Every year, millions of engineers apply to top tech companies — and most of them fail the coding interview. Not because they lack talent, but because they practiced the wrong things.

They grind hundreds of LeetCode problems in silence, memorize solutions they’ll forget under pressure, and walk into interviews without ever having rehearsed the skills that actually get evaluated: structured thinking, clear communication, and calm execution under a timer.

This is the guide we wish existed when we were preparing. It covers what interviewers actually score, a concrete preparation roadmap from beginner to advanced, study plans for every timeline, and the mistakes that cost candidates offers — even when they know the answer.

Want to skip ahead to practicing? Start a mock coding interview now →

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How to Prepare for a Coding Interview: Step by Step

1. Learn the fundamentals — Master arrays, hash maps, trees, graphs, and core algorithms like BFS/DFS and dynamic programming.
2. Study problem-solving patterns — Learn to recognize the 8 key patterns (two pointers, sliding window, binary search, BFS/DFS, DP, backtracking, stack, hash map) that cover 80% of interview questions.
3. Practice under timed conditions — Solve medium-difficulty problems in 45 minutes or less while explaining your approach out loud.
4. Do mock interviews — Simulate real interview pressure with a peer, coach, or AI interviewer. Practice communication, hint handling, and debugging.
5. Review and consolidate — Track your weak areas, re-solve failed problems, and rest before the real interview.

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What Interviewers Really Evaluate

Before optimizing your preparation, understand what you’re being scored on. The evaluation rubric at top companies weights process more than output:

Dimension	What Interviewers Watch For	Weight
Problem Understanding	Clarifying questions, restating constraints, identifying edge cases	~15%
Approach & Reasoning	Proposing a brute-force first, reasoning toward optimization, discussing tradeoffs	~25%
Communication	Thinking out loud, explaining decisions, responding to hints	~25%
Code Quality	Clean, readable code with proper naming and logical structure	~20%
Testing & Debugging	Validating with examples, catching bugs, handling edge cases	~15%

Notice that correctness is not a separate category — it’s a byproduct of doing all five well. Most interviewers would rather see a candidate who communicates clearly and reaches 80% of the solution than one who silently produces a perfect answer.

This has a direct implication for how you prepare: solving problems is necessary but not sufficient. You also need to practice the performance.

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Coding Interview Roadmap: Beginner to Advanced

Whether you’re a bootcamp graduate or a senior engineer switching companies, your preparation follows the same trajectory — just at different speeds.

Beginner (New to DSA)

1. Learn the core data structures: arrays, hash maps, linked lists, stacks, queues
2. Understand the core algorithms: binary search, BFS/DFS, basic sorting
3. Solve 50–75 easy problems to build fluency
4. Focus on reading and understanding editorials, not speed

Intermediate (Comfortable with Basics)

1. Learn to recognize problem patterns (two pointers, sliding window, DP, backtracking)
2. Solve 75–100 medium problems across all pattern categories
3. Begin timed practice (45 minutes per problem)
4. Start mock interviews to practice communication

Advanced (Interview-Ready, Refining)

1. Focus on medium problems with pattern combinations and edge cases
2. Practice explaining your reasoning out loud under time pressure
3. Do mock interviews 2–3× per week
4. Review and plug specific weak areas

The key insight: beginners should spend 80% of their time learning, intermediates 50/50 learning and practicing, and advanced candidates 80% practicing. Most people over-index on learning and under-index on simulation.

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Coding Interview Study Plan

Not everyone has three months. Here are three structured study plans depending on your timeline. Pick the one that matches your starting point, and follow it daily.

2-Week Coding Interview Prep Plan

Best for: Engineers with solid CS fundamentals who need a focused refresh before upcoming interviews.

Daily commitment: 2–3 hours

Day	Focus	What to Do
1	Arrays & Hashing	Solve 4 medium problems: two-sum variants, frequency counting, group anagrams
2	Two Pointers & Sliding Window	Solve 4 problems: container with most water, longest substring without repeating chars
3	Stacks & Binary Search	Solve 4 problems: valid parentheses, search in rotated sorted array
4	Trees (BFS/DFS)	Solve 4 problems: level order traversal, validate BST, lowest common ancestor
5	Graphs	Solve 3 problems: number of islands, clone graph, course schedule
6	Dynamic Programming	Solve 3 problems: climbing stairs, coin change, longest increasing subsequence
7	Timed practice	Re-solve 3 problems from days 1–6 under 45-minute timer. Talk out loud.
8	Mock interview #1	Full 45-minute simulation. Record yourself or use an AI interviewer.
9	Review + weak patterns	Re-do problems you failed or timed out on. Study the editorial solutions.
10	Mock interview #2	Focus on communication: explain every step before writing code.
11	Mixed timed practice	3 random medium problems, 45 minutes each, back-to-back.
12	Mock interview #3	Simulate a real phone screen: one problem, 45 minutes, full explanation.
13	Final weak spots	Review your tracking spreadsheet. Re-solve your 3 weakest problems.
14	Rest + light review	Skim your notes. No new problems. Rest your brain for the real thing.

Checkpoint: By day 14, you should be able to solve a medium problem in ≤ 30 minutes while explaining your approach out loud.

Use the Grind 75 list sorted by frequency to prioritize the highest-ROI problems.

1-Month Coding Interview Prep Plan

Best for: Candidates with some DSA experience who want thorough, structured preparation.

Daily commitment: 1.5–2 hours

Week 1 — Core Data Structures

Day	Topics	Problems
Mon	Arrays, Strings	3 easy/medium: two sum, best time to buy stock, valid anagram
Tue	Hash Maps	3 medium: group anagrams, top K frequent, longest consecutive sequence
Wed	Linked Lists	3 problems: reverse list, merge two sorted, detect cycle
Thu	Stacks & Queues	3 problems: valid parentheses, min stack, daily temperatures
Fri	Review	Re-solve any problems you struggled with. Start your tracking spreadsheet.
Sat–Sun	Catch-up or rest	Light review only

Week 2 — Trees, Graphs & Recursion

Day	Topics	Problems
Mon	Binary Trees	3 problems: invert tree, max depth, level order traversal
Tue	BSTs	3 problems: validate BST, kth smallest, lowest common ancestor
Wed	Graphs (BFS/DFS)	3 problems: number of islands, Pacific Atlantic, course schedule
Thu	Recursion & Backtracking	3 problems: subsets, permutations, combination sum
Fri	Review	Re-solve failures. Update your spreadsheet with patterns used.
Sat–Sun	Catch-up or rest

Week 3 — Advanced Patterns & Timed Practice

Day	Topics	Problems
Mon	Sliding Window	3 timed problems: longest substring, minimum window substring
Tue	Binary Search	3 timed problems: search rotated array, find minimum in rotated array
Wed	Dynamic Programming	3 timed problems: climbing stairs, coin change, longest increasing subsequence
Thu	Heaps & Intervals	3 timed problems: kth largest, merge intervals, meeting rooms II
Fri	Mock interview #1	Full simulation. Focus on talking through your approach.
Sat–Sun	Review weak areas

Week 4 — Simulation Mode

Day	Focus
Mon	Mock interview #2 — focus on time management
Tue	3 random medium problems, back-to-back, timed
Wed	Mock interview #3 — focus on hint handling
Thu	Review your 5 weakest problems from the spreadsheet
Fri	Light mock interview — 1 problem, focus on confidence
Sat	Rest. Skim notes only.
Sun	Interview prep: test environment, prepare desk, sleep early.

Checkpoint: By week 4, you should be able to identify the correct pattern within 2 minutes of reading a new medium problem.

3-Month Coding Interview Prep Plan

Best for: Career switchers, bootcamp graduates, or anyone building DSA skills from scratch.

Daily commitment: 1–2 hours

Month 1 — Build Strong Fundamentals

Goal: Get comfortable solving easy problems and understand core data structures.

Week	Focus	Daily Target
1	Arrays, Strings, Hash Maps	2–3 easy problems. Read editorials after every problem.
2	Linked Lists, Stacks, Queues	2–3 easy problems. Implement each data structure from scratch once.
3	Trees (binary trees, BSTs, traversals)	2–3 easy/medium problems. Master BFS and DFS recursion.
4	Graphs, Heaps, basic sorting	2–3 easy/medium problems. Understand adjacency list representation.

Month 1 checkpoint: Can solve most easy problems without hints. Understand core data structure operations and their time complexity.

Resources: NeetCode Roadmap, LeetCode Top Interview 150

Month 2 — Pattern Recognition & Speed

Goal: Shift from “learning data structures” to “recognizing problem patterns.”

Week	Focus	Daily Target
5	Two Pointers, Sliding Window	2–3 medium problems per day, timed at 45 minutes
6	Binary Search, BFS/DFS variants	2–3 medium problems. Start noting which pattern each problem uses.
7	Dynamic Programming (1D and 2D)	2–3 medium problems. Focus on identifying subproblem structure.
8	Backtracking, Intervals, Greedy	2–3 medium problems. Complete your pattern coverage.

Month 2 checkpoint: Can recognize the correct pattern for most medium problems within 2–3 minutes. Solving speed is improving.

Resources: NeetCode 150, LeetCode Patterns

Month 3 — Interview Simulation

Goal: Transition from silent problem-solving to interview-ready performance.

Week	Focus	Daily Target
9	Verbal practice	Solve 2 problems per day while explaining every step out loud.
10	Mock interviews	3 mock interviews this week. Use Intervu, peers, or recorded self-practice.
11	Mixed simulation	Alternate between mock interviews and timed solo problems. Focus on weak patterns.
12	Final polish	2 mock interviews. Light review of notes. Rest the final 2 days.

Month 3 checkpoint: Can comfortably solve medium problems in 25–30 minutes while communicating clearly. Ready for real interviews.

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Coding Interview Checklist

Use this checklist before your first real interview. If you can check every item, you’re ready.

1. Can solve medium-difficulty problems in 30 minutes or less
2. Can identify the correct pattern within 2 minutes of reading a new problem
3. Can explain your approach clearly before writing any code
4. Can analyze time and space complexity and explain the tradeoffs
5. Have completed at least 3–5 mock interviews with feedback
6. Can respond to interviewer hints naturally without freezing
7. Can debug your own code by tracing through examples step by step
8. Have tested your coding environment (webcam, mic, editor, internet)
9. Know your chosen language’s standard library for common interview operations
10. Can solve 2–3 problems back-to-back without burning out

If you can check all ten, you’re interview-ready.

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The 4-Phase Preparation Framework

The biggest mistake candidates make is treating preparation as a single activity — “do LeetCode problems.” In reality, interview readiness requires building four distinct skills in sequence.

Phase 1: Build the Foundations (Week 1–2)

Before you can solve interview problems efficiently, you need fluency with the building blocks.

Core data structures to master:

• Arrays, strings, and hash maps (the bedrock of ~60% of interview questions)
• Linked lists, stacks, and queues
• Trees (binary trees, BSTs, tries)
• Graphs (adjacency lists, BFS, DFS)
• Heaps and priority queues

Core algorithms and techniques:

• Sorting and binary search
• Recursion and backtracking
• Dynamic programming (top-down and bottom-up)
• Sliding window and two pointers
• BFS/DFS for trees and graphs

How to practice this phase:

• Solve 3–5 problems per day, focusing on understanding — not speed
• After solving, read the editorial and at least one alternative solution
• After each problem, write down the time/space complexity and why — this trains the analysis muscle interviewers test
• Keep a spreadsheet: problem name, pattern used, whether you solved it unaided, and what tripped you up. Review failures the next day

A structured problem list like the Grind 75 is ideal for this phase — it’s ordered by difficulty and covers the essential patterns systematically.

Resources for this phase:

• NeetCode Roadmap — visual map of topics with curated problems for each
• LeetCode Top Interview 150 — LeetCode’s own curated list
• Tech Interview Handbook — free guide covering DSA fundamentals and study plans

Phase 2: Pattern Mastery (Week 3–4)

Once you have the fundamentals, shift from learning data structures to recognizing problem patterns. This is the single biggest unlock for interview performance.

The key patterns that cover ~80% of coding interview questions:

1. Two Pointers — sorted arrays, pair sums, container problems
2. Sliding Window — substrings, subarrays, streaming data
3. BFS/DFS — trees, graphs, islands, shortest paths
4. Binary Search — sorted data, search spaces, optimization
5. Dynamic Programming — overlapping subproblems, optimal substructure
6. Backtracking — permutations, combinations, constraint satisfaction
7. Stack/Queue — parentheses matching, monotonic stacks, BFS
8. Hash Map — frequency counting, two-sum variants, grouping

For each pattern, solve 3–4 problems until you can recognize it within 2 minutes of reading a new problem.

The goal isn’t to memorize solutions — it’s to build intuition. When you see a new problem, you should immediately think “this looks like a sliding window problem” or “I need BFS here.”

This is also where many candidates plateau. If you’ve been grinding LeetCode for months without improving, you’re likely stuck in Phase 1 when you should be in Phase 2 — learning patterns rather than solving problems.

Resources for this phase:

• NeetCode 150 — problems grouped by pattern with video explanations
• LeetCode Patterns — filterable table of problems organized by pattern
• 14 Patterns to Ace Any Coding Interview — concise pattern overview

Phase 3: Interview Simulation (Week 5–6)

This is where most candidates fail to invest time — and it’s the phase that matters most.

The core shift: Move from solving problems silently on your screen to talking through problems out loud under time pressure.

Here’s what changes:

• Set a timer. Give yourself exactly 45 minutes per problem — the same constraint you’ll have in the interview.
• Talk out loud. Explain your thinking as if someone is listening. This feels awkward at first. That’s the point.
• Start with brute force. Say “Here’s a straightforward approach that works but isn’t optimal” before optimizing. Interviewers want to see your reasoning path.
• Do mock interviews. Whether with a friend, a paid service, or an AI interviewer, simulate the real experience.

Mock interviews teach you things no amount of solo practice can:

• How to recover when you’re stuck (instead of freezing)
• How to respond to hints naturally
• How to manage your time so you don’t run out during testing
• How to explain tradeoffs concisely

You can practice any LeetCode problem as a mock interview on Intervu — the AI adapts hints, asks follow-ups, and scores your performance exactly like a real interviewer would.

Phase 4: Fine-Tuning (Final Week)

The week before your interviews, shift from learning to consolidation:

• Review your weak patterns. Go back to problems you struggled with and re-solve them.
• Simulate full loops. Do 2–3 problems back-to-back with 5-minute breaks, mimicking a real onsite schedule.
• Optimize your environment. Test your webcam, microphone, and coding setup. Make sure your IDE or editor is configured how you like it.

To see what a full AI-powered mock interview looks like end to end, watch a real-time walkthrough — it breaks down the key moments where performance matters most.

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Coding Interview Tips That Actually Work

Skip the generic advice. These are the tips that consistently move the needle:

1. Start every problem with 2–3 clarifying questions — even if the problem seems obvious. Interviewers expect this and it buys you thinking time.
2. Say your brute-force approach out loud first. “I could iterate through every pair in O(n²), but let me see if a hash map brings this to O(n).” This shows reasoning.
3. Write code in the order you explained it. Don’t jump between functions. Linear code flow is easier for the interviewer to follow.
4. Test with a small example before the interviewer asks. Trace through your code with the given input, line by line. This catches most bugs.
5. When stuck, shrink the problem. Ask: “What if the input were only 3 elements?” Smaller inputs often reveal the pattern.
6. Use variable names that mean something. left, right, count, freq_map — not i, j, d. Interviewers read your code too.
7. Don’t optimize prematurely. Get a working solution first. You can always optimize after — and the interviewer may not even ask you to.

Want to practice these techniques with real-time feedback? Try a mock interview on Intervu →

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Common Coding Interview Mistakes

After analyzing thousands of mock interviews, these are the patterns that consistently separate passes from fails.

1. Jumping Straight Into Code

Candidates start typing before they understand the problem. Strong candidates spend the first 5–7 minutes clarifying constraints, working through examples, and discussing their approach.

2. Not Starting With a Brute-Force Solution

Interviewers want to see your optimization journey. Say “My first instinct is a brute-force O(n²) approach” — then improve from there. Jumping to the optimal solution skips the reasoning that interviewers are evaluating.

3. Coding in Silence

This is the single most common failure mode. Interviewers can’t evaluate your thinking if you’re not verbalizing it. Practice narrating: “I’m iterating through the array and using a hash map to track values I’ve seen…“

4. Skipping Edge Cases

When the interviewer gives you [1, 2, 3], strong candidates immediately ask: “What about an empty array? Negative numbers? Duplicates? A single element?” This signals thorough problem analysis.

5. Overcomplicating the Solution

Simpler solutions are better solutions. If your approach requires three nested loops and a custom comparator, step back and ask: “Is there a cleaner way to think about this?“

6. Not Testing Your Code

After writing your solution, walk through it with a concrete example. Trace the variables step by step. This catches bugs before the interviewer does — and demonstrates rigor.

Recognizing these mistakes is easy. Fixing them requires practice under realistic conditions. Simulate a real interview →

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How Many LeetCode Problems Are Enough?

You need 75–100 problems with deep pattern understanding. This beats grinding 500 problems with shallow memorization every time.

Here’s how to think about it:

The breakdown:

Level	Problem Count	Focus
Minimum viable	50 easy + 25 medium	Core patterns only
Solid foundation	75 problems (Grind 75)	All major patterns, properly tracked
Strong preparation	100–150 problems	Patterns + speed + tricky mediums
Diminishing returns	200+	Only if weak in specific areas

The real metric isn’t problem count — it’s pattern recognition speed. When you can read a new medium problem and identify the right approach within 2 minutes, you’ve done enough.

Focus your time on the Grind 75 for maximum coverage with minimum problems.

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Mock Interviews vs Solo Practice

There’s a reason athletes scrimmage before games and pilots use flight simulators. Performance under pressure is a fundamentally different skill than practice without it.

Factor	Solo LeetCode	Mock Interviews
Builds pattern recognition	✅	✅
Practices communication	❌	✅
Simulates time pressure	Partially	✅
Provides external feedback	❌	✅
Practices hint handling	❌	✅
Available anytime	✅	Depends on format

The verdict: You need both. Use solo practice for Phase 1–2 (foundations and patterns), then switch to mock interviews for Phase 3–4 (simulation and fine-tuning).

Your options:

• Peer practice — Free, but inconsistent quality and scheduling challenges
• Professional coaching — High quality, but expensive ($100–300 per session)
• AI-powered platforms — Available 24/7, consistent quality, instant feedback

At Intervu, our AI interviewer conducts realistic mock coding interviews with voice interaction, a live code editor, and detailed scoring. You can practice any problem from the Grind 75 list or import any LeetCode problem directly.

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Language-Specific Tips

Your choice of language matters less than fluency in it. But knowing your language’s standard library well can save critical minutes in a 45-minute round. Here’s what to focus on for each:

Python

Python is the most popular interview language for a reason — concise syntax means less time typing and more time thinking.

Must-know standard library:

• collections.defaultdict and collections.Counter — eliminates boilerplate for frequency counting and grouping
• heapq — Python only has a min-heap; for a max-heap, negate values (heapq.heappush(h, -val))
• bisect.bisect_left / bisect.insort — binary search and sorted insertion in one line
• itertools.combinations / itertools.permutations — useful for brute-force approaches before optimizing
• sorted() with key=lambda — custom sorting is extremely common in interviews

Common pitfalls:

• Mutable default arguments (def f(x=[])) — a classic Python gotcha
• Integer division: // truncates toward negative infinity, not toward zero. Use int(a/b) if you need C-style truncation
• List slicing creates copies — nums[:] is O(n), not O(1)

JavaScript

A strong choice if you’re a frontend engineer, but be aware of the quirks that can bite you under pressure.

Must-know features:

• Map and Set — use these instead of plain objects for hash-based problems. Map preserves insertion order and handles any key type
• Array.sort() — sorts lexicographically by default! Always pass a comparator: arr.sort((a, b) => a - b)
• Spread and destructuring — const [first, ...rest] = arr is clean for recursive patterns
• String.prototype.charCodeAt() — needed for character-to-index math (e.g., c.charCodeAt(0) - 'a'.charCodeAt(0))

Common pitfalls:

• No built-in heap or priority queue — you’ll need to implement one or use a sorted approach
• === vs == — always use strict equality in interviews to avoid type coercion surprises
• Array.splice() is O(n) — avoid it inside loops when performance matters

Java

Verbose, but the type system catches bugs at compile time — which is valuable when you can’t run code.

Must-know classes:

• HashMap / HashSet — the workhorses. Know .getOrDefault(), .putIfAbsent(), and .computeIfAbsent() to write cleaner code
• PriorityQueue — min-heap by default. For max-heap: new PriorityQueue<>(Collections.reverseOrder())
• TreeMap / TreeSet — sorted collections with O(log n) operations. .floorKey(), .ceilingKey() are powerful for range queries
• Deque (as ArrayDeque) — use for both stacks and queues instead of Stack or LinkedList
• StringBuilder — always use this for string concatenation in loops; String += is O(n²)

Common pitfalls:

• Integer comparison: use .equals() not == for Integer objects (values > 127 are not cached)
• Array initialization: int[][] dp = new int[m][n] — Java initializes to 0, but confirm with your interviewer
• Generics don’t work with primitives — use Integer, not int, in collections

C++

The fastest option and favored in competitive programming, but harder to debug under interview pressure.

Must-know STL:

• unordered_map / unordered_set — O(1) average hash lookups
• priority_queue — max-heap by default. For min-heap: priority_queue<int, vector<int>, greater<int>>
• sort() with custom comparators — sort(v.begin(), v.end(), [](auto& a, auto& b) { ... })
• lower_bound / upper_bound — binary search on sorted containers
• pair<int,int> and structured bindings (auto [a, b] = p) — clean for graph and coordinate problems

Common pitfalls:

• Iterator invalidation — modifying a container while iterating over it causes undefined behavior
• Off-by-one errors with .end() — it points past the last element, not to it
• Memory: prefer vector over raw arrays; use reserve() if you know the size upfront to avoid reallocations

Which Language Should You Choose?

The best language is the one you can write clean, bug-free code in without thinking about syntax. If you’re equally comfortable in multiple languages, Python is the safest choice — it lets you express ideas in the fewest lines, giving you more time to think and communicate.

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What to Expect on Interview Day

A typical FAANG interview loop looks like this:

Phone Screen (45 min)
    → 1 coding problem, medium difficulty
    → Pass: invited to virtual onsite

Virtual Onsite (4–5 rounds, 45 min each)
    → 2–3 coding rounds
    → 1 system design round (mid/senior)
    → 1 behavioral round

Time management within a 45-minute round:

Phase	Time	What to Do
Understand	0–5 min	Read the problem, ask clarifying questions, state assumptions
Plan	5–10 min	Discuss brute force, then propose your optimized approach
Code	10–30 min	Write clean, commented code
Test	30–40 min	Trace through examples, fix bugs
Discuss	40–45 min	Complexity analysis, follow-up questions

When you get stuck:

• Say so. “I’m not immediately seeing the optimal approach. Let me think about what data structure would help here.”
• Ask for a hint. Interviewers expect this — using hints well is a positive signal.
• Work through a concrete example. Often, tracing through the input manually reveals the pattern.

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The Day Before Your Interview

The final 24 hours matter more than most candidates realize.

Do:

• Review your 3–5 weakest problem patterns — but don’t learn anything new
• Re-solve 2–3 medium problems you’ve already cracked, just for confidence
• Test your environment: webcam, microphone, editor, internet connection
• Prepare your desk: water, notepad for scratch work, quiet room
• Get 7–8 hours of sleep — cognitive performance drops sharply with sleep debt

Don’t:

• Cram new topics — it creates anxiety without building real skill
• Attempt new or unfamiliar problems — a frustrating session the night before hurts your confidence
• Stay up late reading solutions — diminishing returns after 9 PM
• Skip meals — your brain runs on glucose

The goal is to arrive calm, rested, and confident in the skills you’ve already built.

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Recommended Resources

Here’s a curated list of the best free and paid resources, organized by what they’re best for:

Category	Resource	Why It’s Useful
Problem Lists	Grind 75	Optimized 75-problem list, ordered by ROI
Problem Lists	Blind 75	The original curated list that started the trend
Pattern Learning	NeetCode	Video explanations + roadmap organized by pattern
Pattern Learning	LeetCode Patterns	Filterable table mapping problems to patterns
Study Guide	Tech Interview Handbook	Free, comprehensive guide covering DSA fundamentals
Mock Interviews	Intervu.dev	AI-powered mock interviews with voice, code editor, and scoring
Mock Interviews	Pramp	Free peer-to-peer mock interviews

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Frequently Asked Questions

How do you prepare for a coding interview?

Follow a structured approach: (1) build DSA fundamentals, (2) learn problem-solving patterns, (3) practice under timed interview conditions with mock interviews, and (4) review weak areas. Most candidates need 4–8 weeks of consistent daily practice.

How long does it take to prepare for a coding interview?

It depends on your starting point. With a CS background and some algorithm familiarity, 4–6 weeks of focused preparation is typical. Starting from scratch, plan for 2–3 months. The key is consistency — 1–2 hours daily is more effective than weekend cramming sessions.

How many LeetCode problems should I solve?

75–100 problems with deep understanding of patterns is more effective than grinding 500 problems. Focus on the Grind 75 list for maximum coverage with minimal problems. The right metric is pattern recognition speed, not problem count.

What is the best way to practice coding interviews?

Combine pattern-based problem solving with mock interviews. Solo practice builds your algorithm toolkit. Mock interviews build the communication, time management, and pressure-handling skills that determine your actual interview performance.

What are the best coding interview tips?

Start every problem with clarifying questions, propose a brute-force approach before optimizing, think out loud throughout, test your code with examples before the interviewer asks, and use meaningful variable names. These five habits cover the majority of what separates strong candidates from weak ones.

What are the most common coding interview mistakes?

The top mistakes are: jumping into code without understanding the problem, coding in silence, skipping edge cases, over-engineering the solution, and not testing your code with examples.

Are mock interviews really necessary?

Yes. Solving problems and performing in an interview are fundamentally different skills. Communication, time management, and composure under pressure can only be developed through simulation. Even 3–5 mock interviews will significantly improve your performance.

Should I use Python or Java for coding interviews?

Use the language you’re most comfortable writing bug-free code in. Python is the most popular choice due to its concise syntax and built-in data structures, but Java and C++ are equally valid. Avoid learning a new language just for interviews.

What if I get stuck during the interview?

Getting stuck is normal and expected. Verbalize your thought process: “I’m considering a hash map approach but I’m not sure how to handle duplicates.” Ask for a hint — interviewers provide them intentionally, and using them well is a positive signal. Try working through a small concrete example to find the pattern.

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Start Practicing Like It’s the Real Interview

Coding interview preparation isn’t about memorizing solutions. It’s about building a systematic practice habit that develops the skills interviewers actually evaluate: structured thinking, clear communication, and calm execution under pressure.

Follow the framework:

1. Foundations — Master the core data structures and algorithms
2. Pattern Mastery — Recognize problem types within 2 minutes
3. Interview Simulation — Practice talking, timing, and handling pressure
4. Fine-Tuning — Consolidate, rest, and arrive confident

The candidates who get offers aren’t the ones who solved the most problems — they’re the ones who practiced like the real interview.

Ready to start? Try a mock coding interview now →