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What is Salesforce Testing?

Salesforce testing primarily concerns testing your Salesforce deployments to affirm their functionality as required. Salesforce testing is validation testing by a tester to check codes in developed applications with built-in salesforce functionality. It is mainly the customization of codes performed with vanilla SDFC and done primarily to test codes developed by developers.

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Key Highlights

Salesforce testing tests and customizes applications to provide quality and error-free applications.

Its types include End-to-End, Regression, Load & performance, and manual and automated testing.

Some famous tools are Selenium, testRigor, Tricentis, and Panaya Foresight.

Coordination, clear communication, and role-based testing are important roles of testers.

Why is it Important?

It is essential for reducing development costs and application development in a short time.

It helps to verify the problems and fix them quickly by providing easy functional flow creation to the team.

It allows the organization to limit physical servers of web applications and storage issues.

It helps to customize the application codes, and customer needs as per requirement. As a result, it is the most relevant method and tool for validating customized features in built-in applications.

Furthermore, it helps to enable quality in the finished product by identifying the bugs and risks at the initial stages.

Types #1 Manual testing

The manual testing process includes testing through the chúng tôi application through traditional methods.

The QA team uses manual functional testing like happy path tests, integration tests, and system and regression tests.

#2 Automated testing

Automated testing includes using a computer testing program for testing in chúng tôi or chúng tôi applications.

#3 End-to-end testing

Administrators prebuilt test cases and situations with limited technical experience in this testing.

It is time-consuming but provides a quick workout of an exhaustive process.

This testing includes visual testing to track user experiences.

#4 Regression testing

Through this testing, developers and testers identify the need for new or existing changes in the codes of applications.

The difference can be either small or large and completed after changes are made to any code of an application.

#5 Load and performance testing

Testers use this testing to leverage automation tools in the sandbox environment.

It is done to confirm the performance of the salesforce in serving users by monitoring inputs, workflows, and queries.

Top Testing Tools 1. Selenium

Selenium Contains different tools and libraries to support browser automation.

It is an open-source umbrella project that helps authoritarian functional tests all over modern websites.

2. TestRigor

TestRigor provides effortless solutions for testing using simple English commands.

It is supported in Web, all browsers, mobile, iOS, and OS systems.

3. Tricentis

Tricentis provides fast and relevant UI testing facilities for salesforce applications.

Tricentis contain self-healing and improving locators to stabilize tests and reduce maintenance costs. End-to-end extensions of scenarios from web applications are also available.

4. Panaya Foresight

Panaya Foresight is a salesforce testing tool that controls an organization’s salesforce through risks and impacts identification.

It enables 85% bug reduction in the production process and risk-based testing.

Increasing Demand for Salesforce Testing

Every enterprise nowadays needs automation as a mandatory process to solve critical production issues.

It is expected to provide easy solutions to functional flow creation with the visual and no-code approach in teams of organizations.

According to the World Quality Report 2023-2023, the need for quality assurance in the future will accelerate. Thus, the need for manual and automated testing will grow.

Important Roles of Salesforce Testing

Clear communication among testers and developers is essential in salesforce testing.

Coordination among testers and business as per required document for salesforce needs efforts.

Role-based testing by testers to ensure consistent data testing is an essential role.

Furthermore, compatibility testing in third-party applications is an important role that testers must be familiar with.

Familiarity with application flows and performing tests per salesforce standard rules is also necessary.

The tester needs to understand the customizable features that can help develop the salesforce application.

Boundary value analysis and Equivalence partitioning are essential roles for a tester.

Related Jobs a. Salesforce Developer

Responsibilities include a timeline and goal creation. Also, need to test the stability and functioning of the application.

A Salesforce Developer (fresher) salary starts from $62k to $124k per annum.

b. QA Analyst

They are responsible for identifying flaws and errors in a program.

Full functionality and free-from-bug applications are the primary goals of QA Analysts.

The basic salary for QA Analyst starts from $42k to $83k.

c. ETL Testers

The job responsibility includes transformation logic, validating data sources, and uploading data in target areas.

The salary of an ETL Tester averages up to $95k per annum.

Essential Tips for Salesforce Testing

In salesforce testing, test data needs to be validated before reporting functionality.

Automation testing should be done using Selenium and HP functional testing tools.

It must include UI testing, Regression, system, and functional testing methods.

Testers must know their roles and positive & negative functional flows in applications.

Loading of web pages simultaneously while testing should be avoided.

Tests should be run as real profile users rather than testers and developers.

Benefits of Salesforce Testing

Salesforce testing provides reliable software development.

It improves the quality of end products.

It helps to reduce business risks.

It can provide quick execution and test coverage.

It also reduces the development and maintenance costs of organizations.

Optimization of the test process is available.

Reduce data leakage and security issues.

Increases customer relationships and confidence.

Salesforce administration can develop internal users in salesforce platforms.

Developers can easily reuse existing applications from App Exchange to customize their applications.


Salesforce is the first cloud-based Customer Relationship Management. It is used to validate and customize applications per requirements and bug detections. Salesforce testing contains challenges of testing the customization without testing the SDFC features. Selenium, UFT, and other crucial salesforce tools for testing.

FAQs Q1. How to carry out salesforce testing?

Answer: To test, as a tester, you must do functional testing to check bugs. Then check for the smooth running of the development with existing features. Salesforce UAT testing is the next phase, where the real-world business case should be used for functionality checking.

Q2. Is Salesforce testing in demand? Q3. What is required for Salesforce testing?

Answer: For performing Salesforce testing, a tester must include functional testing, system testing, UI testing, regression testing, and system integration testing. Tools such as Selenium and HP Unified Functional Testing (UFT) can be used for automation testing.

Q4. Is coding required for Salesforce testing?

Answer: Salesforce, a low or no-code app development organization, doesn’t need a salesforce developer with a background in coding. This is why it can be a perfect choice for an IT aspirant without a coding background.

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Automation Testing Tutorial For Beginners (Process, Benefits, Tools)

What is Automation Testing and How Does It Work?

Automation Testing, often known as Test Automation, is a software testing approach that involves the execution of a test case collection using particular automated testing software tools. On the other hand, manual testing is carried out by a person sitting in front of a computer, methodically carrying out the test processes.

In addition to entering test data into the System Under Test, the automated testing software may analyze predicted and actual outcomes and provide complete test reports. Software Test Automation necessitates significant financial and human resources.

Continuous implementation of the same test suite will be required in subsequent development cycles. This test suite may be recorded and replayed as needed using a test automation tool. There is no need for human interaction after the test suite has been automated. Test Automation’s return on investment has increased as a result of this. The purpose of automation is to minimize the number of test cases that must be done by humans, not to completely remove human testing.

In this automated software testing course, you’ll master the fundamentals of test automation, including −

What are Automation Testing and How Does It Work?

What Are the Benefits of Automated Testing?

What Test Cases Should Be Automated?

Method of Automated Testing

Choosing a test tool

Describe the automation’s scope.

Planning, Design, and Development are all important aspects of any project.

Implementation of the Test

The Automation Framework

Best Practices for Automation Tools

Advantages of Automated Testing

Automated Testing Types

What Should You Look for in an Automation Tool?

Automated Testing Software

What are the benefits of test automation?

Test automation is the most effective technique to improve software testing effectiveness, test coverage, and execution speed. The importance of automated software testing may be summed up as follows −

Manual testing takes time and money to test all procedures, fields, and bad cases.

Manually testing for multilingual sites is challenging.

In software testing, test automation eliminates the need for human interaction. Unattended automated testing is possible (overnight)

Test automation accelerates the execution of tests.

Increased Test Coverage is aided by automation.

Manual testing may become tedious and, as a result, prone to errors.

What Test Cases Should Be Automated?

To maximize the automation ROI, test cases to be automated might be chosen based on the criteria below.

High-risk – critical-to-business test scenarios

Test scenarios that are run on a regular basis

Manually doing test cases that are time consuming or challenging

Test Cases that take a long time to complete

Test cases in the following categories are not appropriate for automation −

Newly developed test cases that have not been personally performed at least once

Test cases in which the requirements change regularly

Test cases that are run on an as-needed basis.

Process of Automated Testing

In an Automation Process, the stages are as follows −

Step 1 − Choose a test tool

Step 2 − Define the Automation Scope

Step 3 − Design, Planning, and Development

Step 4 − Execution of the Test

Step 5 − Maintenance

Choosing a test tool

The technology that the Application under Test is based on has a big impact on the Test Tool you choose. QTP, for example, does not support Informatica. As a result, QTP will not be able to test Informatica apps. Conducting a Proof of Concept of Tool on AUT is an excellent idea.

Define the automation’s scope

The area of your Application Under Test that will be automated is referred to as the scope of automation. The following factors aid in determining scope −

The elements that are critical to the company’s success

Scenarios with a significant quantity of data

Functionalities that are shared across apps

Possibility from a technical standpoint

The percentage of business components that are reused

The difficulty of the test cases

Cross-browser testing using the same test scenarios is possible.

Planning, Design, and Development are all important aspects of any project.

You establish an Automation strategy and plan at this phase, which includes the following details −

Tools for automation have been chosen.

The design of the framework and its characteristics

Automation things that are both in-scope and out-of-scope

Preparation of an automation testbed

Scripting and execution schedules and timelines

Automation Testing Deliverables

Execution of the Test

Automation During this phase, scripts are run. Before they may be configured to run, the scripts need input test data. They generate extensive test results after they’ve been run.

The automation tool may be used directly or via the Test Management tool, which will launch the automation tool.

For instance, Quality Center is a Test Management solution that, in turn, invokes QTP to run automation scripts. Scripts may run on a single system or across several machines. To save time, the execution might be carried out at night.

Maintenance Methodology for Test Automation

The Test Automation Maintenance Approach is a step of automation testing that is used to see whether the new features introduced to the program are operating properly. When new automation scripts are introduced, they must be evaluated and maintained in order to enhance the efficacy of automation scripts with each release cycle.

The Automation Framework

A framework is a collection of automation principles that aid in the automation process.

Maintaining Testing Consistency

Enhances the structure of tests

Code use is kept to a minimum.

Code maintenance is reduced.

Reusability should be improved.

Involvement of non-technical testers in coding is possible.

The time it takes to learn how to use the instrument may be cut in half.

Uses data when it’s appropriate

In automated software testing, there are four kinds of frameworks −

Framework for Data-Driven Automation

Framework for Keyword-Driven Automation

Framework for Modular Automation

Framework for Hybrid Automation

Best Practices for Automation Tools

Keep the following in mind if you want to get the most out of automation.

Prior to the commencement of the project, the scope of Automation must be specified in detail. This is a good way to establish expectations for Automation.

Choose the correct automation tool: A tool should not be chosen primarily on its popularity, but rather on its ability to meet the automation needs.

Select a suitable framework.

Scripting Standards – When creating automation scripts, standards must be event of a system failure or unexpected application behavior.

For Error Logging, user-defined messages should be codified or standardized so that testers can interpret them.

Measure metrics – The success of automation cannot be judged just by comparing the manual and automated efforts, but rather by collecting the data listed below.

Percentage of faults discovered

The amount of time necessary for each release cycle’s automated testing.

Release takes the least amount of time possible.

Customer Satisfaction Index (CSI) is a measure of how satisfied customers are with

Enhancement of productivity

If you follow the above recommendations, your automation will be a huge will assist you in choosing the right tool for your needs −

Support for the Environment


Database Validation

Object recognition

Image Evaluation

Testing for Error Recovery

Mapping of Objects

Used Scripting Language

Support for a variety of test kinds, such as functional, test management, mobile, and so on…

Multiple testing frameworks are supported

The automation software scripts are simple to debug.

The ability to distinguish items in a variety of settings.

Test reports and findings that are extensive

Reduce the cost of training for chosen tools.

One of the most difficult difficulties to overcome before automating is tool selection. Identify the needs first, then investigate potential tools and their capabilities, create expectations for the tool, then do a Proof Of Concept.

Automated Testing Software

On the market, there are a plethora of Functional and Regression Testing Tools. Here are the greatest test automation solutions that our experts have recommended.

1. Ranorex Studio

Ranorex Studio, an all-in-one test automation solution, is used by over 14,000 people across the globe to speed up testing. For novices, Ranorex open APIs for automation specialists.


End-to-end testing and functional UI on PC, web, and mobile

Cross-browser testing is a method of determining how well a website works

SAP, ERP, Delphi, and legacy systems are just a few examples.

Apple’s iOS and Google’s Android

Run tests in parallel on actual or virtual computers, locally or remotely.

Playback of the test execution on video

Reporting capabilities built-in

For a full testing toolchain, Ranorex connects with top technologies like as Jira, Git, Azure DevOps, Jenkins, Bamboo, Bugzilla, SpecFlow, NeoLoad, TestRail, and more.


The Kobiton mobile device testing platform supports both scripted and script less test automation. Users may develop manual tests that are automatically re-run on a range of real-world devices. Kobiton fully supports test automation frameworks like Appium, Espresso, and XCTest, as well as providing its own scriptless test automation using NOVA AI.


Kobiton’s device lab management allows you to connect to cloudbased devices, on-premises devices, and on-desk devices.

Manual test sessions may be converted into scripts that can be run on many devices, allowing users to generate test scripts automatically.

When a test fails, easily link your defect management system to immediately record tickets with debug sessions attached.

Appium Anywhere technology from Kobiton guarantees fewer flaky test scripts by ensuring that your test executes the same on all devices.

Kobiton’s scriptless test automation provides open-source Appium code that may be used in a variety of ways.


ZAPTEST is a Software Automation solution for any company that utilizes software for operations or development and wants to automate back-office operations or software testing procedures while also developing a revolving automation framework.


Automated Functional and Performance Testing

RPA stands for Robotic Process Automation (Robotic Process Automation)

RPA Software Automation + Seamless Testing

Execution on Multiple Platforms (Parallel)

Automated DevOps (Mock-ups)

API Evaluation



LambdaTest is a popular tool for doing automated cross-browser testing. They provide a selenium grid that is ultra-fast, scalable, and secure, allowing customers to conduct tests on over 2000 browsers and operating systems. It works with all modern and older browsers.


Test execution is quick and flawless thanks to the newest tech stack

To reduce test cycles, parallel test execution is used.

Simple connection with CI/CD, project management, and team communication systems.

Users may test their geo location as well as their locally hosted website.

Users may use a variety of APIs to get all of the information they need.

All major languages and frameworks are supported.


Test Automation is a software testing approach that executes a test case set utilizing particular automated testing software tools.

Test automation is the most efficient technique to improve software testing productivity, test coverage, and computational efficiency.

The technology that the Application under Test is based on has a big impact on the Test Tool you choose. Maintenance of Test Automation Approach is a kind of automated testing that is used to see whether the new features introduced to the program are operating properly.

For automation to be effective, the correct automation technology, testing procedure, and team must all be in place. For effective testing, manual and automated approaches should be used together.

Definition, Benefits Of Full Disclosure

Intersegment Sales

Revenue generated by means of an exchange between segments that belong to the same business

Written by

CFI Team

Published December 26, 2023

Updated June 28, 2023

What are Intersegment Sales?

Intersegment sales refer to revenue generated by means of a transaction between segments within the same business. It is generally the case with large conglomerates that engage in several lines of business. Such companies manage segments that have interconnect operations either vertically or horizontally.

Companies are required to disclose all intersegment sales under a specific heading, usually referred to as “Intersegment Reporting,” or “Intersegment Sales,” in the notes to the financial statements in their annual reports. Several accounting standards boards around the world require companies to disclose such sales in order to provide full disclosure or an accurate picture of the business’ financial health.


Revenue generated from transactions between two segments that belong to the same business is known as intersegment sales. 

Companies are required to disclose all intersegment sales under a specific heading in the notes to the financial statements.

Intersegment sales and segment sales reporting are related, but are composed of different amounts and are reported differently in the audit report.

Intersegment Sales vs. Segment Reporting

When a company operates a business with multiple branches of operations, and each branch, or segment, generates revenue independently through its operations, the individual revenue results are recorded under the “segment reporting” section in the company’s annual report. If that same company generates revenue by means of sales between segments, those amounts are reported in the notes to the financial statements in a section normally called intersegmental sales revenue.

Companies generally divide their operations into different geographical segments, or different operative or functional segments, and so on. The key difference between the two terms basically relates to the nature of the transactions and how they are disclosed. For example, when a company is operating three segments, such that, segment A deals in raw materials for the production of product A, which the company exclusively sells under segment B,  and provides services on the product under Segment C.

In such a case, when the company is transacting between segment A and segment B for the production of product A, it is engaging in intersegment sales, as segment A is booking revenue by selling to segment B.

On the other hand, when multinational companies are divergent in their operations and generate revenue through different operational segments, and not internally but externally by making sales in the market, it will fall under segment reporting.

Benefits of Disclosing Intersegment Sales 1. Provides an accurate financial picture

When a company discloses its intersegment sales, it provides an accurate financial picture of its sales and operations through its annual reports.

2. Helps navigate internal operations

Diligently reporting intersegment sales helps in the smooth navigation of the company’s internal operations. The practice gives an accurate financial, as well as operational picture, of the interdependency of the operating segments of the company – and eventually helps in efficient planning and management.

3. Helps in sales/revenue planning

Full and precise disclosure of intersegment sales accurately segregates the revenue that the company is generating externally and internally. It helps in knowing how much revenue comes from where – which essentially helps the management in making financial and operational decisions.

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Definition, Types, Precedence And Examples

What are Operators in C?

The C programming language utilizes operators as symbols representing precise operations to be executed on one or more operands. C provides a wide range of operators that can perform arithmetic, logical, and bitwise operations and operations on pointers and arrays. Operators are symbols that help in performing functions of mathematical and logical nature. The classification of C operators is as follows:








Even though there are many operators, the execution of these operations happens based on the precedence given to them. Precedence is the order in which the compiler executes the code comprising numerous operators.

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Explanation of Operators in C

Below is a detailed explanation of operators in C:

#1 Arithmetic Operators

These operators are responsible for performing arithmetic or mathematical operations like addition (+), subtraction (-), multiplication (*), division (/), the remainder of the division (%), increment (++), and decrement (–).

There are two types of arithmetic operators:

Unary Operators: This type of operator works with a single value (operand) like ++ and –.

Binary Operators: This type of operator works with two operands like +,-,*,/

Here is a tabular form of the number of arithmetic operators in C with the functions they perform.

Operator Function

+ Adds two values

– Subtract a second value from the first.

* Multiply two values

/ Divide numerator by the denominator

% Remainder of division

++ Increment operator – increases integer value by one.

— Decrement operator – decreases integer value by one

int main() { int a = 12, b = 6, c; c = a + b; printf(“a+b = %d n”, c); c = a – b; printf(“a-b = %d n”, c); c = a *b; printf(“a*b = %d n”, c); c = a / b; printf(“a/b = %d n”, c); c = a % b; printf(“Remainder when a divided by b = %d n”, c); return 0; }


#2 Relational Operators

The below table lists the relational operators in C with their functions.

Operator Function Example

== It will check if the two operands are equal 6 == 2 returns 0

!= It will check if the two operands are not equal. 6 != 2 returns 1

> It will check if the operand on the left is greater than the operand on the right

< It will check if the operand on the left is smaller than the right operand 6 < 2 returns 0

>= It will check if the left operand is greater than or equal to the right operand

<= It will check if the operand on the left is smaller than or equal to the right operand 6 <= 2 return 0

Example: C Program using relational operators

int main() { int a = 7, b = 7, c = 10; printf(“%d == %d = %d n”, a, b, a == b); printf(“%d == %d = %d n”, a, c, a == c); printf(“%d < %d = %d n”, a, b, a < b); printf(“%d < %d = %d n”, a, c, a < c); printf(“%d != %d = %d n”, a, b, a != b); printf(“%d != %d = %d n”, a, c, a != c); printf(“%d <= %d = %d n”, a, b, a <= b); printf(“%d <= %d = %d n”, a, c, a <= c); return 0; }


#3 Logical Operators

Logical Operators are to get True or False results.

The table below lists the logical operators used in C

Operator Function Example (if a=1 and b=0)

&& Logical AND (a && b) is false

|| Logical OR

! Logical NOT (!a) is false

Example: C Program using logical operators.

int main() { int a = 8, b = 8, c = 12, result; result = (a == b) && (c < b); printf(“(a == b) && (c < b) equals to %d n”, result); result = !(a != b); printf(“!(a == b) equals to %d n”, result); result = !(a == b); printf(“!(a == b) equals to %d n”, result); return 0; }


#4 Bitwise Operators

These operators are for bit-level operations on the operands. The operators first convert into bit-level and then perform the calculations.

Operator Function

& Bitwise AND

| Bitwise OR

^ Bitwise exclusive OR

~ Bitwise complement

<< Shift left

>> Shift right

Example: C program for Bitwise AND

int main() { int a = 10, b = 8; printf(“Output = %d”, a&b); return 0; }



00001010 & 00001000 = 00001000 = 8 (In decimal)

#5 Assignment Operators

These types of operators help us assign a value to a variable.

Operator Function Example

= It will assign values from right-side operands to left-side operands a=b

+= It will add the right operand to the left operand and assign the result to left a+=b is the same as a=a+b

-= It will subtract the right operand from the left operand and assign the result to the left operand a-=b is the same as a=a-b

*= It will multiply the left operand with the right operand and assign the result to the left operand a*=b is the same as a=a*b

/= It will divide the left operand with the right operand and assign the result to the left operand a/=b is the same as a=a/b

%= It will calculate the modulus using two operands and assign the result to the left operand a%=b is the same as a=a%b

#6 Conditional Operators

Also, known as Ternary Operator or? : Operator, these operators are useful for decision-making.


Expression 1? Expression 2: Expression 3 #7 Special Operators

Here are some special operators used in C

Operator Function

& This operator is used to get the address of the variable.

Example: &a will give an address of a.

* This operator works as a pointer to a variable.

Example: * a where * is a pointer to the variable a.

size of () This operator gives the size of the variable.

Example: The size of (char) will give us 1.

Example: C program using a special operator

int main() { int *ptr, q; q = 40; /* It assigns the address of q to ptr */ ptr = &q; /* display q’s value using ptr variable */ printf(“%d”, *ptr); return 0; }


C Operators Precedence

Generally, arithmetic, logical, and relational operators are used while coding in C. The precedence for these operators in arithmetic is greater than logical and relational. Note that all the operators in arithmetic also follow a different order of precedence. Let’s check which operators hold the highest precedence.

Order of Precedence in Arithmetic Operators

The increment and decrement (+ + and – -) operators hold the highest precedence in arithmetic operators. After that next precedence is for the unary minus ( – ) operator; next, three operators, /, *, and %, have equal precedence. The lowest precedence is for the operators like addition ( + ) and subtraction ( – ). In case of equal priority, the compiler takes charge while evaluating them. Remember the C operator associativity rule for all operators with the same precedence. Then the execution happens from left to right.

For example,

int main() { int a = 15, b = 20, c = 32, result; result = a * b – ++c; printf(“The result is: %d”, result); return 0; }


Explanation: Here, in the given equation, first, “++” executes; hence the value of c will be 33. Next, “* “holds the highest precedence after “++.” Hence after the execution of “a * b,” the result will be 300. Then the execution of “-” happens and results in 267.

Order of Precedence in Relational/Logical Operators

For example,

Output: False

Misc Operators in C

The Misc operators or miscellaneous operators are conditional operators that include three operands. In these 3, the execution of the first operand happens first. Then the execution of the second operand, if it is non-zero, or a third operand executes to provide the necessary Output. Besides the operators discussed above, C programming language supports a few other special operators like sizeof and “?:”.

Operator Description Example

sizeof() Finds the size of a variable sizeof(b), if b is an integer, then the Output will be 4.

?: Conditional operator Condition? X: Y; here, if the condition is true, the result will be X, else Y.

& Address of a variable &a returns the actual address

* Pointer *a

Time and Space Complexity

Time and space complexity are the terms concerning the execution of an algorithm. The Time complexity is the time taken to run the algorithm as a function of the input. Space complexity is the space or memory the algorithm takes as an input function. These two terms depend on many terms like processor, operating system, etc.

Final Thoughts

C operators are the symbols used to perform relational, mathematical, bitwise, or logical operations. C language includes a lot of operators to perform various tasks as necessary in the program. Different kinds of operators are arithmetic, logical, and relational.

Frequently Asked Questions (FAQS)

Q1. What are the boolean operators in C?

Q2. What does ** mean in C?

Answer: The “**” in C is a double-pointer or pointer-to-pointer. Where * is a pointer that holds the address of the variable. ** mean the address of a variable already holding an address of a different variable.

Q3. What is the difference between prefix and postfix operators in C?

Answer: Prefix and postfix are the operators written before and after the operands. These operators are the increment (+ +) and decrement (- -) operators. For example, “++c” is the prefix operator, and “c++” is the postfix operator.

Q4. What is the Modulus operator?

Answer: The modulus operator is the arithmetic operator of C, and it works between two operands. The division of the numerator value by the denominator results in the remainder. In simpler words, the produced rest for the integer division is the modulus operator.

Q5. Does C language support operator overloading?

Answer: Operator overloading is a method of polymorphism where the programmer makes specific changes in the existing code without changing its meaning. Operator overloading is possible only in C++. Since polymorphism is possible only in an object-oriented language, C doesn’t support operator overloading.

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This EDUCBA guide to C Operators discusses the operators used in C language with their syntax and examples. EDUCBA also suggests the following articles to learn more.

Common Data Capturing Types And Tools


We saw the Data Science spectrum in the previous article, Common terminologies used in Machine Learning and Artificial Intelligence, but what do we need in order to enable each stage? That’s where tools and languages come into the picture.

But before that, we need to understand another aspect that comes prior to the spectrum, before your team starts exploring the data and building models, you should define and build a data engine. You need to ask questions like Where is the data being generated? How big is the data, Which tools are required for collecting and storing it? etc.

Note: If you are more interested in learning concepts in an Audio-Visual format, We have this entire article explained in the video below. If not, you may continue reading.

In this article, we’ll focus on the storage side of things. I want to point out here that you don’t need to memorize the tools that you’re going to see but should be aware of what’s out there to answer the questions we asked earlier. And here is the Data Science Spectrum-

The Three V’s of Big Data

We need to understand the characteristics of the data, and we can divide this into three V’s- Volume, Variety, and Velocity. We’ll understand each of these in a bit more detail and cover some of the commonly used tools for each type as well.

The Three V’s- Volume

Let’s look at the first V, Volume.

Volume refers to the scale and amount of data at hand.

Recall that 90% of the data we see in the world today was generated in the last few years. But we’re decreasing storage and computational costs so collecting and storing huge amounts of data has become far easier. I’m sure all of you must have heard the term Big Data. Well, the volume of data defines if it qualifies as “big data” or not. When we have relatively small amounts of Data Lake, say, 1, 5, or 10 GB, we don’t really need a big data tool to handle this. Traditional tools tend to work well on this amount of data.

When the data size increases significantly to 25 GB or 50 GB, this is the point when you should start considering big data tools.

But when the size of the data exceeds, even at this point, you most definitely do need to implement big data solutions. Traditional tools are not capable of handling 500 GB or 1TB of data, no matter how much we might want them to.

So what are some other tools that can handle these different data sizes? Well, let’s look at them.

Tools for handling data of different sizes-

So Excel easily, the most popular and recognizable tool in the industry for handling small datasets. But the maximum number of rows it supports per sheet is 1 million. And one sheet can only handle up to 16,380 columns that are at a time. This is simply not enough when the amount of data is big.

Access is another Microsoft tool. Popularly used for data storage. Again, smaller databases up to 2 GB can be stored, but beyond that, simply not possible for Microsoft Access.

SQL is a database management system that has been around since the 1970s. It was a primary database solution for quite a few decades. It’s still popular, but other solutions have emerged. SQL’s main drawback is that it’s very difficult to scale as your database continues to grow.

I’m sure you must have heard of Hadoop. It’s an open-source distributed processing framework that manages data processing and storage for big data. You will more than likely come across Hadoop anytime you build a machine learning project from scratch.

Apache hive is a data warehouse built on top of Hadoop. Hive provides a SQL-like interface to query data, storing various databases in file systems that integrate with Hadoop.

The Three V’s- Variety

The second V we have is Variety, which refers to their different types of data. This can include structured and unstructured data. Under the structured data umbrella, we can classify things like tabular data, employee tables, payout tables, loan application tables, and so on and so forth.

As you might’ve gathered, there’s a certain structure to these data types. But when we swing over to unstructured data, we see formats like emails, social media, which includes your Facebook posts, tweets, etc, customer feedback, video feeds, satellite image feeds among other things.

The data stored in these formats do not follow a trend or pattern. It’s huge and diverse and can be quite challenging to deal with.

So what tools are available in the market for handling and storing these different data types? The two most common databases out there are SQL and NO-SQL( Not Only-SQL).

SQL is the market-dominant player for a number of years before NO-SQL emerged. Some examples of SQL databases include MySQL, Oracle SQL, whereas NO-SQL includes popular databases like MongoDB, Cassandra, etc. These NO-SQL databases are seeing huge adoption numbers because of their ability to scale and handle dynamic data, something that SQL struggles with.

The Three V’s- Velocity

The third and final V is Velocity. This is the speed at which data is captured. This includes both real-time and non-real-time capture. But in this article, we’ll focus more on real-time data. This includes Sensor data, which is captured by self-driving cars and CCTV cameras among other things. Self-driving cars need to process data really quickly when they’re on the road. And CCTV cameras of course are popularly used for security purposes and need to capture data points all day long.

Stock Reading is another example of real-time data. Actually, did you know that more than 1TB of trade information is generated during each trade session at the New York stock exchange? That’s the size of real-time data we talking about here, 1TB during each trade session.

Of course, Detecting fraud and Credit card transactions also fall into real-time data processing. And Social media posts and tweets are prime examples for explaining what real-time data looks like. In fact, it takes less than two days for 1 billion tweets to be sent. This is exactly where data storage has become so important in today’s world.

Now let’s look at some of the common tools that captured real-time data for processing.

it’s fault-tolerant 

really quick

and it’s used in production by a lot of organizations

Another one is Apache Storm. It can be used with almost any programming language. A storm can process over 1 million tuples per second and is highly scalable. It’s a good option to consider for high data velocity.

So that was all about the types of data in a few widely used tools associated with them.

End Notes

In this article, we saw some common data capturing types and tools associated with them. We learned about the three V’s of Big Data and also learned about various tools required for handling data with different sizes, different types such as structured or unstructured,d and for real-time data.

If you are looking to kick start your Data Science Journey and want every topic under one roof, your search stops here. Check out Analytics Vidhya’s Certified AI & ML BlackBelt Plus Program


Boosting In Machine Learning: Definition, Functions, Types, And Features

This article was published as a part of the Data Science Blogathon.


Boosting is a key topic in machine learning. Numerous analysts are perplexed by the meaning of this phrase. As a result, in this article, we are going to define and explain Machine Learning boosting. With the help of “boosting,” machine learning models are able to enhance the accuracy of their predictions. Let’s take a closer look at this approach:

What is Boosting in Machine Learning?

Before delving into the topic of ‘Machine Learning boosting,’ it is necessary to explore the term’s meaning. Boosting is defined as ‘encouraging or assisting something in improving.’ Machine learning augmentation does the same objective by empowering machine learning models and increasing their accuracy. As a result, it is a widely used algorithm in data science.


In machine learning, boosting refers to the methods that transform weak learning models into strong ones. Assume we need to categorize emails as ‘Spam’ or ‘Not Spam’. To make these differences, we can apply the following approach:

If an email has only one picture file, it is spam (because the image is usually promotional)

If the email begins with the line ‘You have won the lottery,’ it is spam.

If an email has only a collection of links, it is spam.

If the email originates from a source in our contact list, it is not spam.

Now, while we have categorization criteria in place, do you believe they are powerful enough on their own to determine if an email is a scam or not? That is not the case. On their own, these principles are insufficient to categorize an email as ‘Not Spam’ or ‘Spam.’ We’ll need to strengthen them, which we may achieve by adopting a weighted average or by taking into account the forecast of the higher vote.

Thus, in this situation, we have five classifiers, three of which classify the email as ‘Spam.’ As this class has a greater vote total than the ‘Not Spam’ category, we will consider an email to be ‘Spam’ by default.

This example was intended to demonstrate the concept of boosting techniques. They are more intricate than that.

How do they work?

As seen in the preceding example, boosting combines weak learners to generate rigorous rules. Therefore, how would you recognize these flaws in the rules? To discover an unknown rule, instance-based learning techniques must be used. Whenever a base learning method is used, a weak prediction rule is generated. You’ll repeat this procedure numerous times, and the boosting algorithm will merge the weak rules into a strong rule with each iteration.

Each iteration of the boosting algorithm finds the best possible distribution. It will begin by distributing the allocations equally across several categories. Observations will be given more weight if the first learning process makes a mistake. After allocating weight, we go on to the next step.

In this stage, we’ll continue the procedure till our algorithm’s accuracy improves. The output of the weak learners will then be combined to produce a strong one, which will strengthen our model and enable it to make more accurate predictions. A boosting algorithm focuses on the assumptions that result in excessive mistakes as a result of their insufficient regulations.

Different Kinds of Boosting Algorithms

Boosting algorithms may be implemented using a variety of different types of underlying engines, such as margin maximizers, decision stamps, and others. There are three primary types of Machine Learning augmentation algorithms:

Adaptive Boosting (also known as AdaBoosta)

Gradient Boosting


The first two, AdaBoost and Gradient Boosting, will be discussed briefly in this article. XGBoost is a far more difficult subject, which we will address in a future article.

Adaptive Boosting

Consider a box with five pluses and five minutes. Your assignment is to categorize them and organize them into distinct tables.

In the first iteration, you weigh each data point equally and use a decision stump in the box. However, the line separates just two pluses from the group; the remaining pluses stay together. Your decision stump (which is a line that runs through our fictitious box) fails to accurately forecast all data points and has substituted three pluses for the minuses.

In the subsequent iteration, we give greater weight to the three pluses we overlooked earlier; but, this time, the decision stump only separates the group by two minutes. We’ll reweight the minuses that were overlooked in this iteration and restart the procedure. After a few repetitions, we can integrate several of these outcomes to generate a single rigorous prediction rule.

AdaBoost operates in the same manner. It begins by predicting using the original data and weighing each point equally. Then it gives bigger weight to observations that the first learner fails to accurately anticipate. It repeats this procedure until the model’s accuracy exceeds a predefined limit.

Adaboost supports decision stamps as well as other Machine Learning methods.

Here is an AdaBoost implementation in Python:

from sklearn.ensemble import AdaBoostClassifier from sklearn.datasets import make_classification X,Y = make_classification(n_samples=100, n_features=2, n_informative=2, n_redundant=0, n_repeated=0, random_state=102) clf = AdaBoostClassifier(n_estimators=4, random_state=0, algorithm=’SAMME’), Y)

Gradient Boosting

Gradient Boosting uses the Gradient descent approach to minimize the operation’s loss function. Gradient descent is a first-order optimization process for locating a function’s local minimum (differentiable function). Gradient boosting trains several models consecutively and can be used to fit innovative models to provide a more accurate approximation of the response.

It creates new base learners that correspond with the negative gradient of the loss function and are connected to the whole system. Gradient Tree Boosting will be required in Python (also known as GBRT). It may be used to solve classification and regression difficulties.

Here is an implementation of Python Gradient Tree Boosting:

from sklearn.ensemble import GradientBoostingRegressor model = GradientBoostingRegressor(n_estimators=3,learning_rate=1),Y) # for classification from sklearn.ensemble import GradientBoostingClassifier model = GradientBoostingClassifier(),Y)

Features of Boosting in Machine Learning

Since boosting is an ensemble model, it’s pretty natural to interpret its predictions.

Boosting algorithms have higher predictive power than decision trees and bagging.

Scaling it up is a little more challenging, as each estimator in boosting is predicated on the previous estimators.


I really hope you found this post about boosting to be informative. First, we spoke about what this algorithm is and how it may be used to address problems in Machine Learning. Its functioning and how it functions were then examined in greater detail.

We also spoke about the many kinds of it. We learned about AdaBoost and Gradient Boosting as a result of their examples, which we shared as well.

I’m glad you found it interesting. In order to contact me, you may do so using the following methods:


If you still have questions, feel free to send them to me by e-mail.

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