Spaced Repetition for Coding Interviews: The Complete Guide
How to apply the most effective learning technique to algorithm study. Stop relearning the same concepts.
Master the science of learning. Spaced repetition, active recall, and interleaving—the evidence-based techniques top engineers use to retain algorithms permanently.
These are the Learning Strategies for Software Engineers that actually work. Stop "grinding" and start learning with evidence-based protocols: Spaced Repetition, Active Recall, Interleaving, and the Feynman Technique. Master the neuroscience of retention and never forget an algorithm again.
In 1885, Hermann Ebbinghaus discovered the "Forgetting Curve." His research showed that humans forget 50% of new information within 1 hour and 70% within 24 hoursunless they actively work to retain it.
This is why you can watch a 3-hour tutorial on Dynamic Programming, feel like you understand it, and then be completely lost the next day. Your brain categorized the information as "temporary noise" and flushed it. The techniques below are designed to signal to your brain that this information is worth keeping.
Reading about patterns is passive. Our story-based course forces you to apply them in real scenarios.
Start the AdventureSRS is the antidote to the forgetting curve. Instead of reviewing everything every day (inefficient) or never reviewing (ineffective), SRS algorithms schedule reviews at the exact moment you are about to forget.
The key insight is that each successful retrieval strengthens the memory trace and extends the time until the next review is needed. After 5-6 well-timed reviews, information moves to permanent storage.
Passive learning (reading, watching) is easy and comfortable. Active learning (producing, testing) is hard and uncomfortable. Learning happens in the struggle. The effort of retrieving information strengthens the neural pathways.
The "peek and close" technique is crucial. Looking at the full solution kills the learning process because your brain thinks "I got it" without actually building the neural pathways to reproduce it.
Block practice (doing 50 Array problems in a row) creates false confidence. You perform well during practice but fail during interviews. Why? Because on interview day, you will not know the topic ahead of time.
Interleaving means mixing up topics. Do one Graph problem, then one Dynamic Programming problem, then one Array problem. This forces your brain to practice the most important interview skill: Pattern Recognition—figuring out which tool to use, not just how to use it.
This technique is simple but powerful: Ask "why" relentlessly. Don't just memorize that "Two Sum uses a Hash Map." Ask yourself:
This forces you to understand the reasoning behind the solution, not just the code. When you encounter a variation of the problem, you can adapt because you understand the principles.
Named after physicist Richard Feynman, this technique exposes gaps in your understanding by forcing you to explain concepts in simple terms.
If you cannot explain it simply, you do not understand it well enough. The interview is essentially a Feynman test—can you explain your solution clearly to the interviewer?
These common study habits feel productive but actively harm your learning:
The articles below explore each of these techniques in depth. If you are struggling with retention, start with Spaced Repetition. If you understand concepts but cannot produce solutions, focus on Active Recall.
How to apply the most effective learning technique to algorithm study. Stop relearning the same concepts.
Why you forget algorithms and how Feynman's 4-step method, enhanced with AI, builds deep understanding that survives interview pressure.
Stop reading and start coding. Our course uses an interactive terminal and spaced repetition to burn these concepts into your long-term memory.
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