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1. Substring problem patterns:
- https://lnkd.in/giASrwds
2. Sliding window patterns:
- https://lnkd.in/gjatQ5pK
3. Two pointer patterns:
- https://lnkd.in/gBfWgHYe
4. Backtracking patterns:
- https://lnkd.in/g9csxVa4
5. Dynamic Programming patterns:
- https://lnkd.in/gbpRU46g
6. Binary search patterns:
- https://lnkd.in/gKEm_qUK
7. Tree patterns:
- https://lnkd.in/gKja_D5H
8. Graph patterns:
- https://lnkd.in/gKE6w7Jb
9. Monotonic patterns:
- https://lnkd.in/gdYahWVN
10. Bit manipulation patterns:
- https://lnkd.in/gmMMST5J
11. String question patterns:
- https://lnkd.in/gkNvEi8j
12. DFS and BFS patterns:
- https://lnkd.in/gPgpsgaQ
13. Fourteen Coding interview patterns:
- https://lnkd.in/gMZJVkFf
Practice Platforms:
- HackerRank
- LeetCode
- GeeksforGeeks
- takeUforward: https://lnkd.in/d-UNHu6B
- Piyush Agarwal: https://lnkd.in/dtBth5PF
- Code With Harry: https://lnkd.in/d-Uq-tCn
- Shrayansh Jain: https://lnkd.in/dUABhnbT
System Design KIT:
- https://lnkd.in/dte69Z5N
What Undercode Say
Mastering Data Structures and Algorithms (DSA) is a cornerstone for excelling in technical interviews. The patterns listed above provide a structured approach to solving complex problems efficiently. For instance, the Sliding Window technique is invaluable for optimizing problems involving arrays or strings, such as finding the maximum sum of a subarray of size k. Here’s a Python implementation:
def max_sum_subarray(arr, k):
max_sum = float('-inf')
window_sum = sum(arr[:k])
for i in range(len(arr) - k):
window_sum = window_sum - arr[i] + arr[i + k]
max_sum = max(max_sum, window_sum)
return max_sum
Similarly, Dynamic Programming is essential for problems like the Knapsack Problem, where you optimize resource allocation. Here’s a Python snippet:
def knapsack(weights, values, capacity): n = len(weights) dp = [[0] * (capacity + 1) for _ in range(n + 1)] for i in range(1, n + 1): for w in range(1, capacity + 1): if weights[i-1] <= w: dp[i][w] = max(values[i-1] + dp[i-1][w-weights[i-1]], dp[i-1][w]) else: dp[i][w] = dp[i-1][w] return dp[n][capacity]
For Tree Traversal, mastering DFS and BFS is crucial. Here’s a BFS implementation in Python:
from collections import deque def bfs(root): if not root: return [] queue = deque([root]) result = [] while queue: node = queue.popleft() result.append(node.val) if node.left: queue.append(node.left) if node.right: queue.append(node.right) return result
Linux commands like grep, awk, and `sed` are invaluable for processing text data, while Windows PowerShell commands like `Get-Process` and `Start-Service` streamline system management. For example, to find a process in Linux:
ps aux | grep <process_name>
In Windows, to start a service:
Start-Service -Name <service_name>
Consistency in practicing these patterns and commands will not only prepare you for interviews but also enhance your problem-solving skills in real-world scenarios. Keep exploring platforms like LeetCode and HackerRank, and leverage the provided resources to deepen your understanding.
**Additional Resources**:
Stay curious, keep learning, and keep coding!
References:
initially reported by: https://www.linkedin.com/posts/rajatgajbhiye_dsa-a-day-can-keep-interview-rejection-away-activity-7302175912597360641-0iHj – Hackers Feeds
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