeter Timer is an inbuilt JMeter plug-in that can assist you in timing out your sampler requests. Many testers refer to this pause in requests as "think time," as it simulates the time spent by real users between steps in a real-world scenario.

Samplers : JMeter uses samplers to make several types of queries to a server. JMeter provides genuine queries to the web server under test using samplers. Except for Test Action, each sampler delivers one or maybe more sample results.

Post-processors : After the sampler, a Post-Processor element is executed and can be used for the post-condition response. If a Preprocessor is included in a test plan, it will be run after the response has been received. A Post-Processor is frequently used to extract information from a response to a specific action.

Assertions : In JMeter, assertions are used to verify the response to a request that you have given to the server. The assertion is the process of comparing the expected and actual results of a request at runtime.
Listeners- A listener is a component that displays the sample results. The output can be displayed in the form of a tree, tables, graphs, or simply sent to a log file.
Data parameterization allows test scripts to be reused by removing the need for hardcoding values for the same request with varied parameters. In a single test script, parameterization is the process of establishing distinct datasets for different users. For instance, in the same script, executing numerous users with different credentials. As a result, it's one of the most important components of creating performance testing.

The data parameterization provided by JMeter is listed below :

* Config of a CSV Data Set : The CSV Data Set Config reads all values from a CSV file, stores them in variables, and uses them as Test Data during execution. The "CSV Data Set Config" allows you to save unique user data such as names, emails, and passwords in CSV files as an external data source. JMeter can read the CSV file line by line with the help of this config element, and then use split parameters to assign different values to separate threads.

* Variables that are defined by the user : User-defined variables (UDV) are used to define specific variables that can hold values that you need in several places. UserDefinedVariables differ from CSVDataSetConfig in that CSV can hold hundreds of thousands of values, whilst UDV is only suited for tiny data sets.

You can also specify variable/user values in UDV. This could be useful in instances where two users should use the same value and the next two users should use a different value. Also, if you declare a variable at the Test Plan/Thread Group level and then have the same variable with a different value inside one of two thread groups or a specific sampler. In this scenario, the local variable will override the global variable.
Parameterizing tests in JMeter involves dynamically changing certain values within the test plan to simulate different user inputs or scenarios. This is particularly useful for creating more realistic and versatile performance tests. There are several methods for parameterizing tests in JMeter:

* Using User Defined Variables :
* Define variables within the Test Plan or Thread Group using the User Defined Variables element.
* Reference these variables in other test elements by enclosing them in ${} syntax.

* Using CSV Data Set Config :

* Create a CSV file containing the parameter values.
* Configure the CSV Data Set Config element in the Test Plan to read data from the CSV file.
* Reference the variables read from the CSV file in other test elements using ${} syntax.

* Using Regular Expressions and Extractors :

* Use Regular Expression Extractor to extract dynamic values from server responses.
* Store the extracted values in variables.
* Reference these variables in subsequent requests to reuse the extracted values.

* Using Functions :

* Utilize built-in JMeter functions to generate or manipulate values dynamically.
* Functions can be used directly within test elements by enclosing them in ${__functionName(parameters)} syntax.

* Using Properties :

* Define properties either in the JMeter properties file or pass them via the command line.
* Reference properties in the test plan using ${__P(propertyName, defaultValue)} syntax.

* Using HTTP Request Defaults :

* Set default values for HTTP requests using the HTTP Request Defaults element.
* Override default values by referencing variables or properties in individual HTTP requests.

* Combining Methods :

* Combine multiple parameterization methods to achieve complex scenarios.
* For example, use CSV Data Set Config to vary user input data and Regular Expression Extractor to handle dynamic values in server responses.
In JMeter, a Controller is a test element used to organize and structure the test plan hierarchy. Controllers serve as containers for other test elements such as samplers, timers, assertions, and listeners. They provide a way to group related test elements together, define the flow of the test execution, and control the behavior of the test plan. Here's a more detailed explanation of what a Controller is in JMeter:

* Organizational Component : Controllers help organize and structure the test plan by grouping related test elements together. They provide a logical way to organize test scenarios, making it easier to manage and maintain complex test plans.

* Hierarchical Structure : Controllers have a hierarchical structure, allowing users to nest controllers within each other to create a tree-like structure. This hierarchical arrangement enables users to define the flow of the test execution and control the sequence in which test elements are executed.

* Types of Controllers : JMeter provides various types of controllers to cater to different testing scenarios and requirements. Some of the commonly used controllers include:

Simple Controller : A basic controller that groups test elements together without imposing any logic or behavior.
Loop Controller : Repeats the execution of its child test elements a specified number of times.
Transaction Controller : Measures the overall response time of its child test elements and treats them as a single transaction.
If Controller : Executes its child test elements based on a condition or expression.
Switch Controller : Selects and executes one of its child test elements based on a condition or switch value.

* Execution Control : Controllers allow users to control the flow and behavior of the test execution. Users can define the order in which test elements are executed, specify loop counts, set conditions for conditional execution, and more.

* Scope : Controllers can be added at different levels within the Test Plan hierarchy, including at the Test Plan level, Thread Group level, or individual Sampler level. This allows users to apply controllers globally or selectively to specific sections of the test plan.

* Pre-Processing and Post-Processing : Controllers can execute pre-processing and post-processing actions before and after the execution of their child test elements. This includes actions such as setting up variables, extracting data from responses, and cleaning up resources.
Performing parameterization using CSV files in JMeter involves using the CSV Data Set Config element to read data from a CSV file and inject it into your test plan.

Here's a step-by-step guide on how to do it :

* Prepare Your CSV File
* Add CSV Data Set Config Element
* Configure CSV Data Set Config
* Reference Variables in Test Elements
* Run Your Test
In JMeter, handling dynamic parameters in requests is crucial for accurately simulating real-world scenarios and ensuring the effectiveness of performance tests. Dynamic parameters typically refer to values that change with each request, such as session IDs, tokens, timestamps, or unique identifiers.

JMeter offers several mechanisms to handle dynamic parameters effectively:

* Regular Expression Extractor
* Boundary Extractor
* CSS/JQuery Extractor
* XPath Extractor
* JSON Extractor
* BeanShell PostProcessor or PreProcessor
* Correlation Recording
In JMeter, assertions are used to validate the response to a request that you have given to the server. The assertion is the process of comparing the expected and actual results of a request at runtime. If you want to apply assertion to a certain Sampler, make it a child of that Sampler.

By adding "Assertion Listener" to the Thread Group, you can see assertion outcomes. Other listeners will be able to see failed assertions as well.

Some common assertions in JMeter are :

* Response Assertion : Response Assertion is used for combining and comparing pattern strings against one or more server response values.

* Size Assertion : Size Assertion is used to check whether the server response includes the expected number of bytes.

* Duration Assertion : The Duration Assertion is used to check whether or not a server response is received within a defined time limit. If the response takes longer than the specified time, the sample request will be marked as unsuccessful.

* XML Assertion : XML Assertion is used to check whether the server response data contains a valid XML document.

* HTML Assertion : HTML Assertion is used to ensure that the response contains proper HTML syntax and that JTidy is not being used (HTML Syntax Checker). If the HTML syntax response is incorrect, the test will fail.
In JMeter, correlation refers to the process of dynamically extracting and replacing dynamic parameters in subsequent requests with values obtained from previous server responses. The purpose of correlation is to ensure that JMeter scripts accurately simulate real-world user interactions with the application being tested. Here's why correlation is important:

Maintaining Session State : Many web applications use session-based authentication mechanisms where a session ID or token is generated upon successful login and needs to be included in subsequent requests to maintain the user's session state. Correlation ensures that the session ID/token extracted from the login response is used in subsequent requests.

Handling Dynamic Parameters : Web applications often include dynamic parameters in responses, such as unique IDs, timestamps, or tokens. These parameters need to be captured and dynamically replaced in subsequent requests to ensure that the test accurately reflects real user behavior.

Ensuring Script Reusability : Correlation allows JMeter scripts to be reusable across multiple test runs. By dynamically extracting and replacing dynamic parameters, scripts can be reused without manual intervention, making test maintenance easier and more efficient.

Generating Realistic Load : Correlation ensures that JMeter accurately simulates the behavior of real users interacting with the application. Without correlation, requests may fail due to missing or incorrect parameters, leading to inaccurate load test results.

Improving Test Accuracy : Correlation improves the accuracy of test results by ensuring that each virtual user session is independent and consistent with real user sessions. This allows testers to identify performance issues and bottlenecks more effectively.
Debugging a JMeter script involves identifying and resolving issues or errors that may arise during test execution.

Here are several approaches to debug a JMeter script :

* Check Test Plan Configuration
* Verify Sampler Configuration
* Check Assertions and Response Data
* Enable Debug Sampler
* Use View Results Tree Listener
* Review Log Files
* Run Tests in Non-GUI Mode
* Use Debugging Tools
* Incremental Testing
* Consult Documentation and Community Resources
Many times while handling the tasks in Jmeter, the need for storing the test elements is felt. Workbench stores them all on a temporary basis. In addition to the testing elements, there are certain nontest elements that are also present in it. There is a browser in this tool that helps in configuring these elements simply. Keeping anything on the Workbench doesn’t actually mean it is stored in the memory permanently.
When it comes to testing the loading of an app, only a few users are considered then all for effectively studying the behavior of the app. This also derives a lot of useful information to know the overall performance of the app. Of course, it takes some time in making all the users in the running state. This time period is generally called the Ramp uptime. It is different from different apps depending on the overall number of users, data, and several other factors.
Spike testing is a very common approach in Jmeter. Actually, there are certain tasks that are associated with it. The prime task of the rendezvous point is to managing spike testing without creating any issue. Actually, the synchronizing timer is considered along with it to perform this task. You need to wait for the time till all the active users reach a value that is assigned during the load test.
A pre-processor is something that will happen before the sampler executes. To configure the sample request prior to its execution or to update variables that are not extracted from response text pre-processor elements are used.

Some of the pre-processor elements are :

* HTTP URL re-writing modifier
* HTTP user parameter modifier
* HTML link parser
* BeanShell PreProcessor
To reduce the resource requirements in JMeter

* Use non-GUI mode: jmeter –n –t test.jmx –l test.jtl
* During the load, a test doesn’t use “view results tree” or “view results in table” listeners, use them only during the scripting phase
* Don’t use functional mode
* Instead of using lots of similar samplers, use the same sampler in a loop and use the variable to vary the sample
36 .
What is the maximum number of threads that should be allowed on a single system?
It depends on your system's hardware setup, which includes a processor, JVM, and allotted memory -Xmx, among other things. The number of components in your test plan, such as the number of config items or processors, as well as whether you are using GUI or Non-GUI Mode, have an impact on thread count.
JMeter sends requests immediately, with no latency between samplers or requests. Your server will be overburdened if you perform load/stress testing immediately. Then it won't be able to provide you with realistic findings and won't be able to mimic real-world user traffic. JMeter Timers are the answer to all of these issues. To apply a wait between each sampler/request, a timer element can be added to a test plan.

Both Gaussian and Poisson Timers are based on a mathematical formula with a constant delay and offset.

* JMeter Gaussian Random Timer is used to produce and add a random delay before executing a sampler, as the name implies. Each user request is delayed for a random period of time using the Gaussian Random Timer element. Based on the Gaussian curve distribution, it has a random deviation around the Constant Delay Offset. The sum of the Gaussian distributed value (with mean 0.0 and standard deviation 1.0) times the deviation value you choose and the offset value is the delay (think) time.

* JMeter Poisson Random Timer is also used to produce and add a random delay before executing a sampler. The Poisson Distribution Function is used to create this timer. The total of the Poisson distributed value multiplied by the defined lambda value and the offset value is the delay (think) time.
The HTTP(s) Test Script Recorder records all of your application's HTTP(s) queries to the server. It will only collect HTTP(s) requests, as the name implies. You can also use this recorder's grouping feature to structure your requests so that comparable requests are kept together. As needed, add URL patterns to the include and exclude lists. In order for JMeter to work, some configurations must be done there.

The following are the steps to capture HTTPS traffic :

* HTTP(s) Test script recorder is to be added to WorkBench.
* To start the proxy server, type in the port number.
* Select "Workbench" as the target, or include a Recording Controller in the test plan and use the same target to save all recordings.
* The proxy server should now be running.
* Manually configure your browser's proxy settings to the same port number as the test script recorder.
Variables and functions are utilised in JMeter, just as they are in any other programming language, to make scripts reusable (since a function can be called again and again without having the need to write the same code again and again). Variables can be used to hold any value and then referenced anywhere in your code, just like any other programming language. So, with JMeter, it may be your server name, path, port number, or whatever else you want to save in a variable and utilise in multiple places afterwards.

JMeter has a number of built-in routines that can be used to test various situations. If you're accessing an application on your machine IP rather than an external URL, for example, you can use the machine IP function to get your IP address. JMeter's Function Dialogue may be found in the settings menu, where you can examine the definition and function string.

The syntax for calling a variable and function in your script is shown below :

Variable – {varName}.
Here, varName denotes the name of the variable.
Example – {name}

Function – {_functionName}.
Here, functionName denotes the name of the function.
Example – {_counter()}, {_threadNum} etc.
The Regular Expression Extractor in JMeter is a post-processor element used to extract dynamic values from server responses using regular expressions. It allows testers to capture specific patterns or text fragments from the response data and store them in JMeter variables for later use within the test plan. Here's an explanation of how the Regular Expression Extractor is used in JMeter:

1. Dynamic Value Extraction :  The main purpose of the Regular Expression Extractor is to extract dynamic values from server responses. These values could include session IDs, tokens, unique identifiers, timestamps, or any other piece of data that needs to be captured and reused in subsequent requests.

2. Configuration : To use the Regular Expression Extractor, you need to add it as a child element to the sampler whose response you want to extract values from.

In the Regular Expression Extractor configuration, you specify the following parameters :

* Reference Name : The name of the variable where the extracted value will be stored.
* Regular Expression : The regular expression pattern used to match and capture the desired value from the response.
* Template : A template string that defines how the matched value should be formatted before being stored in the variable.
* Match No. : Specifies which match of the regular expression should be used. Use "0" to indicate random match, "1" for the first match, "2" for the second match, and so on.
* Default Value : Optionally, you can specify a default value to use if no match is found.

3. Regular Expression Syntax :
* Regular expressions are patterns used to match and extract text from strings. Users need to be familiar with regular expression syntax to create effective extraction patterns.
* Regular expressions can be simple or complex, depending on the pattern of the text being searched for. They can include literal characters, metacharacters, character classes, quantifiers, and more.

4. Variable Usage :
* Once the Regular Expression Extractor is configured and executed, it extracts the value matching the specified regular expression pattern from the response.
* The extracted value is stored in the specified variable, which can then be referenced in subsequent requests or test elements using JMeter's variable syntax, ${variableName}.

5. Validation and Debugging :
* After configuring the Regular Expression Extractor, it's important to validate the extraction pattern by executing the test and verifying that the correct values are being extracted and stored in the variables.
* Debugging tools like the View Results Tree listener can be used to inspect sampler results and verify that the extraction process is working as expected.
A Test Fragment in JMeter is a reusable component that contains a set of test elements, such as samplers, controllers, assertions, or listeners, organized within a logical group. Test Fragments serve as building blocks for creating modular and reusable test plans in JMeter.

Here's a detailed explanation of what a Test Fragment is and how it is used :

* Reusable Component
* Organization
* Parameterization
* Scoping
* Reusable Logic
* Integration with Test Plans
Yes, JMeter can also record HTTP or HTTPS requests sent to the server through your mobile application. Mobile and JMeter must be connected to the same network.

The following is the needed configuration :

* In JMeter, set your proxy server to run on a specific port.
* Set up the proxy on your phone's wifi settings and use the same port number as the recorder.
* On your mobile device, install the Root CA certificate.
* From your mobile, send server requests and watch them get captured by the selected controller.
Yes, you can run Selenium scripts in JMeter in order to get an indication of how well they perform.

* It can be done in two ways. You can either utilise JUnit libraries to create Selenium scripts and save them as Jars, which you can then add to the JMeter directory. Then, in your test plan, add the JUnit sampler and import the Jar file.

* Or else, you can place the Webdriver sampler plugin in the JMeter ext folder. JMeter should be restarted. In the Webdriver sampler, write your Selenium code and then run it to observe how it performs.
In JMeter, sessions and cookies may be controlled via config components like HTTP Cache Manager, which allows you to clear cookies after each iteration and add user-defined cookies. The HTTP Cache Manager assists you in cleaning the cache after every iteration as needed in load tests, as well as limiting the number of objects that can be cached. The HTTP sampler can be configured with both of these config elements.
JMeter tests can be conducted in GUI or non-GUI modes. Because the AWT (Abstract Window Toolkit) event thread can kill the tests in high load conditions, it is highly advised to conduct the load test in Non-GUI mode. JMeter's GUI mode is ideal for adding and updating new configuration components, thread groups, and samplers, as well as viewing a variety of different listeners for troubleshooting.

The GUI option, on the other hand, has a constraint that slows down CPU consumption while running the recorded script. JMeter performance suffers when several listeners are used in a script. In order to avoid this, the script should be run in non-GUI mode. In non-GUI mode, there is a benefit to driving more requests per second out of JMeter.

JMeter supports a number of non-GUI modes, including :

* Command-line
* ANT plugin
* MAVEN plugin
* Jenkins
Spike Testing is a type of performance assessment that examines how the system behaves when the load is significantly increased on the system. Using the Synchronizing Timer in JMeter, you may perform spike testing. The threads are clogged by synchronising the timer until a certain number of threads are blocked, then releasing them all at once, resulting in a significant sudden load.

JMeter offers you two options to carry out spike testing :

Use the JMeter Ultimate Thread Group : This strategy will necessitate advance planning. Using the Ultimate Thread Group, the tester can perform many ramp-ups and ramp-downs in a single test. These could be gradual or more abrupt. For our purposes, you could introduce a spike during the test, for example, after 10 minutes of slow ramp-up and then stable load, ramp up to 10X in 10 seconds, then ramp down to the previous load level after 1 minute. The disadvantage of this method is that you won't be able to regulate concurrency during the test run. You won't be able to predict when the spike will occur.

Use JMeter Properties : This method will provide you with the most choice and flexibility. Determine how many threads you'll run at the start of the test, as well as when you'll want to create spikes dynamically. Use JMeter Properties for the number of threads, then use Real-Time Control to change the Properties while the test is executing.
In JMeter, controllers are used to regulating the flow of request execution. They allow you to specify the order in which requests are processed in a Thread. It allows you to choose "when" a user request is sent to a web server. They choose the sequence in which user requests are processed.

Some controllers used in JMeter are listed below :

* Recording controller :- JMeter has the ability to record your testing steps; a recording controller is a container for these recordings.

* IF controller : IF Controller decides whether or not to run a batch of child samplers based on particular criteria.

* While controller : The JMeter While Controller basically runs child Samplers and keeps running until the condition in the condition field becomes false.

* Transaction controller : The Transaction Controller in JMeter is a useful tool for organising and determining how different pieces of your test will appear in a report. The Transaction Controller creates a second sample that measures the total time it takes to complete the nested test items.

* Loop controller : The Loop Controller causes the user request to be repeated a given number of times or to be repeated indefinitely.

* Simple controller : Simple Controller is a container for user requests.

* Module controller : Module Controller's purpose is to make JMeter more modular. Web applications, in general, are made up of small functional units (e.g., login, create account, logoff...). This capability can be saved as "modules" in Simple Controller. The Module Controller will determine which module is required to run.

* Random Controller : In each loop period, the Random Controller causes all user requests to be processed in a random sequence.

* Interleave Controller : Interleave Controller takes one of the user requests and makes it run in each loop of the thread.
A certificate is required to authenticate HTTPS connections, which are established when the browser connects to the webserver. JMeter creates it for the purpose of intercepting SSL traffic and recording actions. This certificate must be installed on your mobile device in order to record actions via mobile. It is necessary to install the JMeter protected CA certificate in the browser before recording any secured web application with JMeter.

The HTTP(S) Test Script Recorder in JMeter can be used to record the protected online application. Certificates are used to authenticate the connection between the browser and the web server in secured (HTTPS) communications. The server presents the certificate to the browser when connecting through HTTPS. The browser verifies that the server certificate is signed by a Certificate Authority (CA) that is related to one of the browser's built-in root CAs. To intercept the HTTPS connection from the browser, JMeter must utilise its own certificate to enable encrypted connections. JMeter must effectively impersonate the target server.
It is dependent on the system's hardware.

On a 2-3 GHz CPU, for example, 400-600 threads can be produced. It also depends on the elements included in your test strategy.

The higher the number of processors and XML processing components, the higher the CPU burden and, as a result, the fewer threads. Load testing with multiple machines is recommended for large loads.
BeanShell is one of the most advanced JMeter built-in components. BeanShell is a lightweight Java scripting language that JMeter uses to do some sophisticated tasks. With the help of coding, the BeanShell sampler can execute a variety of tasks. You can get the thread number, run the current sampler, collect the cookies, and so forth. It comprehends Java syntax and provides scripting features such as loose types, commands and method closures. BeanShell can be a wonderful solution to achieve your goals if your test case is peculiar and creating it using embedded JMeter components is nearly impossible. BeanShell entities in JMeter include accessibility both to internal JMeter APIs as well as any external classes packed into the JMeter classpath (make sure to drop appropriate jars into your JMeter installation's /lib/ext folder and place the relevant "import" statements at the top of your BeanShell scripts).

The following BeanShell-enabled components are available in all JMeter versions :

* Beanshell Sampler : A sampler that can operate independently.
* Beanshell PreProcessor : A sampler pre-processor that operates before the sampler and can be used to establish prerequisites (i.e. to generate some input).
* Beanshell PostProcessor : A post-processor that runs after the sampler and can be used for cleanup or recovery.
* Beanshell Assertion : A powerful assertion that allows you to use the JMeter API completely. Java conditional logic can be used to control the outcome of the assertion.
* __Beanshell Function : A JMeter function that permits custom BeanShell code to be executed while the sampler is running.