Algorithms

Algorithm complexity measures how the running time or memory usage of an algorithm grows as the size of its input increases. Big-O notation is the standard way to express this.

Space complexity describes how much memory an algorithm needs relative to its input size. Alongside time complexity, it helps you evaluate whether an algorithm is practical for a given situation.

Time complexity describes how the running time of an algorithm grows as the input size increases. Using Big O notation, you can compare algorithms and predict which will perform better on large datasets.

Drawing a flowchart means turning an algorithm into a clear visual diagram using the correct symbols, decision paths, and loop structures. A well-drawn flowchart communicates logic better than code alone.

Flowchart symbols are standardised shapes used to represent different types of steps in an algorithm. Learning the standard symbols lets you read and draw flowcharts clearly and consistently.

A flowchart is a visual diagram that uses standard shapes and arrows to represent the steps and decisions in an algorithm or process.

Study of problem-solving approaches, algorithm design, and computational complexity analysis.

Pseudocode structures — sequence, selection, and iteration — are the three building blocks used to express any algorithm. Mastering them lets you plan solutions to complex problems clearly.

Pseudocode is an informal, plain-English way of describing an algorithm's steps without worrying about the exact rules of any programming language.

Pseudocode is an informal way of describing an algorithm using plain language and programming-like structure. It lets you plan your logic before worrying about the syntax of a real programming language.

Binary search finds a target value in a sorted list by repeatedly halving the search space. It is dramatically faster than linear search for large datasets.

Linear search checks each item in a list one by one until it finds the target or reaches the end. It is the simplest search algorithm and works on any list, sorted or unsorted.

Searching algorithms find a specific item within a collection of data. The two most fundamental approaches are linear search and binary search.

Bubble sort is a simple sorting algorithm that repeatedly swaps adjacent items that are in the wrong order. It is a great first algorithm to study because its logic is easy to follow step by step.

Insertion sort builds a sorted list one item at a time by inserting each new item into its correct position among the already-sorted items. It works especially well on small or nearly-sorted lists.

Selection sort finds the smallest item in the unsorted portion of a list and moves it into place, one item at a time. It is easy to understand and always makes the same number of comparisons.

Sorting algorithms arrange a list of items into a defined order. Understanding how they work helps you choose the right one for a given task.