Sliding Window Algorithm – Fixed & Variable Length

📌 When to Use Sliding Window

• If a problem asks for:
  • Longest/shortest subarray with a condition
  • Fixed-length sum/subarray
  • Substring problems with characters/frequency
• And constraints mention:
  • Positive integers or lowercase letters
  • Contiguous window
• Then Sliding Window is your go-to strategy.

🔍 Keyword Clue: Subarray / Substring
🧠 Technique Hint: Start with two pointers → expand → shrink

---

🪟 Sliding Window Types

Type	Use Case Example	Window Behavior
Fixed Length	Max sum of k elements	Always move right pointer k
Variable Length	Longest substring with at most 2 distinct chars	Expand + shrink based on rule

---

🔒 Fixed-Length Window

Use when you’re given a fixed window size k and need to compute something over every window of size k.

✅ Constant time to slide window: +arr[i] - arr[i-k]
✅ Efficient for problems involving sums or frequency over exact-sized windows

---

🔓 Variable-Length Window

Use two pointers (start, end) to dynamically expand and shrink the window depending on conditions.

✅ Great for problems where you don’t know the window size up front
✅ Use when constraints say things like:

• “at most K characters”
• “longest subarray with sum ≤ target”
• “substring with K distinct characters”

---

💡 Key Insight

When you see problems like:

• “subarray”, “substring”
• Sum, max/min, count
• Length k, or conditions like “at most” or “exactly”

✅ Think Sliding Window!

---

🧠 Sliding Window Patterns

Pattern	Strategy Description
Fixed window of size k	Slide right pointer, remove left
Longest subarray with sum	Expand with end, shrink with start
Substring with distinct chars	Use hashmap to track frequency