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dedicated visualizer

Quick Sort

Partitions the array around a pivot and recursively sorts the resulting partitions. This page keeps the runner, chart, and controls focused on a single algorithm so the walkthrough feels calmer than the overview page.

sortingintermediatebest O(n log n)worst O(n²)space O(log n)
pivotpartitioningdivide and conquerin-place

session controls

Compare this algorithm against a related one, turn on quiz mode, or keep the current state in a shareable URL.

current shareable URL

Copy the URL to preserve this exact dataset, target, compare mode, and quiz state.

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Want a different problem or visual mode? Jump back to the catalog and open another dedicated page.

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scenario presets

Load a focused input that reveals a specific behavior quickly instead of hand-editing every value first.

dataset controls

Use your own array, randomize a fresh one, or restore defaults. The same dataset is shared by both panels in compare mode.

Enter up to 12 integers. Values are normalized to the range 1–99 for clean visualization.

step 1 / 350% complete

current action

choose pivot

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run summary

Finished in 35 steps. Final order: 1, 2, 3, 5, 6, 7, 8, 9.

comparisons

14

swaps

11

sorted

8

steps

35

current explanation

Quick sort chooses a pivot, partitions around it, and recurses on both sides.

simple explanation

Pick one value, move smaller ones left and larger ones right.

pseudocode

1choose a pivot value
2scan the partition against the pivot
3swap smaller values into the left partition
4place the pivot into its final index
5recurse on both partitions

complexity card

best

O(n log n)

average

O(n log n)

worst

O(n²)

space

O(log n)

algorithm notes

intuition

Quick sort wins by placing pivots correctly and shrinking the unsorted problem quickly.

tradeoffs

  • Fast in practice with good pivots.
  • Worst-case time degrades to O(n²).
  • In-place but usually not stable.

when to use it

Use when average-case speed and in-place behavior matter more than stability.

interview tips

  • Discuss pivot strategy and how randomized pivots reduce worst-case risk.
  • Be ready to explain partition invariants.

what I learned building this

typed definitions

One algorithm schema now drives the catalog, counters, pseudocode, notes, and visual modes, which keeps the UI consistent as the lab grows.

replay over mutation

Precomputed steps made it much easier to synchronize explanations, metrics, quiz prompts, and scrubber playback without hidden state drifting out of sync.

portfolio framing

Shareable URL state, compare mode, and responsive layouts mattered as much as the algorithm logic because this page needs to teach clearly and still feel polished as a product.

more in this lane

Want a different take on the same problem family? These stay in the same category but change the strategy.