Selection Sort Algorithm Explained Rust Programming | Step-by-Step Guide with Examples & Pseudocode
Sorting is an essential concept in computer science and programming. In this video, we explore Selection Sort, one of the simplest sorting algorithms. We will break down how it works step by step, analyze its time complexity, and implement it using pseudocode and practical examples.
🔹 What You’ll Learn:
✔️ What sorting is and why it's important
✔️ Difference between ascending and descending order
✔️ How Selection Sort works with a detailed walkthrough
✔️ Big O Notation (O(n²)) and performance analysis
✔️ Pseudocode for Selection Sort
✔️ Practical example with an unsorted array
📌 What is Sorting?
Sorting is the process of arranging elements in a specific order—either ascending (increasing) or descending (decreasing). It helps in optimizing searches and data organization.
Example:
🔹 Unsorted Array: [4, 3, 1, 2]
🔹 Ascending Order: [1, 2, 3, 4]
🔹 Descending Order: [4, 3, 2, 1]
🔥 Selection Sort Explained (Step-by-Step)
Selection Sort repeatedly finds the smallest (or largest) element from the unsorted section and swaps it with the first unsorted element.
📌 Step-by-Step Example:
1️⃣ Start with an unsorted array: [4, 3, 1, 2]
2️⃣ Find the smallest element and swap it with the first element
3️⃣ Repeat the process for the remaining unsorted elements
4️⃣ Continue until the array is fully sorted
💡 Pseudocode for Selection Sort:
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for i in range(0, size-1):
smallest = i
for j in range(i+1, size):
if array[j] array[smallest]:
smallest = j
swap(array[i], array[smallest])
This approach ensures that with each iteration, one element is placed in its correct position.
📊 Time Complexity Analysis (Big O Notation)
🔹 Worst-case Time Complexity: O(n²)
🔹 Best-case Time Complexity: O(n²)
🔹 Average Time Complexity: O(n²)
📌 Since Selection Sort always runs in O(n²), it's not the most efficient sorting algorithm for large datasets. However, it's useful for learning sorting fundamentals.
🛠 Selection Sort Example in Action
Let's take another array: [5, 10, 1, 4, 11] and apply Selection Sort.
✔️ Step 1: Find the smallest value → 1 and swap with 5 → [1, 10, 5, 4, 11]
✔️ Step 2: Find the next smallest value → 4 and swap with 10 → [1, 4, 5, 10, 11]
✔️ Step 3: The array continues sorting until fully sorted → [1, 4, 5, 10, 11]
🚀 Why Learn Selection Sort?
✅ Easy to understand and implement
✅ Works well for small datasets
✅ Helps in understanding the basics of sorting
👉 Want to see the full implementation? Watch the video till the end!
📌 Don't forget to LIKE 👍, SUBSCRIBE 🔔, and COMMENT 💬 if you found this helpful!
🔍 Related Topics:
🔹 Bubble Sort vs Selection Sort
🔹 Insertion Sort Algorithm
🔹 Quick Sort and Merge Sort
🔹 Sorting Algorithms Comparison
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