Algorithm Examples: Sorting, Searching, and More

📚 Quick Study Guide

• 🔍 Sorting Algorithms: Rearrange elements in a specific order (e.g., ascending or descending). Common examples include Bubble Sort, Insertion Sort, Merge Sort, and Quick Sort.
• ⏱️ Time Complexity: A way to measure how the runtime of an algorithm grows as the input size increases. Expressed using Big O notation (e.g., $O(n)$, $O(n^2)$, $O(log n)$).
• 🤝 Searching Algorithms: Find a specific element within a dataset. Common examples include Linear Search and Binary Search.
• 🌲 Binary Search: Requires a sorted dataset and works by repeatedly dividing the search interval in half.
• ✨ Algorithm Analysis: Evaluating algorithms based on factors like time complexity, space complexity, and correctness.
• 💾 Space Complexity: The amount of memory space required by an algorithm to execute.
• 💡 Optimization: Improving an algorithm to reduce its time or space complexity.

🧪 Practice Quiz

1. Question 1: Which sorting algorithm has an average time complexity of $O(n \log n)$?
   1. Bubble Sort
   2. Insertion Sort
   3. Merge Sort
   4. Selection Sort
2. Question 2: What is the primary requirement for using Binary Search?
   1. The data must be unsorted.
   2. The data must be sorted.
   3. The data must contain only positive numbers.
   4. The data must be stored in a linked list.
3. Question 3: Which of the following algorithms has the best time complexity for searching an element in a sorted array?
   1. Linear Search
   2. Binary Search
   3. Bubble Sort
   4. Insertion Sort
4. Question 4: What does Big O notation represent?
   1. The exact runtime of an algorithm.
   2. The maximum memory used by an algorithm.
   3. The growth rate of an algorithm's runtime as the input size increases.
   4. The number of lines of code in an algorithm.
5. Question 5: Which sorting algorithm works by repeatedly stepping through the list, comparing adjacent elements and swapping them if they are in the wrong order?
   1. Merge Sort
   2. Quick Sort
   3. Bubble Sort
   4. Insertion Sort
6. Question 6: What is space complexity?
   1. The time it takes for an algorithm to run.
   2. The amount of memory space required by an algorithm.
   3. The number of variables used in an algorithm.
   4. The number of loops in an algorithm.
7. Question 7: Which of the following is NOT a sorting algorithm?
   1. Merge Sort
   2. Binary Search
   3. Quick Sort
   4. Insertion Sort