Effective Study Strategy

Studying for coding interviews isn't like studying for school exams. Here's how to maximize your preparation time.

The Golden Rule

Quality > Quantity. Understanding > Memorization.

Doing 300 problems mindlessly is worse than deeply understanding 50.

The 80/20 Principle

20% of topics appear in 80% of interviews. Focus there first.

High-Priority Topics (Do These First)

Tier 1 - Absolute Must-Know:

  • Arrays & Strings
  • Hash Maps & Sets
  • Two Pointers
  • Sliding Window
  • Binary Search
  • Stacks & Queues
  • Basic recursion

Tier 2 - Very Common:

  • Trees (DFS, BFS, traversals)
  • Dynamic Programming (1D)
  • Backtracking (combinations, permutations)
  • Graphs (BFS, DFS basics)
  • Linked Lists

Tier 3 - Less Common:

  • Heaps/Priority Queues
  • Tries
  • Advanced DP
  • Union-Find
  • Topological Sort

Study Time Allocation

For a 6-week prep (15 hours/week):

Week 1-2: Tier 1 (50% of time)
- Arrays, strings, hash maps
- Two pointers, sliding window
- Binary search basics

Week 3-4: Tier 2 (35% of time)
- Trees and basic graphs
- Introduction to DP
- Backtracking patterns

Week 5-6: Tier 3 + Mock Interviews (15% of time)
- Less common topics
- Mock interviews
- Review weak areas

The Learning Loop

Phase 1: Learn the Pattern (30%)

Don't: Jump straight to Leetcode hard problems.

Do: Learn the pattern first.

1. Read about the technique
2. Understand why it works
3. See 2-3 examples
4. Code a basic example yourself

Example - Sliding Window:

Day 1: Read about sliding window concept
       Understand fixed vs. variable size
       Watch a video tutorial

Day 2: Code "max sum subarray of size k"
       Code "longest substring without repeating"
       Note the pattern

Phase 2: Practice the Pattern (50%)

Do 5-10 problems per pattern.

Problems 1-3: Easy - Build confidence
Problems 4-7: Medium - Core competency
Problems 8-10: Hard - Edge cases and variations

The Right Way to Practice:

1. Try for 20-30 minutes
2. If stuck, look at hints (not solution)
3. If still stuck (45 mins), look at solution
4. IMPORTANT: Implement yourself after seeing solution
5. Come back in 3 days and solve again from scratch

Phase 3: Review and Consolidate (20%)

After each topic:
- Review your solutions
- Identify common mistakes
- Create a "pattern template"
- Do 2-3 random problems mixing old topics

The Mistake-Driven Learning System

Your mistakes are your curriculum.

Step 1: Track Your Mistakes

Create a "mistakes journal":

Problem: Two Sum
Mistake: Used arr.indexOf() in loop → O(n²)
Why: Didn't think about nested iteration
Fix: Use hash map for O(1) lookup
Pattern: Always check if operation inside loop

Step 2: Categorize Mistakes

Common mistake categories:

1. Conceptual Errors

  • Chose wrong approach
  • Misunderstood problem
  • Didn't recognize pattern

2. Implementation Bugs

  • Off-by-one errors
  • Wrong boundary conditions
  • Index mistakes

3. Edge Cases

  • Empty input
  • Single element
  • Duplicates
  • Negative numbers

4. Optimization Misses

  • Didn't see O(n) solution
  • Used wrong data structure
  • Redundant operations

Step 3: Target Your Weaknesses

If you keep making the same mistake:

Repeatedly mess up index calculations?
→ Do 10 problems focusing on index manipulation

Keep choosing wrong data structures?
→ Make a cheat sheet: "When to use what"

Always miss edge cases?
→ Create an edge case checklist for every problem

Study Techniques That Work

Technique 1: The 3-Pass Method

Pass 1: Understand

  • Read the problem
  • Work through examples
  • Identify pattern
  • Plan approach

Pass 2: Implement

  • Code the solution
  • Test with examples
  • Fix bugs

Pass 3: Optimize

  • Analyze complexity
  • Look for improvements
  • Refactor

Technique 2: Spaced Repetition

Day 1: Learn and solve problem
Day 3: Solve again from scratch
Day 7: Solve again
Day 14: Solve again
Day 30: Final review

The problems you solve multiple times are the ones you'll remember.

Technique 3: The Feynman Technique

After solving a problem:

1. Explain the solution out loud
2. Explain it like teaching someone
3. If you stumble, you don't understand it yet
4. Go back and clarify

Technique 4: Pattern Templates

Create your own templates:

Example - Backtracking Template:

def solve(nums):
    result = []
    current = []

    def backtrack(start):
        # Base case
        if len(current) == target_length:
            result.append(current[:])
            return

        # Try choices
        for i in range(start, len(nums)):
            current.append(nums[i])
            backtrack(i + 1)
            current.pop()

    backtrack(0)
    return result

Save these. Modify for specific problems.

Study Schedule Examples

Aggressive: 6 Weeks Full-Time (40 hours/week)

Week 1: Arrays, Strings, Hash Maps
- Mon-Tue: Learn + 10 easy problems
- Wed-Thu: 10 medium problems
- Fri: 3 hard problems + review
- Sat-Sun: Mixed practice + mock interview

Week 2: Two Pointers, Sliding Window
- Same structure

Week 3: Trees, Binary Search
Week 4: DP, Backtracking
Week 5: Graphs, Advanced Topics
Week 6: Mock interviews + review weak areas

Moderate: 12 Weeks Part-Time (15 hours/week)

Weeks 1-3: Tier 1 Topics
- 2 hours/day weekdays
- 2.5 hours/day weekends
- One topic per week
- 20-25 problems/week

Weeks 4-8: Tier 2 Topics
Weeks 9-11: Tier 3 + Mock Interviews
Week 12: Final review + company-specific prep

Maintenance: Ongoing (5 hours/week)

Already interviewed before, staying sharp:
- 1-2 problems/day
- Focus on weak areas
- One mock interview/week
- Review old problems

Platform Strategy

LeetCode

Best for: Pattern-based learning, company tags

How to use:

1. Sort by "Acceptance Rate" (high to low) within difficulty
2. Use company tags if targeting specific companies
3. Do "Top Interview Questions" list
4. Check "Similar Problems" after solving

HackerRank

Best for: Structured learning paths

How to use:

1. Follow their interview prep kit
2. Good for beginners
3. Clear explanations

AlgoExpert / Educative

Best for: Video explanations and organized curriculum

How to use:

1. Watch video first
2. Try problem
3. Compare with solution

Common Study Mistakes

❌ Mistake 1: Doing Random Problems

Problem: No pattern reinforcement, can't recognize similar problems.

Fix: Study by topic/pattern, do 5-10 problems per pattern.

❌ Mistake 2: Looking at Solutions Too Quickly

Problem: False sense of understanding, can't solve independently.

Fix: Struggle for 20-30 minutes. If stuck, look at hints first.

❌ Mistake 3: Not Coding Solutions

Problem: Can understand but can't implement.

Fix: Always code it yourself, even after seeing solution.

❌ Mistake 4: Not Reviewing

Problem: Forget everything after a week.

Fix: Spaced repetition. Solve again after 3 days, 7 days, 14 days.

❌ Mistake 5: Only Doing Easy Problems

Problem: False confidence, can't handle interview difficulty.

Fix: Mix difficulty. Aim for 60% medium, 30% easy, 10% hard.

❌ Mistake 6: Memorizing Solutions

Problem: Fails when problem is slightly different.

Fix: Understand the pattern, not just the solution.

Progress Tracking

Track these metrics:

Week 1:
✓ Topics covered: Arrays, Hash Maps
✓ Problems solved: 25 (10 easy, 12 medium, 3 hard)
✓ Patterns mastered: Frequency counting, complement finding
✓ Mock interviews: 1 (Score: 2/4)
✓ Weak areas: Off-by-one errors, edge cases

Week 2:
✓ Topics covered: Two pointers, Sliding window
✓ Problems solved: 22 (8 easy, 12 medium, 2 hard)
✓ Patterns mastered: Two pointers, fixed/variable window
✓ Mock interviews: 1 (Score: 2.5/4)
✓ Improvements: Better at edge cases
✓ Weak areas: Still slow on optimization

When You're Ready for Interviews

You're ready when:

  • ✅ Can solve 70%+ of medium problems
  • ✅ Can explain your solution clearly
  • ✅ Mock interview scores consistently 3/4 or higher
  • ✅ Recognize patterns quickly
  • ✅ Can optimize brute force to optimal

You don't need to:

  • ❌ Solve every hard problem
  • ❌ Know every algorithm
  • ❌ Get optimal solution immediately
  • ❌ Be perfect

Key Takeaway

Effective study is about deliberate practice: focus on patterns, learn from mistakes, and review regularly. It's better to deeply understand 50 problems than to superficially complete 300. Quality, consistency, and active learning beat raw volume every time.

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