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DSA · Theory

Sliding Window Maximum (Maximum of all Subarrays of size K)

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Theory

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Sliding Window Maximum (Maximum of all Subarrays of size K)

Sliding Window Maximum (Maximum of all Subarrays of size K) sits in lab hour. Arun’s job is Arun walking through Sliding Window Maximum Maximum of all Subarrays of size K. Write that first.

Keep Sliding Window Maximum (Maximum of all Subarrays of size K) small. Arun should finish Arun walking through Sliding Window Maximum Maximum of all Subarrays of size K in a few lines, not a 40-line dump.

Skip Sliding Window Maximum (Maximum of all Subarrays of size K) and skipping the failure case for Sliding Window Maximum Maximum of all Subarrays of size K shows up in lab hour.

Use Sliding Window Maximum (Maximum of all Subarrays of size K) when Arun walking through Sliding Window Maximum Maximum of all Subarrays of size K must stay clear. If a simpler DSA step works, use that instead.

Don’t do this with Sliding Window Maximum (Maximum of all Subarrays of size K): skipping the failure case for Sliding Window Maximum Maximum of all Subarrays of size K. Interviewers spot it in ten seconds.

After Sliding Window Maximum (Maximum of all Subarrays of size K), Arun should still remember skipping the failure case for Sliding Window Maximum Maximum of all Subarrays of size K.

One breath for Sliding Window Maximum (Maximum of all Subarrays of size K), then Arun walking through Sliding Window Maximum Maximum of all Subarrays of size K, then skipping the failure case for Sliding Window Maximum Maximum of all Subarrays of size K. Sit down.

Exam tip

For Sliding Window Maximum (Maximum of all Subarrays of size K): definition + lab hour + one failure.

Example

# Sliding Window Maximum (Maximum of all Subarrays of size K)
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)

Sliding Window Maximum (Maximum of all Subarrays of size K): dry-run [4, 1, 3]. Say the list after one step.

Short notes

  • DefSliding Window Maximum (Maximum of all Subarrays of size K) — Arun uses it for Arun walking through Sliding Window Maximum Maximum of all Subarrays of size K in lab hour.
  • RuleSliding Window Maximum (Maximum of all Subarrays of size K) → one Sliding Window Maximum Maximum of all Subarrays of size K step Arun can write from memory.
  • RememberSliding Window Maximum (Maximum of all Subarrays of size K) + a dry-run table (lab hour).
  • UseSliding Window Maximum (Maximum of all Subarrays of size K) in lab hour (Arun walking through Sliding Window Maximum Maximum of all Subarrays of size K).
  • TrapSliding Window Maximum (Maximum of all Subarrays of size K) — skipping the failure case for Sliding Window Maximum Maximum of all Subarrays of size K.
  • ExSliding Window Maximum (Maximum of all Subarrays of size K) → Arun walking through Sliding Window Maximum Maximum of all Subarrays of size K.

Questions

1

Define Sliding Window Maximum (Maximum of all Subarrays of size K) without jargon. Then point at Arun walking through Sliding Window Maximum Maximum of all Subarrays of size K.

2

Where does Sliding Window Maximum (Maximum of all Subarrays of size K) show up in lab hour?

3

What trap does Arun hit with Sliding Window Maximum (Maximum of all Subarrays of size K)?

4

Dry-run one Sliding Window Maximum Maximum of all Subarrays of size K step Arun can write from memory and say the result.

Previous← Self-Balancing Binary Search TreesNextAVL Trees Operations →
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