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Two Pointers

Converging or parallel pointers scan arrays and strings in linear time, replacing nested O(n²) loops with single O(n) sweeps. Most useful when the data is sorted or has a symmetric structure (palindromes, pair sums).

27 problems 11 Easy 10 Medium 6 Hard

Two-pointer techniques use one or two indices to scan a sequence in linear time. The 'converging' variant has pointers walking inward from both ends until they meet — ideal for sorted arrays, palindromes, and pair-sum problems. The 'parallel' variant has both pointers moving in the same direction at different speeds or with different responsibilities, classically a read-pointer paired with a write-pointer for in-place filtering and compression.

The pattern's power is what it eliminates: many problems that look O(n²) (find every pair satisfying a property) collapse to O(n) once you exploit sortedness or symmetry to advance both pointers monotonically.

When to reach for this pattern

  • Input is sorted (or trivially sortable) and you need a pair/triplet with a sum or difference property
  • Palindrome or symmetric-structure check
  • In-place compaction of an array (remove duplicates, remove a value)
  • Merging two sorted sequences
  • Comparing the structure of two strings (subsequence check)

Canonical template 

// converging two-pointer
int l = 0, r = nums.size() - 1;
while (l < r) {
    int sum = nums[l] + nums[r];
    if (sum == target) return {l, r};
    if (sum < target) ++l;
    else --r;
}

// write-pointer (in-place filter)
int w = 0;
for (int x : nums)
    if (keep(x)) nums[w++] = x;
return w;

C++ · adapt the names and types to your problem.

Common pitfalls

  • Using <= instead of < in the converging loop can compare an element with itself
  • Forgetting to dedup adjacent equal values when emitting pairs / triplets
  • Incrementing both pointers on a match in problems where the count of matches matters
  • Treating r - l as the count instead of the gap — off-by-one on inclusive ranges

Related patterns

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Problems (27)

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