The content describes the process of converting a simple calculator program in C++ into a reusable component for client applications. It emphasizes separating functionality into distinct source files, creating a public interface via a header file, and packaging the compiled implementation as a static library. This enables clients to use the calculator's functions without receiving the original source code.
The STM32U5A5 features a Cortex-M33 core enhancing secure boot capabilities with TrustZone technology. It ensures secure memory attribution and controlled transitions from Non-secure to Secure environments. Using Option Bytes, it enforces security settings. The device performs secure image verification through ECDSA, maintaining a strong Root of Trust to protect boot processes.
The dissertation template aids students in engineering and applied research by providing a structured approach to addressing research problems through clear connections among literature, methodology, evidence, and findings. It emphasizes the importance of tailored content and adherence to institutional guidelines. The template supports various research designs, ensuring clarity and rigor in presentations.
The content discusses embedded programming using Rust, highlighting the Embassy framework for hardware interaction on STM32 microcontrollers. It explains how Embassy simplifies peripheral management by providing an abstraction layer, enabling the application to function without direct register manipulation. This project focuses on integrating sensors and cloud communication within an STM32 home monitoring system.
Learn how Cargo.toml, crates, Cargo.lock and cargo build configure and compile a bare-metal Rust application for an STM32U5 microcontroller.
This blog outlines the development of a cloud-connected sensor node using the STMicroelectronics B-U585I-IOT02A Discovery Kit. The project combines a custom bootloader in C with Rust firmware for data acquisition and cloud integration via AWS IoT Core, providing a comprehensive engineering guide from hardware setup to data visualization.
Explore C++26 Contracts through a practical ring-buffer example, including preconditions, postconditions, manual C++23 checks and GCC evaluation semantics.
The post compares C++ and Rust regarding array bounds checking. It highlights that C++ allows out-of-bounds access, leading to undefined behavior, while Rust implements automatic bounds checking, triggering a panic on invalid access. Rust provides safer alternatives, such as the get() method, enhancing memory safety without manual error handling.
The post discusses exploring C++26, detailing setup on Ubuntu and features like template for, reflection, and JSON serialization. It introduces annotations as a powerful feature that simplifies validation in class constructors, ensuring values remain within specified ranges. This approach avoids error-prone manual validation when new class members are added.
Logical operators in C++ combine conditional statements to yield boolean values. The primary operators include Logical AND (&&), Logical OR (||), and Logical NOT (!). They enable complex conditions in decision-making structures, dictate execution flow, and follow a specific precedence, enhancing programming efficiency and functionality.
The content explains how addresses of array elements are computed in C++, focusing on a char array, an int array, and a double array. It details the relationship between base address, index, and element size, emphasizing pointer arithmetic and calculating addresses using the formula: base address + index × sizeof(element type).
In Python, names and objects are distinct; unlike in C/C++, where a variable directly links to memory, Python's variable names function as bindings to objects. Reassigning a name creates a new binding without overwriting the old object. This separation clarifies Python's behavior, such as in parameter passing and variable assignments.
The post discusses using the experimental C++26 reflection feature for JSON serialization of user-defined classes, specifically focusing on the CanDataSource class. It contrasts manual serialization approaches with the flexibility offered by reflection, allowing automatic updates in JSON output when class definitions change. Full source code is available on GitHub.
Exam Question Pattern 1 Pointers, dynamic arrays and template classes: a complete C++ examination revision guide based on recurring question patterns Vivek Bhadra | C++…
Understanding the memory layout of a C++ program is crucial for systems programmers. It includes regions such as program code, initialized data, the heap, stack, and free space, each with distinct functions. The stack, operating on a LIFO principle, manages function calls and local variables but has limited size, which can lead to overflow.
This article explains how to format C++ code using clang-format in VS Code on Linux, ensuring a consistent coding style across the entire codebase. It covers installation, configuration of .clang-format and .vscode/tasks.json files, and includes instructions for formatting individual files or entire projects, highlighting benefits such as cleaner code reviews and easier onboarding.
The author aims to explore C++26 progressively, focusing on its new features, particularly reflection. C++26 introduces the `enumerators_of()` function, allowing easy access to enum class members without manual updates. The author discusses utilizing this feature to convert enum values to strings and promises to share further insights as exploration continues.
The author explores the new "template for" feature in C++26 while attempting to reduce redundancy in calling a function template. They illustrate the concept with examples, highlighting how "template for" allows iterating over arrays as non-type template arguments. The discussion includes compiling the code and best practices for defining arrays.
"Prompting C++ for Systems Engineering" by Vivek Bhadra is a comprehensive guide to modern C++ focusing on practical applications in systems engineering. It covers fundamentals to advanced topics like AI-assisted development, memory management, multithreading, and debugging. The book targets students and professionals seeking to enhance their C++ skills with real-world projects and examples.
This post outlines advanced C++ debugging strategies beyond conventional techniques. It emphasizes understanding the problem, effective code inspection, targeted searches, log analysis, historical comparisons, version control, and using visual diff tools. The content also mentions the author's book for a comprehensive guide on systematic debugging approaches and AI assistance in engineering.
STM32CubeMX is a graphical tool by STMicroelectronics for STM32 microcontroller projects, streamlining setup and code generation. The installation process on Ubuntu 22.04 can face Java runtime issues, particularly requiring Java 21 for version 6.17.0. Creating a symbolic link to Java 21 resolves installation errors, ensuring successful setup.
The author successfully installed the GCC 16.1 compiler on an Ubuntu machine, outlining the installation steps and necessary dependencies. Following installation, a sample C++26 program utilizing reflection was compiled and executed without issues, demonstrating the new features of the compiler. The process and the author's excitement for the new capabilities are detailed.
Machine learning can be daunting for beginners, but Google Colab simplifies the process by allowing users to run workflows directly in their browser without complex setup. This guide outlines creating a complete ML pipeline in Colab, from library installation and data loading to training models and evaluation, concluding with the utility of voice features for Parkinson's disease prediction.
This post details the setup of a local Splunk Enterprise server on Ubuntu, integrating it with AWS VPC Flow Logs. It guides users through downloading, installing Splunk, exporting logs from AWS CloudWatch, and configuring data ingestion. This local environment serves as a valuable resource for cloud log management and analytics.
The post emphasizes the importance of creating an IAM user for daily AWS activities instead of using the root account. It details the steps for setting up an IAM user with administrative permissions, enabling MFA, creating access keys for CLI, and verifying configuration. This approach enhances security and access control.
The content discusses various partitioning methods for database tables, including range, list, and hash partitioning, along with their applications. It also covers data storage calculations, B-Tree construction, and the nature of B-Trees. Key concepts include composite partitioning, selectivity in data warehouses, and handling duplicate values in B-Tree indexes.
The content discusses various types of encryption, notably symmetric (using a single key) and asymmetric (utilizing a public and private key). It evaluates methods such as AES, homomorphic encryption, and client-server approaches, emphasizing the importance of strong key management practices and the significance of encryption across sectors like healthcare and finance.
The Physical Design Process in database management transforms logical models into practical structures for efficient data handling. It focuses on optimizing data storage, access, and retrieval through methods like indexing, partitioning, and aggregation. This ensures quick query responses and scalability while maintaining a systematic architecture for performance and manageability.
Serverless architecture is a cloud computing model where the provider manages the infrastructure, allowing developers to focus solely on code execution in response to events. This paradigm shift emphasizes event-driven designs, efficient scaling, and cost-effectiveness, reducing operational overhead while highlighting security challenges related to input validation, permissions, and dependency management.
The Shared Responsibility Model outlines security roles between cloud providers and customers across IaaS, PaaS, and SaaS. Providers manage infrastructure security while customers secure their deployed resources. Understanding these responsibilities is crucial to prevent breaches. Effective cloud security frameworks like IAM, API gateways, and VM hardening mitigate risks in various architectures.
OLTP systems require a normalized schema to process everyday transactions efficiently, ensuring data integrity, reducing anomalies, and supporting concurrent users. In contrast, data warehouses use denormalized structures for analytical purposes. The Staging Area facilitates data extraction, cleansing, and integration before loading into the warehouse, vital for decision-making and reporting.
The content discusses OLAP (Online Analytical Processing) concepts, highlighting the differences between relational databases and multidimensional structures, specifically data cubes. It elaborates on OLAP operations, implementation types (MOLAP, ROLAP, HOLAP), and their advantages and disadvantages, aiming to support effective data analysis and decision-making within organizations.
The post discusses the nature of streaming data, characterizing it as often loosely structured due to its variety and dynamic flow. It evaluates data ingestion patterns, describes workloads for a real estate portal's architecture, and addresses aspects of message delivery semantics for live streaming and online shopping platforms, emphasizing flexibility and accuracy.
Apache Kafka is a distributed messaging system that supports high throughput and low latency, ideal for real-time data processing. It combines publish-subscribe and queuing models, enabling effective data communication across applications. Key components include producers, consumers, topics, and partitions, ensuring reliability, scalability, and durability in data management.
This overview discusses distributed data flows, outlining their significance in modern systems. It highlights how systems like Apache Kafka and Flume facilitate the movement of data across diverse components, addressing the challenges of integration and scaling. Delivery semantics, such as "At Most Once" and "Exactly Once," dictate reliability and performance trade-offs in data delivery.
Distributed systems necessitate careful coordination due to their reliance on shared state across multiple nodes. Manual management risks errors, pushing the need for a dedicated service like Apache ZooKeeper. It offers features such as configuration management, leader election, and strong consistency, crucial for high availability and scalable real-time data processing.
Streaming data architectures consist of layered systems focused on real-time processing. The Lambda model features dual paths for batch and stream processing, ensuring accuracy and scalability but increasing complexity. Alternatively, Kappa simplifies this with a single stream approach, relying on replayable logs. Both require careful management of availability, latency, and scalability.
This document summarizes the functionalities and applications of real-time and streaming data systems, emphasizing their key distinctions. It explains real-time systems' focus on immediate responses and streaming systems' continuous data processing. With various examples and applications across industries, it serves as a foundational guide for understanding these essential concepts in data processing.
Modern data applications require the integration of various components to manage large, complex data flows effectively. Core non-functional requirements are reliability, scalability, and maintainability. Traditional databases face challenges in scaling, leading to big data systems that address these issues through distributed architectures, fault tolerance, and a focus on immutability for data integrity and easier recovery.
The content discusses the challenges of processing sensor data in embedded software using traditional loops, highlighting issues with complexity and error management. It introduces the advantages of C++20's std::ranges, allowing for cleaner, more efficient data processing through a chain of filters and transformations without convoluted logic, while emphasizing potential drawbacks of relying on views.
The post discusses partitioning a set of 12 sales price records into three bins using equal-frequency, equal-width, and clustering methods. It further explains data smoothing techniques through bin means and medians. Key points highlight the benefits and limitations of each method, particularly regarding sensitivity to outliers.
C++17 introduced std::optional to improve API design by allowing functions to return an optional value. Instead of returning a placeholder like -1 when a key isn't found in a map, std::optional lets functions return std::nullopt. C++23 further enhances error handling with std::expected, allowing custom error messages.
The project outlines the creation of an AI-based examiner tool that automates the marking of handwritten GCSE exams. Teachers can upload scanned PDFs, and in 20-30 seconds, receive detailed feedback reports formatted as .docx files. Built using Python, Flask, and Gemini AI, it offers an efficient marking solution while ensuring data privacy.
The post discusses building a multithreaded HTTP web server in C++ using a thread pool to handle concurrent connections, Nginx as a reverse proxy, and Docker for containerization. The server manages shared state with mutexes and condition variables, ensuring thread safety. Key features include live management, health checks, and rate limiting.
The content discusses the transition from a monolithic to a microservices architecture for a growing online retail company. It explains challenges of monolithic systems under increased demand, benefits of microservices such as independent deployment and service autonomy, and suggests a microservices redesign to enhance scalability, fault isolation, and maintainability.
The content discusses scalable architecture for a video streaming platform, addressing vertical and horizontal scaling, and load balancing to manage increased traffic. It also outlines the design of a distributed e-commerce platform's scaling algorithm and explores the CAP theorem's trade-offs in distributed systems. Finally, it emphasizes the importance of database sharding and caching for a global-scale video sharing platform.
Chapter 3 of the Security Fundamentals focuses on Infrastructure Security, emphasizing the importance of safeguarding the components that support various services and systems. It provides a summary that encompasses key security principles and strategies for protecting infrastructure from potential threats. Additionally, the chapter introduces the concept of scalability, discussing how systems can grow and adapt to meet increasing demands without compromising security or performance. This section highlights the necessity of designing infrastructures that are both secure and scalable to ensure sustainable operation and resilience against cyber risks. Overall, it underscores the interplay between security and scalability in modern technology environments.
The discussion centers on returning std::vector from C++ functions, highlighting Return Value Optimization (RVO) introduced in C++17. RVO allows the compiler to avoid copying vectors by constructing them in place when there's a single return path. For multiple return paths, std::move is used to transfer ownership efficiently. Exceptions exist, particularly with the conditional operator, which requires copying. Returning references from member functions is safer than from free functions since the object's lifetime ensures validity.
In multi-threaded programming, protecting shared resources is crucial. std::mutex is common, but may bottleneck performance when many readers access data. std::shared_mutex can optimize scenarios with many readers and few writers, though its advantages depend on thread concurrency. Understanding the workload's read/write balance is key for effective synchronization.
This post discusses the importance of efficient data handling in modern C++, exploring methods of passing contiguous data buffers to functions, including raw pointers, std::vector, std::array, and the C++20 feature std::span. It highlights the strengths and weaknesses of each method, emphasizing std::span's benefits for safe, flexible data management without ownership.