LeetCode Anki: The Best Way To Actually Remember Coding Problems (Most People Don’t Do This) – Learn faster, stop re-solving the same questions, and turn LeetCode into long‑term muscle memory.
Leetcode anki means turning problems into spaced‑repetition flashcards so patterns stick. See how to capture core ideas, use active recall, and let apps like...
How Flashrecall app helps you remember faster. It's free
What Is “LeetCode Anki” And Why Do People Swear By It?
Alright, let’s talk about this “leetcode anki” thing, because it’s actually super simple: it just means using Anki-style flashcards to remember LeetCode problems, patterns, and solutions long term. Instead of solving a problem once and forgetting it a week later, you turn the key idea into a flashcard and review it with spaced repetition. That way, the patterns (like two pointers, sliding window, binary search on answer, etc.) stay in your head when you actually need them in an interview. And honestly, this is exactly the kind of workflow that apps like Flashrecall make way easier, because they handle the spaced repetition and active recall for you automatically.
Why “Solve More LeetCode” Stops Working After A Point
You’ve probably felt this:
- You grind a bunch of LeetCode problems
- You finally crack a hard one
- Two weeks later… you open a similar problem and your brain goes: “Wait… how did I do this again?”
That’s the core problem “leetcode anki” tries to fix.
LeetCode is great for practice, but terrible for retention if you just brute-force problems without reviewing them smartly. Your brain forgets details unless you actively recall them over time.
That’s where spaced repetition comes in:
- You review a problem’s idea after 1 day
- Then 3 days
- Then a week
- Then 2 weeks
- And so on, with increasing gaps
Each review is like telling your brain: “Yo, this is important, don’t delete this.”
Flashrecall basically automates that for you so you don’t need a spreadsheet or a manual review schedule.
How “LeetCode + Anki-Style Cards” Actually Works
Let’s keep this super practical. Here’s what “leetcode anki” looks like in real life:
1. You solve (or read) a LeetCode problem.
2. You identify the core idea, not just the code. Example:
- “Use sliding window with a hashmap to track counts”
- “Binary search on answer + feasibility check”
3. You turn that into a flashcard.
4. You review that card over time until it’s burned into your brain.
The cool part: with Flashrecall, this takes like 30 seconds per problem.
Why Flashcards Work So Well For LeetCode
There are two big learning techniques here:
1. Active Recall
Instead of re-reading solutions, you force yourself to remember:
- “What pattern solves this?”
- “What’s the time complexity?”
- “What’s the trick / edge case?”
This is way more powerful than passively scrolling through editorial pages.
2. Spaced Repetition
You don’t cram everything the night before an interview. You spread it out, and the app decides when to show you each card for maximum retention.
Flashrecall bakes both into the app:
- Every flashcard is built around active recall
- The spaced repetition engine automatically schedules your reviews
- You get study reminders so you don’t fall off the wagon
Why Use Flashrecall Instead Of Anki For LeetCode?
Since the keyword is literally “leetcode anki”, let’s be honest for a second: Anki is powerful, but it’s also kind of clunky, especially on mobile.
Here’s how Flashrecall compares for coding interview prep:
Flashrecall vs Anki For LeetCode
- Fast, modern, and easy to use on iPhone and iPad
- Built-in spaced repetition with auto reminders
- Create cards instantly from:
- Screenshots of LeetCode problems
- Text you paste from the prompt or editorial
- PDFs, YouTube links, or even audio
- Works offline, so you can review cards on the train, in bed, wherever
- You can chat with the flashcard if you’re unsure and want more explanation
- Free to start: perfect if you’re just testing the “leetcode anki” style workflow
- Very flexible, but the UX is kind of old-school
- Mobile apps are okay but not exactly smooth or modern
- Setting up decks, add-ons, and syncing can be annoying
- No built-in “chat about this card” feature
If you want something that just works on your phone, looks clean, and doesn’t make you fiddle with settings for an hour, Flashrecall is a much more chill experience:
Flashrecall automatically keeps track and reminds you of the cards you don't remember well so you remember faster. Like this :
How To Use Flashrecall For LeetCode Step‑By‑Step
Let’s walk through a simple workflow you can copy.
Step 1: Pick Your Problem
Say you’re doing:
- “Longest Substring Without Repeating Characters”
- Or “Number of Islands”
- Or “Meeting Rooms II”
After you solve it (or study the solution), ask:
- What’s the main pattern?
- What’s the trick or insight?
- Any edge cases that are easy to forget?
Step 2: Turn It Into A Flashcard
Open Flashrecall and create a card. You’ve got a few options:
- Manual card
- Front:
> “LeetCode: Longest Substring Without Repeating Characters – what pattern and data structure do we use?”
- Back:
> “Sliding window + hashmap (or array of size 128/256) to track last index of each char. Move left pointer when we see a duplicate within the current window.”
- From text
- Copy part of the problem statement or editorial
- Paste into Flashrecall and auto-generate cards from it
- From image
- Screenshot the LeetCode problem
- Import into Flashrecall and let it create flashcards from the image text
This is where Flashrecall feels really nice for “leetcode anki” – you don’t have to manually type everything if you don’t want to.
Step 3: Add A Few Smart Details
On the back of the card, you can also add:
- Time & space complexity
- Language-specific gotchas (e.g., Python dict vs Java HashMap)
- Edge cases: empty array, single element, negative numbers, etc.
Example:
> “Number of Islands – what’s the standard approach and complexity?”
> “DFS or BFS on the grid. Treat each ‘1’ as land, mark visited by mutating the grid or a visited set. Count connected components.
> Time: O(m n), Space: O(m n) in worst case for recursion/queue.”
Step 4: Let Spaced Repetition Do Its Thing
Once the card is in Flashrecall:
- You review it
- You rate how hard it was
- Flashrecall schedules the next review for you
You don’t need to decide:
- “Should I review all DP problems today?”
- “When did I last review sliding window?”
The app handles that, and you just open it when you get a study reminder.
What Kind Of LeetCode Cards Should You Make?
You don’t want to make a card for every single line of code. That’s overkill. Instead, focus on:
1. Patterns
- “When to use sliding window?”
- “When is two pointers better than a hashmap?”
- “Typical use cases for binary search on answer?”
- “Common DP patterns: knapsack, LIS, interval DP, etc.”
2. Problem-Specific Tricks
For example:
- “Trapping Rain Water – what’s the optimal approach?”
- “Why do we sort intervals for Merge Intervals?”
- “How do we detect a cycle in a linked list and find its start?”
3. Edge Cases & Pitfalls
- “What’s the edge case for reversing a linked list?”
- “What happens with empty input / single element / all negatives?”
- “Why do we use long instead of int in some overflow-prone problems?”
4. Complexity & Tradeoffs
- “Time/space complexity of each approach for a problem”
- “Why we choose one data structure over another”
Flashrecall is great here because you can:
- Make short, focused cards
- Review them offline
- Chat with the card if you’re like “wait, explain this again?”
Example Mini Deck For “LeetCode Anki” Style Practice
Here’s a quick sample of how a tiny deck might look:
- Front: “Pattern: Longest Substring Without Repeating Characters – what’s the approach?”
- Back: “Sliding window with hashmap/array to track last seen index. Move left pointer when duplicate seen in current window.”
- Front: “Pattern: Number of Islands – graph representation + algorithm?”
- Back: “Grid as implicit graph. Use DFS/BFS to explore connected ‘1’s. Count components.”
- Front: “When do we use binary search on answer instead of array index?”
- Back: “When answer is in a numeric range, and we can write a monotonic feasibility check (e.g., capacity to ship packages within D days).”
- Front: “Two pointers – typical use cases?”
- Back: “Sorted arrays, linked lists, partitioning, removing duplicates, checking palindromes, etc.”
You can build this kind of deck super fast in Flashrecall using text, screenshots, or manual cards.
Using Flashrecall Beyond LeetCode
The nice bonus: once you get into this “leetcode anki” style, you’ll probably start using the same approach for other stuff:
- System design concepts
- Database basics
- Language-specific quirks (Python, Java, C++)
- Even non-tech: exams, languages, medicine, business, school subjects
Flashrecall is built exactly for this kind of multi-topic learning:
- Works offline
- Free to start
- iPhone + iPad
- Handles images, text, PDFs, YouTube links, audio, and typed prompts
- Lets you chat with a flashcard if you want more explanation on something confusing
How To Start Today (Without Overcomplicating It)
If you’re overthinking how to do “leetcode anki” perfectly, don’t.
Do this:
1. Download Flashrecall:
👉 https://apps.apple.com/us/app/flashrecall-study-flashcards/id6746757085
2. Next time you solve a LeetCode problem, make just 1–2 flashcards:
- One for the main pattern
- One for the trick / edge case
3. Review them when the app reminds you.
That’s it.
No massive deck. No perfection. Just small, consistent reps.
In a few weeks, you’ll notice:
- You recognize patterns instantly
- You don’t “kind of remember” – you actually remember
- Interview questions feel familiar instead of scary
That’s the whole magic of mixing LeetCode with Anki-style spaced repetition, and Flashrecall just makes it way easier to stick with.
Frequently Asked Questions
Is Anki good for studying?
Anki is powerful but requires manual card creation and has a steep learning curve. Flashrecall offers AI-powered card generation from your notes, images, PDFs, and videos, making it faster and easier to create effective flashcards.
What's the fastest way to create flashcards?
Manually typing cards works but takes time. Many students now use AI generators that turn notes into flashcards instantly. Flashrecall does this automatically from text, images, or PDFs.
How do I start spaced repetition?
You can manually schedule your reviews, but most people use apps that automate this. Flashrecall uses built-in spaced repetition so you review cards at the perfect time.
What is active recall and how does it work?
Active recall is the process of actively retrieving information from memory rather than passively reviewing it. Flashrecall forces proper active recall by making you think before revealing answers, then uses spaced repetition to optimize your review schedule.
Related Articles
- Anki LeetCode Study System: 7 Powerful Flashcard Tricks To Finally Crack Coding Interviews Fast – Stop forgetting patterns and turn every LeetCode problem into long‑term muscle memory.
- Anki Mac OS Alternatives: The Best Way To Study Smarter On Your Mac (Most Students Don’t Know This) – If you’re using Anki on macOS and it feels clunky or outdated, this guide will show you a faster, easier way to do flashcards on your Mac and iPhone.
- Gamify Anki: 9 Powerful Ways To Make Studying Addictive (And The App Most Students Don’t Know About) – Turn boring flashcard grind into a game you actually want to play every day.
Research References
The information in this article is based on peer-reviewed research and established studies in cognitive psychology and learning science.
Cepeda, N. J., Pashler, H., Vul, E., Wixted, J. T., & Rohrer, D. (2006). Distributed practice in verbal recall tasks: A review and quantitative synthesis. Psychological Bulletin, 132(3), 354-380
Meta-analysis showing spaced repetition significantly improves long-term retention compared to massed practice
Carpenter, S. K., Cepeda, N. J., Rohrer, D., Kang, S. H., & Pashler, H. (2012). Using spacing to enhance diverse forms of learning: Review of recent research and implications for instruction. Educational Psychology Review, 24(3), 369-378
Review showing spacing effects work across different types of learning materials and contexts
Kang, S. H. (2016). Spaced repetition promotes efficient and effective learning: Policy implications for instruction. Policy Insights from the Behavioral and Brain Sciences, 3(1), 12-19
Policy review advocating for spaced repetition in educational settings based on extensive research evidence
Karpicke, J. D., & Roediger, H. L. (2008). The critical importance of retrieval for learning. Science, 319(5865), 966-968
Research demonstrating that active recall (retrieval practice) is more effective than re-reading for long-term learning
Roediger, H. L., & Butler, A. C. (2011). The critical role of retrieval practice in long-term retention. Trends in Cognitive Sciences, 15(1), 20-27
Review of research showing retrieval practice (active recall) as one of the most effective learning strategies
Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J., & Willingham, D. T. (2013). Improving students' learning with effective learning techniques: Promising directions from cognitive and educational psychology. Psychological Science in the Public Interest, 14(1), 4-58
Comprehensive review ranking learning techniques, with practice testing and distributed practice rated as highly effective

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