Sort Target
Algorithm
Speed
Normal ~12s · 34 ms ×2
Powersort(2018)
▶ Try this Source
O(n log n) ✓ Stable ✗ In-place
🔧 How it works

Scans the input for natural runs like Timsort, but schedules merges by computing a "power" value from each run's position and size to determine the provably optimal merge order.

🎯 Key property

The power-based scheduling guarantees a comparison count close to the information-theoretic lower bound on structured inputs, a proven improvement over Timsort's heuristic stack rules when runs have irregular lengths.

👁 Watch for
  • Compare adjacent pairs are tested during the run-detection scan; a power value is computed from each run's position in the array and its length relative to its neighbour
  • RangeCopy when two runs are merged, the shorter is copied into a buffer before the merge begins
  • IndexWrite values from the buffer are written back into the original array as the merge proceeds
🕰 History 🌳 Lineage ⚡ Optimization
UsesRun DetectionCopy-Smaller StrategyHybrid SwitchingMerge Order Optimization
Initial State
This is the array before sorting. Follow Powersort step by step.
Main Array
25
0
26
1
27
2
28
3
29
4
30
5
31
6
32
7
24
8
23
9
22
10
21
11
20
12
19
13
18
14
17
15
33
16
34
17
35
18
36
19
37
20
38
21
39
22
40
23
16
24
15
25
14
26
13
27
12
28
11
29
10
30
9
31
41
32
42
33
43
34
44
35
45
36
46
37
47
38
48
39
8
40
7
41
6
42
5
43
4
44
3
45
2
46
1
47
57
48
58
49
59
50
60
51
61
52
62
53
63
54
64
55
56
56
55
57
54
58
53
59
52
60
51
61
50
62
49
63
RunsDetect 0 runs on stack
Waiting for run detection…
0 / 715 ops ( 0.0%) 0.0%
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