Top 10 Interesting Fact About C++
The fact that C++ has been around for roughly 40+ years is due to a variety of factors, including its dependability, maturity, and versatility. C++ continues to be at the center of many programming curricula because of its quick speed and flawless performance, and it has a wide-ranging ecosystem. Because of this, C++ programming is among the most popular services provided by software outsourcing firms.
Top 10 interesting fact about C++
1). Gaming
Playing
again and again... The most cutting-edge gaming engines for computers are
created in C/C++ and Assembly. Who can forget the Quake gaming platform? The
renowned video game Quake, which used cutting-edge 3D graphics techniques. And
this is but one illustration of this sort.
2). YouTube
Everyone
adores it, but how many of you are aware that C++ is used extensively in its
"backend" (don't use this term around C++ programmers:))?
3). Microsoft Office
Does anyone
know that Microsoft Office was created in C++ while being used on hundreds of
millions of PCs every day? Few consumers are aware that one of the most
well-known desktop software programs ever was created in C++ (and some still
maintain that C++ is dead).
4). The desktop operating systems
C/C++ and
Assembly make up the majority of the desktop operating systems that you use on
your computers every day, such as Windows, Linux, and MacOS. The widely used
JavaScript and its substitutes are not present.
5). GCC
Now, what
language was used to create GCC (GNU Compiler Collection, the compilers for
C/C++)? Yes, GCC was also created in C/C++. Although it might sound like a
recursion, C/C++ compilers are really written in C/C++.
6). AI/ML
And at the
very top of the list is AI/ML. "But AI applications are written in
Python," you could object. The high-end AI/ML libraries, such as
TensorFlow, Caffe, CNTK, mlpack, etc., are all built in C/C++, and here is
where the secret resides. To call the functions from such libraries and utilize
them in your code, you just use the Python bindings.
7). C++ contains over 35 operators
In contrast
to other languages, C++ has more than 35 operators that include implementations
for manipulation, logical operations, arithmetic, and other topics. All of them
may be uploaded for varied program requirements, however the conditional
operator is the one exception. The vast range of operators in C++ makes
user-defined types resemble built-in types.
8). Serves various data types
With
user-defined operations, unions, queues, and other coding components, many
built-in C++ functions perform flawlessly.
9). Python connected
TensorFlow
is constructed in C++ as opposed to the C language used to create the Python
interpreter, which is accessible through a Python layer.
10). Most criticized language
Even though
it is extremely well-liked and has a track record of success, C++ is often
criticized by programmers. Donald Knuth, Linus Torvalds, and others have addressed
the key qualities of C++, including its abundance of non-orthogonal features,
lack of readability benefits, technical complexity, and more.
As you can
see, C++ is still relevant today. In order to help build all the IT
masterpieces that we so love utilizing both in business and in our daily lives,
its utilization keeps expanding and enlarging the regions of coverage. And if
you are thinking about using C++ for your project, visit this blog to learn
more about it and to obtain the most recent information.
📘 IT Tech Language
☁️ Cloud Computing - What is Cloud Computing – Simple Guide
- History and Evolution of Cloud Computing
- Cloud Computing Service Models (IaaS)
- What is IaaS and Why It’s Important
- Platform as a Service (PaaS) – Cloud Magic
- Software as a Service (SaaS) – Enjoy Software Effortlessly
- Function as a Service (FaaS) – Serverless Explained
- Cloud Deployment Models Explained
🧩 Algorithm - Why We Learn Algorithm – Importance
- The Importance of Algorithms
- Characteristics of a Good Algorithm
- Algorithm Design Techniques – Brute Force
- Dynamic Programming – History & Key Ideas
- Understanding Dynamic Programming
- Optimal Substructure Explained
- Overlapping Subproblems in DP
- Dynamic Programming Tools
🤖 Artificial Intelligence (AI) - Artificial intelligence and its type
- Policy, Ethics and AI Governance
- How ChatGPT Actually Works
- Introduction to NLP and Its Importance
- Text Cleaning and Preprocessing
- Tokenization, Stemming & Lemmatization
- Understanding TF-IDF and Word2Vec
- Sentiment Analysis with NLTK
📊 Data Analyst - Why is Data Analysis Important?
- 7 Steps in Data Analysis
- Why Is Data Analysis Important?
- How Companies Can Use Customer Data and Analytics to Improve Market Segmentation
- Does Data Analytics Require Programming?
- Tools and Software for Data Analysis
- What Is the Process of Collecting Import Data?
- Data Exploration
- Drawing Insights from Data Analysis
- Applications of Data Analysis
- Types of Data Analysis
- Data Collection Methods
- Data Cleaning & Preprocessing
- Data Visualization Techniques
- Overview of Data Science Tools
- Regression Analysis Explained
- The Role of a Data Analyst
- Time Series Analysis
- Descriptive Analysis
- Diagnostic Analysis
- Predictive Analysis
- Pescriptive Analysis
- Structured Data in Data Analysis
- Semi-Structured Data & Data Types
- Can Nextool Assist with Data Analysis and Reporting?
- What Kind of Questions Are Asked in a Data Analyst Interview?
- Why Do We Use Tools Like Power BI and Tableau for Data Analysis?
- The Power of Data Analysis in Decision Making: Real-World Insights and Strategic Impact for Businesses
📊 Data Science - The History and Evolution of Data Science
- The Importance of Data in Science
- Why Need Data Science?
- Scope of Data Science
- How to Present Yourself as a Data Scientist?
- Why Do We Use Tools Like Power BI and Tableau
- Data Exploration: A Simple Guide to Understanding Your Data
- What Is the Process of Collecting Import Data?
- Understanding Data Types
- Overview of Data Science Tools and Techniques
- Statistical Concepts in Data Science
- Descriptive Statistics in Data Science
- Data Visualization Techniques in Data Science
- Data Cleaning and Preprocessing in Data Science
🧠 Machine Learning (ML) - How Machine Learning Powers Everyday Life
- Introduction to TensorFlow
- Introduction to NLP
- Text Cleaning and Preprocessing
- Sentiment Analysis with NLTK
- Understanding TF-IDF and Word2Vec
- Tokenization and Lemmatization
🗄️ SQL
💠 C++ Programming - Introduction of C++
- Brief History of C++ || History of C++
- Characteristics of C++
- Features of C++ || Why we use C++ || Concept of C++
- Interesting Facts About C++ || Top 10 Interesting Facts About C++
- Difference Between OOP and POP || Difference Between C and C++
- C++ Program Structure
- Tokens in C++
- Keywords in C++
- Constants in C++
- Basic Data Types and Variables in C++
- Modifiers in C++
- Comments in C++
- Input Output Operator in C++ || How to take user input in C++
- Taking User Input in C++ || User input in C++
- First Program in C++ || How to write Hello World in C++ || Writing First Program in C++
- How to Add Two Numbers in C++
- What are Control Structures in C++ || Understanding Control Structures in C++
- What are Functions and Recursion in C++ || How to Define and Call Functions
- Function Parameters and Return Types in C++ || Function Parameters || Function Return Types
- Function Overloading in C++ || What is Function Overloading
- Concept of OOP || What is OOP || Object-Oriented Programming Language
- Class in C++ || What is Class || What is Object || How to use Class and Object
- Object in C++ || How to Define Object in C++
- Polymorphism in C++ || What is Polymorphism || Types of Polymorphism
- Compile Time Polymorphism in C++
- Operator Overloading in C++ || What is Operator Overloading
- Python vs C++ || Difference Between Python and C++ || C++ vs Python
🐍 Python - Why Python is Best for Data
- Dynamic Programming in Python
- Difference Between Python and C
- Mojo vs Python – Key Differences
- Sentiment Analysis in Python
🌐 Web Development
🚀 Tech to Know & Technology
- The History and Evolution of Data Science
- The Importance of Data in Science
- Why Need Data Science?
- Scope of Data Science
- How to Present Yourself as a Data Scientist?
- Why Do We Use Tools Like Power BI and Tableau
- Data Exploration: A Simple Guide to Understanding Your Data
- What Is the Process of Collecting Import Data?
- Understanding Data Types
- Overview of Data Science Tools and Techniques
- Statistical Concepts in Data Science
- Descriptive Statistics in Data Science
- Data Visualization Techniques in Data Science
- Data Cleaning and Preprocessing in Data Science

