Glossary

What Is Algorithm?

An algorithm is a step-by-step procedure for solving a problem or accomplishing a task. In programming, algorithms are the logic behind sorting data, searching records, finding shortest paths, and processing information. Understanding algorithms is essential for writing efficient code and passing technical interviews.

How Algorithm Works

Algorithms are everywhere: Google Search uses PageRank to rank results. GPS apps use Dijkstra's algorithm to find shortest routes. Netflix uses collaborative filtering algorithms for recommendations. Instagram's feed uses ranking algorithms to order posts.

Algorithm efficiency matters: a naive search through 1 million records takes 1 million comparisons. Binary search takes 20. The right algorithm can make the difference between a page loading in 50ms vs 50 seconds.

Why Developers Use Algorithm

You don't need to memorize every algorithm, but understanding fundamental patterns — divide and conquer, greedy, dynamic programming, graph traversal — lets you recognize and solve new problems efficiently.

Key Concepts

  • Time Complexity — How execution time grows with input size — O(1), O(log n), O(n), O(n²)
  • Space Complexity — How memory usage grows with input size — algorithms trade time for space and vice versa
  • Divide and Conquer — Break a problem into smaller subproblems, solve each, combine results — merge sort, quicksort
  • Greedy Algorithms — Make the locally optimal choice at each step — works for some problems (coin change, scheduling)
  • Brute Force — Try every possible solution — always works but often too slow for large inputs
  • Recursion — An algorithm that calls itself with smaller inputs — base case stops the recursion

Binary Search Algorithm

javascript
function binarySearch(arr, target) {
  let left = 0;
  let right = arr.length - 1;

  while (left <= right) {
    const mid = Math.floor((left + right) / 2);
    if (arr[mid] === target) return mid;
    if (arr[mid] < target) left = mid + 1;
    else right = mid - 1;
  }

  return -1; // Not found
}

// O(log n) — searches 1 billion items in ~30 steps
binarySearch([1, 3, 5, 7, 9, 11, 13], 7); // → 3

Learn Algorithm — Top Videos

Algorithm Educators

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Frequently Asked Questions

Do I need algorithms for web development?

You rarely implement sorting or graph algorithms from scratch. But understanding Big O, data structures, and algorithmic thinking helps you write efficient code, choose the right tools, and pass interviews.

How do I learn algorithms?

Start with Big O notation, then learn searching (binary search), sorting (merge sort, quicksort), and basic data structures. LeetCode Easy problems build pattern recognition. Books: 'Grokking Algorithms' for beginners.

What algorithms should every developer know?

Binary search, BFS/DFS (graph traversal), sorting (quicksort, merge sort), hash tables, and dynamic programming basics. These cover 90% of interview and real-world algorithm needs.

Want a structured learning path?

Plan a Algorithm Lesson →

Related Terms

Data StructureBig O NotationSorting AlgorithmBinary SearchDynamic Programming

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