What to Practice for Coding Interviews
Most candidates know they need to practice. What they don't know is what to practice — and in what order. So they open LeetCode, sort by difficulty, and start from the top. Three months later, they've solved 200 problems and still bomb real interviews.
The problem isn't effort. It's selection. Practicing the wrong things, or practicing everything with equal weight, is how you get stuck. Coding interviews test a specific set of patterns across a specific set of topics — and if you don't know which ones you're weak in, you can't fix them.
This guide gives you a clear answer: what the core topics are, how interview-critical each one is, and how to figure out which ones you specifically need to work on.
TL;DR
- Coding interviews test 10 core topic areas — arrays, trees, graphs, dynamic programming, and more
- Most interviews at mid-to-large companies focus heavily on arrays/strings, trees, and graphs
- The mistake most candidates make is practicing randomly instead of targeting their weakest areas
- Knowing what you're weak in is as important as knowing what to practice in general
- SkillFlow tracks your proficiency across all 10 topics and picks your next problem based on where you're actually weak — for free
The 10 Core Topics Every Coding Interview Tests
Across hundreds of companies — from startups to FAANG — coding interviews draw from the same pool of topics. Here they are, roughly in order of how often they appear:
| Topic | Interview Frequency | Difficulty to Master |
|---|---|---|
| Arrays & Strings | ⭐⭐⭐⭐⭐ Very High | Low–Medium |
| Binary Trees | ⭐⭐⭐⭐⭐ Very High | Medium |
| Graphs & Matrices | ⭐⭐⭐⭐ High | Medium–High |
| Dynamic Programming | ⭐⭐⭐⭐ High | High |
| Linked Lists | ⭐⭐⭐ Medium | Low–Medium |
| Stacks & Queues | ⭐⭐⭐ Medium | Low |
| Heaps | ⭐⭐⭐ Medium | Medium |
| Backtracking | ⭐⭐⭐ Medium | High |
| Bit Manipulation | ⭐⭐ Lower | Medium |
| Number Theory & Math | ⭐⭐ Lower | Medium |
This is based on publicly available interview reports and platforms like Glassdoor's interview data. These patterns have been consistent for years.
What to Practice First (and Why Order Matters)
Not all topics are created equal in terms of interview frequency or difficulty curve. Here's a practical way to sequence your prep:
Phase 1 — High-frequency, lower barrier
Start with Arrays & Strings and Stacks & Queues. These appear constantly and reward the fewest hours per problem solved. Two-pointer patterns, sliding window, and prefix sums come up in nearly every on-site.
Phase 2 — Tree and graph fundamentals
Binary Trees and Graphs & Matrices are the backbone of most mid-to-senior coding rounds. DFS, BFS, traversal orders, and common tree patterns (LCA, diameter, path sum) appear in virtually every FAANG-level loop.
Phase 3 — Higher difficulty topics
Dynamic Programming and Backtracking are the hardest to build intuition for and take the most time per topic. Don't tackle these first — get solid fundamentals in trees and graphs, then move here.
Phase 4 — Specialized topics
Heaps, Linked Lists, Bit Manipulation, and Number Theory are worth covering but don't require the same depth as the first three phases. A solid understanding of common patterns is usually enough.
The Real Problem: Practicing Without Knowing Where You're Weak
Here's what nobody tells you about coding interview prep: the order you practice topics matters less than knowing which topics you're actually weak in.
Most candidates have significant gaps they don't know about. They feel comfortable with arrays because they've done 40 array problems — but their graph traversal is shaky and they've barely touched dynamic programming. They don't know this because nothing tells them.
If you finish a session having passed the test cases, you feel like you learned something. But passing test cases doesn't tell you whether your approach was correct, whether you understood the pattern, or whether you'd recognize the same pattern in a different problem.
This is the gap that makes prep feel like it's working when it isn't.
How to Figure Out What You Specifically Need
Generic practice lists are a starting point, not a plan. The most efficient path to interview readiness is targeted practice based on your actual performance — not a fixed topic order.
A few ways to diagnose where you're weak:
Track completion by topic, not just by count. 200 problems solved means nothing if 160 of them are arrays. Track how many problems you've done per topic and what your pass rate looks like.
Use timed sessions. Untimed practice inflates your confidence. If you can only solve a problem after 90 minutes of looking things up, you're not interview-ready on that topic.
Review your wrong answers by topic. What are you consistently missing? If you keep getting graph problems wrong, that's the gap — not a motivation problem.
Use a platform that tracks this automatically. SkillFlow maintains a proficiency score across all 10 coding topics and uses it to select your next problem automatically. If your dynamic programming score is your weakest, that's what you practice next. You don't have to self-diagnose — the platform does it for you and adapts as you improve.
What Most People Practice vs. What Actually Works
| Approach | What it looks like | Why it stalls |
|---|---|---|
| Random grinding | Sort by difficulty, pick whatever looks interesting | No pattern coverage, familiar topics get over-practiced |
| Topic-by-topic (fixed order) | Do all arrays, then all trees, then DP | Better structure, but doesn't account for where you specifically are weak |
| Company-specific cramming | Only practice problems from target company's tag | Narrow coverage, doesn't build transferable pattern recognition |
| Adaptive, weakness-targeted | Start with hardest gap, track proficiency over time | Most efficient — closes your actual gaps, not just checks boxes |
The adaptive approach consistently outperforms random grinding because it closes your specific gaps instead of reinforcing your existing strengths.
Honest Verdict
If you're just starting out: Begin with arrays/strings and trees. These two topics alone cover a significant portion of entry-level and mid-level coding rounds. Build those foundations first.
If you've been practicing for a while and still feel shaky: Stop adding more problems and start diagnosing which topics your wrong answers cluster around. Grinding more of the same thing won't fix a gap in a topic you've been avoiding.
If you want a system instead of a list: Use a platform that tracks your per-topic performance and picks what to practice for you. That's the fastest path from "I've been grinding for months" to "I'm actually ready."
Start practicing with adaptive topic targeting on SkillFlow →
Frequently Asked Questions
What topics come up most in coding interviews?
Arrays and strings, binary trees, and graphs are the most frequently tested topics across the widest range of companies. Dynamic programming appears heavily at top-tier companies (FAANG and similarly competitive firms). Linked lists, stacks, and queues are moderately common and relatively quick to cover.
How many problems do I need to practice to be ready?
There's no magic number, and problem count is a misleading metric. A candidate who has solved 80 problems across all 10 topics with genuine understanding is more ready than one who has solved 300 array problems randomly. Focus on coverage and comprehension per topic — not total count.
Should I practice easy, medium, or hard problems?
Most interview rounds at mid-to-large companies focus on medium difficulty problems. Easy problems help build pattern fluency early on. Hard problems are useful for top-tier companies once you have solid foundations. Don't skip mediums in pursuit of hard problems — most interviews don't require them.
What's the best way to know if I'm actually ready?
Timed, blind practice is the best signal. Take a problem you haven't seen before, set a 45-minute timer, and solve it without hints or looking anything up. If you can consistently reach working solutions within that window across multiple topics, you're in interview-ready shape. If you can't, note which topics you're failing on — that's your priority list.
Is it better to focus on one topic at a time or mix topics?
Starting topic-by-topic helps build pattern intuition early — but switching to mixed practice before your interviews is important. Real interviews don't tell you the topic. Once you've covered a topic's core patterns, mix it with others so you practice identifying the right approach from a cold problem, not from a label.
How do I know which topics I'm actually weak in?
The fastest way is to track your pass rate and time-to-solve by topic over time. If you're consistently slow or wrong on a particular topic, that's your gap. Platforms that track per-topic proficiency automatically — like SkillFlow — surface this without requiring you to self-analyze.
Practice smarter with SkillFlow — adaptive coding interview prep →