Big-O

Demystifying Computer Science Fundamentals for Modern Developers In modern software practice, knowing core CS ideas helps you write faster, cleaner code and explain decisions to teammates. This post stays practical, using plain examples you can apply in real projects. Data structures and complexity Think of data as ingredients in a kitchen. An array is a fixed row you reach by position; a linked list is a chain you move through item by item. A map helps you find items by key, while a tree keeps things in a helpful order. The right choice matters for speed and memory. Big-O notation is a simple language to describe how performance grows with more data. For example, looking up one item in a sorted list is often faster than checking every item in an unsorted pile. If your app stores user profiles, a hash map gives quick access by id; if you need ordered results, a tree helps keep things organized. ...

The Essentials of Computer Science Fundamentals for Beginners Computer science is a practical way to solve problems. It is not only for experts; anyone can learn the core ideas and apply them to daily tasks, from organizing files to building small tools. This article explains the fundamentals in simple terms, with clear examples and steps you can try. Algorithms and data structures are two foundational ideas. An algorithm is a precise set of steps to finish a task. A data structure stores information in a way that helps the task run fast. Common ones are lists, arrays, and trees. For example, finding a name in an alphabetized phone list is faster if the list is sorted, because you can skip large parts of the list. ...

Demystifying Computer Science Fundamentals for Modern Developers Modern developers often focus on frameworks, tools, and fast delivery. Yet strong fundamentals from computer science help you write clearer, faster, and more reliable code. This post explains core ideas in plain language and links them to everyday coding tasks. Data Structures Data structures let you organize information for quick access and efficient updates. Common ones include: Arrays and lists: simple, contiguous storage; fast index access but fixed size or slow insertions in the middle. Hash maps: key-value storage with fast lookups; watch for collisions. Trees and graphs: structured ways to represent relationships; trees enable sorted traversal, graphs model networks. When choosing a structure, ask: how will I read the data? how often do I add or remove items? what about memory and cache? ...

A Practical Guide to Computer Science Fundamentals A solid grasp of computer science fundamentals helps you learn faster and work more effectively. This guide focuses on approachable ideas you can apply in real projects. Start with clear problem solving, then explore data structures, algorithms, and basic system concepts. The aim is useful understanding, not jargon. Understanding Problem Solving Good problem solving comes from breaking a task into smaller parts. Define the goal, list questions, and choose simple steps you can test. Practice with small, concrete tasks before tackling large programs. This habit makes it easier to spot mistakes and improve designs. ...