Articles

Data Structures 🇺🇸

In computer science, a collection (often interchangeably referred to as a container) is a sophisticated data structure designed to hold multiple entities, these could be simple elements like numbers or text strings, or more complex objects like user-defined structures. Collections help you store, or...

Basic Concepts 🇺🇸

Data structures and algorithms are fundamental concepts in computer science that are key to building efficient software...

Firewall 🇺🇸

A firewall is like a guard for your computer. It keeps your computer safe from others who shouldn't use it. It checks the information going in and out and follows safety rules. In Linux, there are several utilities to manage your firewall, including iptables, ufw, and firewalld...

Running Executables 🇺🇸

We'll explore the inner workings of the Linux kernel, focusing on how it loads and executes binaries. We'll dive into the execve system call, build a custom kernel, and use debugging tools to see the execution process in action. Whether you're a seasoned developer or just curious about operating sys...

File System 🇺🇸

In Unix, files and filesystems are important components of the operating system's structure. A file is a collection of data stored on disk, which can include anything from text documents and images to executable programs. Files are organized within directories in a hierarchical structure, allowing f...

Mounting 🇺🇸

If you come from a Windows world, the idea of mounting might sound strange at first, since Linux handles storage devices and filesystems quite differently. In Linux, "mounting" is the process of making a storage device (such as a hard disk partition, USB drive, or network share) accessible within th...

Cron Jobs 🇺🇸

Cron is a powerful utility in Unix-like operating systems that automates the execution of scripts or commands at specified times, dates, or intervals. It is used for tasks such as system maintenance, backups, updates, and more...

Services 🇺🇸

A service in computing is a background process that performs specific tasks or offers various functionalities to other programs. These services typically communicate using methods such as sockets or inter-process communication (IPC). The primary purposes of a service include...

Processes 🇺🇸

In any operating system, a process is the fundamental unit of execution—a live instance of a program. Beyond its executable code (the text segment), a process encompasses its dynamic state: the program counter, CPU registers, call stack, heap, and other variable storage. To manage and schedule these...

Permissions 🇺🇸

File permissions are crucial in any Unix-like operating systems, including Linux, which employ several mechanisms for controlling access to files and directories. These mechanisms include standard permissions, special permissions, and access control lists (ACLs)...

Package Managers 🇺🇸

Debian and Ubuntu are popular Linux distributions for home users. These distributions and their derivatives use the Advanced Package Tool (APT). Other distributions use alternative package managers, like DNF, YUM, Pacman, which have unique functionalities and syntax...

Log Files and Journals 🇺🇸

Understanding how logging works in Linux is like learning the language your system uses to communicate. Logs are the detailed records that your system keeps about its activities, and they are invaluable for troubleshooting, monitoring performance, and ensuring security. Let's embark on a journey to ...

Serializable vs Repeatable Read 🇺🇸

Transaction isolation levels are essential for maintaining data integrity and managing concurrency in database systems. Two of the highest isolation levels are Serializable and Repeatable Read, each offering different guarantees to prevent anomalies that can occur when multiple transactions interact...

Runge Kutta 🇺🇸

The Runge-Kutta method is part of a family of iterative methods, both implicit and explicit, which are frequently employed for the numerical integration of ordinary differential equations (ODEs). This family encompasses widely recognized methods like the Euler Method, Heun's method (a.k.a., the 2nd...

Gaussian Interpolation 🇺🇸

Gaussian Interpolation, often associated with Gauss’s forward and backward interpolation formulas, is a technique that refines the approach of polynomial interpolation when data points are equally spaced. Instead of using the Newton forward or backward interpolation formulas directly from one end of...

Statistics and Random Numbers 🇺🇸

Statistics, at its core, is the science of collecting, analyzing, and interpreting data. It serves as a foundational pillar for fields such as data science, economics, and social sciences. An important component of statistics is understanding various distributions or, as some textbooks refer to them...

Environment Variable 🇺🇸

In Unix‐style shells, variables let you store and reuse pieces of information—anything from your editor preference (EDITOR=vim) to the path where executables live (PATH=/usr/local/bin:$PATH) or temporary data in a script (count=0). You’ll encounter two main kinds...

Dziedziczenie i Kompozycja 🇵🇱

Dziedziczenie oraz kompozycja to dwa filary programowania obiektowego, dzięki którym możemy pisać elastyczny, modułowy i łatwy w utrzymaniu kod. Każde z tych rozwiązań niesie ze sobą unikalne zalety i wiąże się z określonymi ograniczeniami, dlatego decyzja o ich zastosowaniu powinna wynikać z charak...

Liczby Losowe 🇵🇱

W języku C++ liczby losowe generuje się za pomocą standardowej biblioteki . Proces losowania zaczyna się od utworzenia generatora liczb pseudolosowych, np. std::mt19937, który bazuje na algorytmie Mersenne Twister. Aby uzyskać bardziej losowe wyniki, generator inicjalizuje się za pomocą unik...

Vector Operations 🇺🇸

A vector is a mathematical entity characterized by both magnitude and direction. Vectors are essential in various fields such as linear algebra, calculus, physics, computer science, data analysis, and machine learning. In the context of NumPy, vectors are represented as one-dimensional arrays, enabl...

Hierarchical Data 🇺🇸

In many applications, data is naturally organized in a hierarchical structure, such as organizational charts, file systems, categories and subcategories, and family trees. Representing and querying this hierarchical data efficiently in a relational database can be challenging due to the flat nature ...

Central Difference 🇺🇸

The central‐difference method is a finite‐difference scheme for estimating derivatives that combines forward and backward differences via Taylor‐series expansions. By evaluating the function at points symmetrically placed around the target, it cancels out many of the lower‐order error terms, yieldin...

Thin Plate Spline Interpolation 🇺🇸

Thin Plate Spline (TPS) interpolation is a non‑parametric, spline‑based technique for fitting a smooth surface through scattered data in two or more spatial dimensions. In its classical 2‑D form one seeks a function $f\colon\mathbb R^{2}\to\mathbb R$ that passes through specified data points while m...

Searching Filtering and Sorting 🇺🇸

NumPy provides a set of functions for searching, filtering, and sorting arrays. These operations are helpful for efficiently managing and preprocessing large datasets, enabling you to extract meaningful information, organize data, and prepare it for further analysis or machine learning tasks. This g...

Reshaping Arrays 🇺🇸

In data manipulation and analysis, adjusting the shape or dimensionality of arrays and matrices is a common task. Reshaping allows you to reorganize data without altering its underlying values, making it suitable for various applications such as data preprocessing, machine learning model input prepa...

Two Phase Locking 🇺🇸

Two‑Phase Locking (2PL) is a scheduling rule built into database engines to keep concurrent transactions from stepping on each other. 2PL does not change what your application writes—it changes when each transaction is allowed to read or write shared data so that the overall result is the same as so...

Least Squares 🇺🇸

Least Squares Regression is a fundamental technique in statistical modeling and data analysis used for fitting a model to observed data. The primary goal is to find a set of parameters that minimize the discrepancies (residuals) between the model’s predictions and the actual observed data. The "leas...

Interpolation 🇺🇸

Interpolation is the problem of reconstructing an unknown function from a finite set of exact data pairs...

Interactivity 🇺🇸

VTK supports interactive visualization through several core features that together form a powerful environment for exploratory data analysis. By combining low-level access to rendering primitives with high-level interactor and widget frameworks, VTK enables you to build applications where users can ...

Accessing Modifying Elements 🇺🇸

In NumPy, arrays are data structures that store elements in a grid-like fashion. Understanding how to access and modify these elements is helpful for efficient data manipulation and analysis. NumPy arrays are 0-indexed, meaning the first element is accessed with index 0, the second with index 1, and...

Matrix Operations 🇺🇸

A matrix is a systematic arrangement of numbers (or elements) in rows and columns. An m × n matrix has m rows and n columns. The dimensions of the matrix are represented as m × n...

Database Caching 🇺🇸

Database caching is a powerful performance optimization technique that involves temporarily storing frequently accessed data in a cache for quick retrieval. By keeping commonly requested information readily available, caching reduces the time it takes to access data and lessens the load on the datab...

Double Booking Problem 🇺🇸

The double-booking problem is a common issue in database systems, particularly in applications like booking platforms, reservation systems, and inventory management. It occurs when multiple transactions simultaneously attempt to reserve or modify the same resource, leading to conflicts and inconsist...

How Tables and Indexes Are Stored on Disk 🇺🇸

Exploring how databases store tables and indexes on disk can provide valuable insights into optimizing performance and managing data efficiently. Let's delve into the fundamental concepts of disk storage in relational databases, focusing on the structures and mechanisms that underlie data organizati...

Squashing Commits 🇺🇸

In Git, you might accumulate multiple small commits over the course of developing a new feature, fixing small bugs, or refactoring code. While these incremental commits are crucial during active development, they can clutter the project history in the long term. This clutter becomes especially evide...