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 C++20 has redefined modern C++ programming with powerful features like concepts and requires clauses. This comprehensive guide is tailored for young professionals and college students, helping you leverage these new tools to write safer, more maintainable code. Throughout this article, you'll find practical code examples. Suggested Reads on templates : CRTP  , Partial Template Specialization  , Perfect Forwarding What Are C++20 Concepts? C++20 Concepts allow you to constrain template parameters directly in your code, ensuring that only types meeting specific requirements are accepted. This feature acts as a compile-time predicate and is essential for creating clear and robust templates. How Concepts Work Concepts enable you to specify what properties a type must have. They improve code readability by making your intentions explicit and significantly enhance error messages when template constraints aren’t met. For example, consider a function designed to add two values on...

InfluxDB is a high-performance, scalable time series database widely used for real-time data monitoring, IoT, and analytics applications. Integrating it with C++ allows you to build efficient data processing applications that deliver real-time insights. This guide is crafted for young professionals and college students seeking a step-by-step, easy-to-understand approach. Why Integrate InfluxDB with C++? Using InfluxDB with C++ brings several benefits: • High-Performance Data Handling – Ideal for applications needing real-time analytics and high write loads. • Versatile Data Monitoring – Perfect for IoT applications, sensor data collection, and performance analytics. • Scalability – Supports projects ranging from small-scale prototypes to enterprise-level deployments. For more details on InfluxDB features, you can check the official InfluxData documentation at https://docs.influxdata.com/influxdb/ . Prerequisites Before starting the integration, ensure you have the following: • A C++ de...

Introduction to SQL and SQL Data Formats SQL, which stands for Structured Query Language, is the foundation of relational databases. It is the standard language for querying and managing data in systems that rely on structured, tabular data. Data is stored in tables with rows and columns in SQL databases, such as MySQL, PostgreSQL, and Oracle. These databases use a Schema-on-write approach, meaning the structure of the data is defined and enforced before data is inserted into the system. SQL databases rely on well-defined schemas to ensure data consistency and integrity. They adhere to ACID principles—Atomicity, Consistency, Isolation, and Durability—which guarantees that transactions are processed reliably. For instance, in a banking system where every transaction must be recorded accurately, SQL databases are ideal because they ensure that every deposit, withdrawal, or transfer is handled securely and consistently. Understanding NoSQL and NoSQL Data Formats NoSQL stands for “...

Partial template specialization is a nuanced feature in C++ that allows developers to customize class templates for specific categories of template arguments. This capability enhances code flexibility and efficiency by enabling tailored behavior for particular data types or conditions. Understanding Partial Template Specialization In C++, templates provide a mechanism for writing generic and reusable code. A class template serves as a blueprint for a class that can handle various data types. However, there are scenarios where the default implementation may not be optimal or applicable for certain types. Partial template specialization addresses this by allowing the customization of the template for specific types or conditions, without necessitating a complete overhaul of the original template. Syntax of Partial Template Specialization The general syntax for a partially specialized class template is as follows: template <typename T1, typename T2> class ClassName { ...

  When it comes to measuring the performance of systems, especially in networking and software engineering, the terms "latency" and "response time" are often used interchangeably. However, these terms have distinct meanings, and understanding their differences is essential for optimizing system performance and troubleshooting effectively.  What is Latency? Latency refers to the time it takes for a single data packet to travel from the source to its destination. It is the delay introduced by the system—be it due to network transmission, processing time, or other factors. In simpler terms, latency measures the delay between the moment a request is made and when it begins to be processed. Latency is often measured in milliseconds (ms). Example of Latency: Imagine you send a request to load a webpage. The latency is the time it takes for the initial request to travel from your computer to the server hosting the webpage. In the video, the example of a video confere...

In software engineering, terms like "fault" and "failure" are fundamental, yet they are often misunderstood or used interchangeably. Grasping the difference between these concepts is crucial for developing reliable software and effectively troubleshooting issues. Let’s delve into these terms, enriched with insights from the referenced video, to clarify their meanings and implications. What is a Fault? A fault refers to an incorrect step, process, or data definition in a computer program. It is essentially a flaw in the system's code or design that has the potential to cause the software to operate incorrectly. Faults are often introduced during the development phase and may remain undetected until they are triggered under specific conditions. Example of a Fault: Consider a function designed to calculate the average of a list of numbers: def calculate_average(numbers): return sum(numbers) / len(numbers) If the input list is empty, this code will resu...

Sharing the code which demonstrates synchronization between two threads. Two threads execute interchangeably, all thanks to the condition variable. I have also shared the code execution output   Check out the Video: #include <iostream> #include <thread> #include <mutex> #include <condition_variable> using namespace std; mutex m; condition_variable cnd; int previousThreadId; void print(int threadID) { for (size_t i = 0; i < 20; i++) { unique_lock<std::mutex> ul(m); //->Threads Waiting Zone cnd.wait(ul, [&]()->bool {    if (threadID != previousThreadId) return true; else return false; }); previousThreadId = threadID; cout << "\nThread # " << threadID << " Executing..."; cout << "\nPrinting  : " << i<< "\n"; ul.unlock(); cnd.notify_one(); } } int main() { thread t[2]; for (size_t i = 0; i < 2; i++) { t[i] = th...