Most developers memorize 300+ coding problems before interviews.
The ones who actually get hired? They learn 8 patterns that cover 90% of everything.
I just published a complete DSA interview prep guide with 50 questions and answers — and the most important part isn't the solutions. It's the patterns behind them.
Here's what I mean:
The "Two Pointers" pattern solves sorted array problems.
The "Sliding Window" pattern solves substring/subarray problems.
The "Fast & Slow Pointers" pattern finds cycles AND middle elements.
The "Backtracking" pattern generates all combinations or permutations.
One pattern. Multiple problems. That's the difference between grinding and actually understanding.
The guide covers:
- Big-O notation and why interviewers care about it
- Arrays, Linked Lists, Stacks, and Queues with real code
- Trees and Graphs (including the classic "Number of Islands")
- 8 coding patterns that map to most interview problems
- Dynamic Programming broken down simply (starting with Climbing Stairs)
- The most common mistakes candidates make (and how to avoid them)
Quick example: Two Sum in O(n)
def two_sum(nums, target):
seen = {}
for i, num in enumerate(nums):
complement = target - num
if complement in seen:
return [seen[complement], i]
seen[num] = i
return []
No nested loops. Just one hash map and a single pass. That's what learning patterns looks like.
If Dynamic Programming always felt impossible, start with Q42 in the guide. It clicks when you see it as just Fibonacci with a twist.
👉 Full guide (free, no login needed): 50 DSA Interview Questions and Answers
Save this for your next interview prep session.
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