Welcome to the Binary Search section. This module covers everything from the core algorithm to advanced applications and interview-ready patterns.

Binary search is a divide-and-conquer search algorithm that finds a target in a sorted collection by repeatedly halving the search space.

Instead of checking every element one-by-one (O(n)), binary search eliminates half of the remaining candidates on every step — achieving O(log n) time.

Searching for 35 in a sorted array of 1,000,000 elements:

Linear Search:  up to 1,000,000 comparisons
Binary Search:  at most 20 comparisons   (log₂ 1,000,000 ≈ 20)

That is the power of logarithmic time.

• Binary Search — Introduction — Algorithm walkthrough, iterative vs recursive, off-by-one bugs

• Patterns Overview — Decision flowchart to pick the right pattern
  • Classic Search — Find exact value in sorted array
  • First/Last Occurrence — Handle duplicates
  • Search on Answer — Min/max feasible value
  • Rotated Array — Search in rotated sorted array
  • Monotonic Function — Boundary search

• Problems Overview — 10 problems from easy to hard
  • Search Rotated Sorted Array, Find Min Rotated, 2D Matrix, Peak Element, Koko Bananas, Ship Packages, Split Array, Sqrt(x), First Bad Version, Time-Based KV

• Advanced Overview — Beyond the basics
  • Floating-Point Search — Continuous ranges with precision
  • Median of Two Arrays — The hardest BS problem
  • Exponential/Interpolation — When log n isn’t enough
  • Real-World Problems — Painter, Cows, Force, Trips

• Interview Questions Overview — 12+ questions
  • Theory & Fundamentals
  • Pattern Recognition
  • Tricky Variations

The golden rule: If you can say “I can eliminate half the candidates” after one comparison, binary search applies.

• Arrays — Binary search operates on arrays
• Recursion — Recursive binary search and divide-and-conquer
• Sorting — Many sorting algorithms complement binary search