Min Sum Contiguous Subarray
Computes minimum subarray sum by inverting Kadane logic.
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Reference implementation (Python)
def min_subarray(arr):
min_so_far = curr = arr[0]
for x in arr[1:]:
curr = min(x, curr + x)
min_so_far = min(min_so_far, curr)
return min_so_farEmbed this visualization
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<iframe src="/embed/min-contiguous-subarray" width="100%" height="380" style="border:1px solid #e6e8ec;border-radius:14px" loading="lazy" title="3D algorithm visualization by CodeWithMunnaX"></iframe>Frequently asked
What is the time and space complexity of Min Sum Contiguous Subarray?
Min Sum Contiguous Subarray runs in O(n) time and O(1) auxiliary space.
Is the Min Sum Contiguous Subarray visualizer free?
The core 3D visualizer, Web Audio chimes and step intuition are free. A one-time ₹49 Pro Pass unlocks advanced algorithms, large custom arrays, Battle Arena and reel export.
Which companies ask Min Sum Contiguous Subarray in interviews?
Min Sum Contiguous Subarray shows up in interviews at Spotify, Google, Airbnb.
How does the 3D visualization of Min Sum Contiguous Subarray work?
Each array value becomes a 3D pillar whose height maps to its value. Comparisons glow amber, swaps flash red, and settled elements lock green while a floating pointer badge tracks the active index — synchronized line-by-line with the Python code.