Quiz (4)
Grokking Algorithm Complexity and Big-O Rate this course Ask Author Contribute Back to course home 0% completed Vote For New Content Introduction Course Overview Basics of Algorithm Analysis Introduction to Algorithm Analysis Measuring Efficiency Functions and Their Growth Rates Asymptotic Notations Overview of Asymptotic Analysis Big-O Notation (O-notation) Big-Omega Notation (Ω-notation) Big-Theta Notation (Θ-notation) Little-o and Little-omega Notations Comparing Asymptotic Notations Time Complexity Analysis Understanding Time Complexity Analyzing Control Structures Analyzing Simple Algorithms Best, Worst, and Average Cases Constant Time: O(1) Linear Time: O(n) Quadratic Time: O(n²) Quiz Space Complexity Analysis Understanding Space Complexity Analyzing Space Complexity of Algorithms Constant Space: O(1) Linear Space: O(n) Quadratic Space: O(n²) Quiz Analyzing Recursive Algorithms Introduction to Recursion Recursion Tree Method Recurrence Relation Method Master Theorem Method Space Complexity Analysis of Recursive Algorithm Logarithmic Time and Space: O(log n) Linearithmic Time: O(n log n) Exponential Time and Space: O(2ⁿ) Quiz Data Structures and Complexity Analysis Array Linked List Hash Table and Set Stack and Queue Binary Search Tree Quiz Practical Applications and Case Studies Sorting Algorithms Graph Algorithms Dynamic Programming Algorithms Coding Interview Problems Trade-offs in Algorithm Design Quiz Question 1 What is the time complexity of accessing an element by its index in an array? A O(1) B O(n) C O(log n) D O(n 2 ) Question 2 What is the time complexity of searching for an element in a singly linked list? A O(1) B O(n) C O(log n) D O(n 2 ) Question 3 What is the space complexity of the following code that finds duplicates in an array using a HashSet? import java.util.HashSet; public class Solution { public boolean hasDuplicate(int[] arr) { HashSet<Integer> set = new HashSet<>(); for (int num : arr) { if (set.contains(num)) { return true; } set.add(num); } return false; } } A O(1) B O(n) C O(logn) D O(n 2 ) Question 4 What is the time complexity of the following code for reversing a linked list? class ListNode { int val; ListNode next; ListNode(int x) { val = x; } } public class Solution { public ListNode reverseList(ListNode head) { ListNode prev = null; ListNode current = head; while (current != null) { ListNode nextNode = current.next; current.next = prev; prev = current; current = nextNode; } return prev; } } A O(1) B O(n 2 ) C O(n) D O(log n) Question 5 What is the space complexity of the following code that checks for balanced parentheses using a stack? import java.util.Stack; public class Solution { public boolean isValid(String s) { Stack<Character> stack = new Stack<>(); for (char c : s.toCharArray()) { if (c == '(' || c == '{' || c == '[') { stack.push(c); } else { if (stack.isEmpty()) return false; char top = stack.pop(); if ((c == ')' && top != '(') || (c == '}' && top != '{') || (c == ']' && top != '[')) { return false; } } } return stack.isEmpty(); } } A O(n) B O(1) C O(log n) D O(n 2 ) Question 6 What is the time complexity of the following code that performs a depth-first traversal on a binary tree? public void dfs(TreeNode root) { if (root == null) return; System.out.println(root.val); dfs(root.left); dfs(root.right); } A O(1) B O(log n) C O(n 2 ) D O(n) Binary Search Tree Sorting Algorithms Mark as Completed On this page
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