🎯 Two Pointers — Two Sum

Approach — tap to compare

Work to solve

approach	n=1K	n=1M
Brute Force	499,500	499,999,500,000
Two Pointers	1,000	1,000,000
Hash Map	1,000	1,000,000

Live: 0 ops used

Two Pointers Pseudocode

1L ← 0;  R ← n-1
2while L < R:
3  sum ← a[L] + a[R]
4  if sum == target: return (L, R)
5  if sum < target: L ← L + 1
6  else: R ← R - 1

Speed: 50%Array size: 8

Two Pointers Visualizer: Two Sum, Brute Force vs Optimized

This Two Pointers simulator animates the classic Two Sum problem three ways so you learn the why, not just the trick. Start with the obvious brute-force double loop (O(n²)), then tap over to the two-pointer walk on a sorted array (O(n)) and the one-pass hash map (O(n)) and watch the live operation counter collapse. L and R pointers glide across numbered cells with a running equation readout — for example ‘12 + 2 = 14 = target’ — while a work-to-solve card projects the cost at n = 1,000 and n = 1,000,000, making the difference between quadratic and linear scaling concrete. A synced pseudocode panel highlights the exact line running each step.

What you can do in this simulation

Tap between three approaches — Brute Force, Two Pointers, and Hash Map — and watch the time/space complexity badges and the operation counter change instantly
Read the live equation readout as L and R pointers glide (for example a[L] + a[R] = 16 > 14 → move R left), so every pointer move has a visible reason
Use the Work-to-solve card to compare operations at n = 1,000 versus n = 1,000,000 and see why O(n²) becomes impractical at scale
Press Play, Pause, or Step to run the search at any speed or advance one comparison at a time, with a pseudocode panel highlighting the current line
Resize the array, generate a new solvable array, and complete missions that ask you to solve the same input with all three approaches

Concepts covered

two pointers technique · two sum problem · time complexity comparison · brute force vs optimized · hash map lookup · sorted array algorithms · O(n) vs O(n squared)

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approach

n=1K

n=1M

Brute Force

499,500

499,999,500,000

Two Pointers

1,000

1,000,000

Hash Map

1,000

1,000,000

Two Pointers Visualizer: Two Sum, Brute Force vs Optimized

What you can do in this simulation

Tap between three approaches — Brute Force, Two Pointers, and Hash Map — and watch the time/space complexity badges and the operation counter change instantly

Read the live equation readout as L and R pointers glide (for example a[L] + a[R] = 16 > 14 → move R left), so every pointer move has a visible reason

Use the Work-to-solve card to compare operations at n = 1,000 versus n = 1,000,000 and see why O(n²) becomes impractical at scale

Press Play, Pause, or Step to run the search at any speed or advance one comparison at a time, with a pseudocode panel highlighting the current line

Resize the array, generate a new solvable array, and complete missions that ask you to solve the same input with all three approaches