Recursion-13 | Space Complexity (Theory)

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Understanding space complexity in recursion is essential for mastering algorithms and writing efficient code. In this video, we break down the two components of space usage in a recursive function:

🧠 1. Recursion-Related Space
👉 Learn how each recursive call adds a new frame to the call stack and how this impacts space complexity — especially in tail vs non-tail recursive functions.

📦 2. Non-Recursion-Related Space
👉 Explore how local variables, input sizes, and auxiliary data structures (like arrays, hashmaps, etc.) contribute to overall memory consumption.

📌 Whether you're preparing for coding interviews or simply aiming to deepen your understanding, this video gives you the clarity you need to analyze recursive functions confidently.

🔍 Examples included:

Factorial

Fibonacci

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Your queries:
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CHAPTERS
0:00 Introduction
0:14 Two Main Parts for Space Complexity in Recursion
0:50 What is Recursion Related Space
6:10 Stack Overflow
7:12 What is Non-Recursion Related Space
8:44 Overall Space Complexity
10:30 Conclusion





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