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Here’s a comprehensive list of 40 Data Structures and Algorithms (DSA) questions frequently asked in technical interviews, along with practical implementations in Python, C++, and Linux commands where applicable.
1. Reverse a Linked List
class Node: def <strong>init</strong>(self, data): self.data = data self.next = None def reverse_linked_list(head): prev = None current = head while current: next_node = current.next current.next = prev prev = current current = next_node return prev
- Find the Middle Element of a Linked List
def find_middle(head): slow = fast = head while fast and fast.next: slow = slow.next fast = fast.next.next return slow.data
3. Implement a Stack Using Arrays
class Stack: def <strong>init</strong>(self): self.stack = [] def push(self, item): self.stack.append(item) def pop(self): return self.stack.pop() if self.stack else None
4. Implement a Queue Using Linked Lists
class QueueNode: def <strong>init</strong>(self, data): self.data = data self.next = None class Queue: def <strong>init</strong>(self): self.front = self.rear = None def enqueue(self, item): new_node = QueueNode(item) if not self.rear: self.front = self.rear = new_node return self.rear.next = new_node self.rear = new_node def dequeue(self): if not self.front: return None temp = self.front self.front = temp.next if not self.front: self.rear = None return temp.data
5. Find Factorial Using Recursion
def factorial(n): return 1 if n == 0 else n factorial(n - 1)
6. Binary Search in an Array
def binary_search(arr, target): low, high = 0, len(arr) - 1 while low <= high: mid = (low + high) // 2 if arr[bash] == target: return mid elif arr[bash] < target: low = mid + 1 else: high = mid - 1 return -1
7. Find Largest/Smallest Element in an Array
Linux command to find largest number in a file
awk 'BEGIN {max = 0} {if ($1 > max) max = $1} END {print max}' numbers.txt
8. Merge Sort Implementation
def merge_sort(arr): if len(arr) > 1: mid = len(arr) // 2 left = arr[:mid] right = arr[mid:] merge_sort(left) merge_sort(right) i = j = k = 0 while i < len(left) and j < len(right): if left[bash] < right[bash]: arr[bash] = left[bash] i += 1 else: arr[bash] = right[bash] j += 1 k += 1 while i < len(left): arr[bash] = left[bash] i += 1 k += 1 while j < len(right): arr[bash] = right[bash] j += 1 k += 1
9. Quick Sort Implementation
def quick_sort(arr): if len(arr) <= 1: return arr pivot = arr[len(arr) // 2] left = [x for x in arr if x < pivot] middle = [x for x in arr if x == pivot] right = [x for x in arr if x > pivot] return quick_sort(left) + middle + quick_sort(right)
- Detect a Cycle in a Linked List (Floyd’s Algorithm)
def has_cycle(head): slow = fast = head while fast and fast.next: slow = slow.next fast = fast.next.next if slow == fast: return True return False
You Should Know:
- Linux Commands for Data Processing:
Sort a file numerically sort -n data.txt Find unique elements uniq sorted_data.txt Count occurrences awk '{count[$1]++} END {for (word in count) print word, count[bash]}' words.txt -
Windows CMD for File Operations:
:: Find largest file in a directory dir /O-S /A-D</p></li> </ul> <p>:: Search for a string in files findstr "search_term" .txt
What Undercode Say:
Mastering these DSA questions is crucial for cracking coding interviews. Practice implementing them in multiple languages and optimize for time and space complexity. Use Linux commands for quick data manipulation and Windows CMD for file operations.
Prediction:
As AI-driven interviews rise, expect automated DSA assessments with real-time code evaluation.
Expected Output:
Reversed Linked List: 5 -> 4 -> 3 -> 2 -> 1 Middle Element: 3 Binary Search Index: 4 Merge Sort Result: [1, 2, 3, 4, 5]
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