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anjan-dutta
anjan-dutta

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I Failed 5 Coding Interviews Despite Solving 200+ LeetCode Problems — Here's What Fixed It

Hey devs!

If you're grinding through coding interviews, you've probably been there: solving problem after problem on LeetCode, feeling prepared, only to blank out when it matters. That's exactly what happened to me. I crushed over 200 problems, but bombed five interviews in a row. The issue? Not lack of practice, but terrible retention.

In this post, I'll break down why one-and-done grinding fails, the science behind better learning, and the tool I built to automate it all. Let's dive in.

The Forgetting Curve: Why Your Brain Betrays You

Your brain isn't a hard drive — it forgets fast. According to the Ebbinghaus forgetting curve, we lose about 70% of new information within 24 hours if we don't review it. I was solving problems daily, but by interview time, most of that knowledge evaporated.

Think about it: Cramming 200 problems might give you a temporary boost, but without reinforcement, patterns like dynamic programming or graph traversals fade. In interviews, I could recognize the problem type but forgot the edge cases or optimizations. One-and-done practice = guaranteed forgetting.

The Solution: Spaced Repetition

Enter spaced repetition — a proven technique where you review material at increasing intervals to combat forgetting. It's like this:

  • Day 1: Learn/solve
  • Day 3: Quick review
  • Week 1: Deeper dive
  • Week 2: Test yourself
  • Month 1: Solidify

This is the same method med students use for anatomy or pharmacology. Studies show it can boost retention by 200-300% compared to massed practice. For coding, it means turning fleeting "aha" moments into automatic pattern recognition.

I needed this for DSA prep, but tracking reviews manually across LeetCode was a nightmare. So, I built my own system.

Introducing DSAPrep: Automated Spaced Repetition for LeetCode

I created DSAPrep.dev — a free web app that integrates spaced repetition directly into your LeetCode workflow. No more spreadsheets or forgotten reviews; it handles the scheduling for you.

Key Features

Mark Problems Complete: Link your LeetCode solves and flag them done in one click.
Auto-Scheduled Reviews: The app uses algorithms to schedule reviews at optimal intervals based on Ebbinghaus principles.
Adaptive Difficulty: Rate how tough a problem felt (easy/medium/hard), and it adjusts intervals — struggle more? Review sooner.
Daily Dashboard: Log in to see exactly what's due today. Solve, review, repeat.
Progress Tracking: Visualize retention with stats on completed reviews and mastery levels.

It's seamless: Solve on LeetCode, log in DSAPrep, and let it manage the rest. No manual tracking required.

Tech Stack

Built with:

  • Frontend: React for a responsive, interactive UI.
  • Backend: Node.js for handling scheduling logic and user data.
  • Database: MongoDB for storing problem logs, schedules, and ratings.

I made it free because interview prep is stressful enough without paywalls.

My Results: From 30% to 85% Retention

Before DSAPrep: 200+ problems solved, but retention hovered around 30%. Interviews felt like starting over.
After: Focused on 80 problems with spaced reviews. Retention jumped to ~85% (self-tracked via mock interviews). Patterns like two-pointer techniques or binary search trees became second nature.

The difference? In one interview, a tricky sliding window problem popped up — I'd reviewed it just a week prior via DSAPrep. Nailed it without panic.

Why This Works for Any Dev

Spaced repetition isn't magic; it's science-backed efficiency. If you're prepping for FAANG or startups, this shifts you from quantity to quality. Less burnout, more confidence.

Try it out at https://dsaprep.dev. Open to feedback — bug reports, feature ideas (like integration with other platforms), or even collab requests.

What's Your Biggest Interview Prep Challenge?

Retention? Nerves? System design? Drop a comment below — let's chat and level up together. Happy coding! 🚀

Top comments (1)

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anjandutta profile image
anjan-dutta

Next, I will post about how the algo works!