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DSA · Theory

Longest common substring

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Theory

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Longest common substring

Don’t start Longest common substring with jargon. Start with folder on disk. That is the whole point.

Longest common substring order — meaning → left < root < right → one limit. Dumping ten features helps nobody.

Skip Longest common substring and unbalanced BST becoming a list shows up in a file explorer.

Kabir ships Longest common substring in a file explorer. That is the use case worth saying.

If folder on disk breaks under Longest common substring, check unbalanced BST becoming a list first.

Place Longest common substring next to nearby DSA work — left < root < right is the link.

One breath for Longest common substring, then folder on disk, then unbalanced BST becoming a list. Sit down.

Diagram
      8
     / \
    3   10
   / \
  1   6
Exam tip

Board: folder on disk. Dry-run Longest common substring. Name the trap: unbalanced BST becoming a list.

Example

# Longest common substring
data = [4, 1, 3]
print("start", data)
if data[0] > data[1]:
    data[0], data[1] = data[1], data[0]
print("after one step", data)

Longest common substring: dry-run [4, 1, 3]. Say the list after one step.

Short notes

  • DefLongest common substring — Kabir uses it for folder on disk in a file explorer.
  • RuleLongest common substring → left < root < right.
  • RememberLongest common substring + time vs memory (a file explorer).
  • UseLongest common substring in a file explorer (folder on disk).
  • TrapLongest common substring — unbalanced BST becoming a list.
  • ExLongest common substring → folder on disk.

Questions

1

In one breath: what does Longest common substring do for Kabir?

2

Name one DSA screen/job that needs Longest common substring.

3

What trap does Kabir hit with Longest common substring?

4

Dry-run left < root < right and say the result.

Previous← Quick Sort Using Hoare's PartitionNextLongest Repeated Substring →
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