How Many Coding Problems Should I Solve Before Feeling Interview Ready?

Software engineering interviews can be incredibly stressful, especially when they involve coding challenges. One question that plagues many candidates is: “How many coding problems should I solve before I’m ready for technical interviews?” Whether you’re a fresh graduate or an experienced developer changing jobs, this question is valid and important.
The short answer is that quality matters more than quantity. However, most successful candidates typically solve between 100 to 300 problems across various difficulty levels and topics. This article explores the factors that influence this number and provides a strategic approach to interview preparation.
Table of Contents
- Understanding the Interview Landscape
- Quality vs. Quantity: What Matters More?
- Baseline Numbers: How Many Problems Should You Solve?
- Factors Affecting the Number of Problems You Need to Solve
- A Strategic Approach to Problem Selection
- Essential Topics to Cover
- Tracking Your Progress
- Beyond Problem Solving: Other Essential Interview Skills
- Signs You’re Ready for Technical Interviews
- Common Mistakes in Interview Preparation
- Resources for Practice
- Conclusion
Understanding the Interview Landscape
Before determining how many problems to solve, it’s crucial to understand what technical interviews typically assess:
- Problem solving skills: Can you break down complex problems into manageable components?
- Algorithmic thinking: Do you know common algorithms and when to apply them?
- Code quality: Can you write clean, efficient, and readable code?
- Technical communication: Can you explain your thought process clearly?
- Knowledge of data structures: Do you understand which data structures to use and why?
- Time and space complexity analysis: Can you analyze and optimize your solutions?
Technical interviews at different companies vary significantly. A startup might focus on practical coding and system design, while big tech companies like Google or Facebook often emphasize algorithmic problem solving. Understanding the specific interview format of your target companies is crucial for focused preparation.
Quality vs. Quantity: What Matters More?
A common misconception is that solving more problems automatically makes you better prepared. This isn’t necessarily true. Consider these points:
The Case for Quality
Deeply understanding 50 problems across different topics can be more valuable than superficially solving 500. When you solve a problem thoroughly, you:
- Understand multiple approaches to the same problem
- Analyze time and space complexity trade-offs
- Implement the solution without help
- Review and optimize your code
- Learn to recognize similar patterns in new problems
A candidate who has mastered a smaller set of problems but can apply those patterns to new scenarios will often outperform someone who has memorized solutions to hundreds of problems.
The Role of Quantity
While quality is paramount, quantity does matter for several reasons:
- Exposure to diverse problem patterns
- Building confidence through repetition
- Developing speed and efficiency
- Reducing anxiety through familiarity
The ideal approach combines both: solve enough problems to cover the major patterns and topics, but focus on understanding each problem deeply.
Baseline Numbers: How Many Problems Should You Solve?
Based on surveys of successful candidates and recommendations from interview coaches, here are some baseline numbers:
For Entry-Level Positions
- Minimum: 50-100 problems
- Ideal: 150-200 problems
- Distribution: 60% easy, 30% medium, 10% hard
For Mid-Level Positions
- Minimum: 100-150 problems
- Ideal: 200-250 problems
- Distribution: 40% easy, 50% medium, 10% hard
For Senior Positions
- Minimum: 150-200 problems
- Ideal: 250-300 problems
- Distribution: 20% easy, 60% medium, 20% hard
These numbers assume you’re solving problems thoroughly, not just reading solutions or solving problems you’ve seen before.
Factors Affecting the Number of Problems You Need to Solve
The ideal number varies based on several personal factors:
1. Your Current Skill Level
Beginners with limited algorithmic knowledge may need to solve more problems to build foundational skills. Experienced developers might need fewer problems but should focus on more complex ones.
2. Your Learning Style
Some people learn better through extensive practice, while others benefit from deeper analysis of fewer problems. Adjust your approach based on how you learn best.
3. Target Companies
Different companies have different interview styles:
- Big Tech (FAANG+): These typically require more preparation, focusing on algorithmic challenges. Aim for the higher end of the ranges mentioned above.
- Startups: Often focus more on practical coding and cultural fit. You might need fewer algorithmic problems but more focus on real-world scenarios.
- Traditional Companies: May have more predictable interview patterns, allowing for more targeted preparation.
4. Time Available for Preparation
With limited time, focus on quality over quantity. If you have only a month to prepare, solving 50 carefully selected problems thoroughly is better than rushing through 200.
5. Prior Interview Experience
If you’ve interviewed before, you’ll have a better sense of your weaknesses and can focus your practice more efficiently.
A Strategic Approach to Problem Selection
Rather than randomly solving problems, follow a structured approach:
Phase 1: Foundation Building (2-4 weeks)
- Study core data structures and algorithms
- Solve 30-50 easy problems covering fundamental concepts
- Focus on array, string, and basic tree/graph problems
- Review each solution thoroughly, even if you solved it correctly
Phase 2: Pattern Recognition (3-5 weeks)
- Identify common problem patterns (two pointers, sliding window, BFS/DFS, etc.)
- Solve 10-15 problems for each important pattern
- Progress to medium difficulty problems
- Start timing yourself (aim to solve medium problems in 30-45 minutes)
Phase 3: Weakness Targeting (2-3 weeks)
- Analyze your performance to identify weak areas
- Double down on topics you struggle with
- Introduce hard problems in your strong areas
- Simulate interview conditions (code on a whiteboard or Google Doc)
Phase 4: Mock Interviews and Refinement (1-2 weeks)
- Conduct mock interviews with friends or through platforms like Pramp or interviewing.io
- Solve new problems under time pressure
- Focus on communication and explaining your thought process
- Review and refine your approach based on feedback
This phased approach ensures you’re not just accumulating solved problems but building skills systematically.
Essential Topics to Cover
Regardless of how many problems you solve, ensure you cover these essential topics:
Data Structures
- Arrays and Strings: 15-20 problems
- Linked Lists: 8-10 problems
- Stacks and Queues: 5-8 problems
- Hash Tables: 10-15 problems
- Trees (Binary, BST, N-ary): 15-20 problems
- Heaps/Priority Queues: 5-8 problems
- Graphs: 10-15 problems
- Tries: 3-5 problems
Algorithms
- Sorting and Searching: 10-15 problems
- Recursion and Backtracking: 10-15 problems
- Dynamic Programming: 15-20 problems
- Greedy Algorithms: 5-10 problems
- Two Pointers/Sliding Window: 8-12 problems
- BFS/DFS: 10-15 problems
- Bit Manipulation: 5-8 problems
Special Topics
- System Design (for mid/senior roles): Study principles and practice 10-15 scenarios
- Object-Oriented Design: 5-8 problems
- Concurrency (if relevant): 5-8 problems
The numbers above add up to roughly 150-220 problems, which aligns with our baseline recommendations.
Tracking Your Progress
Keeping track of your progress is essential for effective preparation. Here’s a system many successful candidates use:
Create a Structured Tracking System
Use a spreadsheet or tool like Notion to track:
- Problem name and link
- Difficulty level
- Topic/pattern category
- Date solved
- Time taken to solve
- Whether you needed hints
- A confidence rating (1-5)
- Notes on the approach and key insights
- Date for review (spaced repetition)
Implement a Review System
Don’t just solve and forget. Use spaced repetition to review problems:
- Review easy problems you solved with difficulty after 1 week
- Review medium problems after 2 weeks
- Review hard problems after 3 weeks
- For problems you solved confidently, extend the review interval
Track Metrics Beyond Numbers
Monitor these indicators of progress:
- Average time to solve problems of each difficulty
- Percentage of problems solved without hints
- Distribution of problems across topics
- Success rate in mock interviews
This systematic tracking helps identify patterns in your performance and areas needing improvement.
Beyond Problem Solving: Other Essential Interview Skills
The number of problems you solve is just one aspect of interview preparation. Other critical skills include:
Technical Communication
Practice explaining your thought process clearly. Many candidates fail not because they couldn’t solve the problem, but because they couldn’t articulate their approach.
Tips for improvement:
- Think out loud while solving problems
- Record yourself explaining solutions
- Practice with non-technical friends
- Use clear terminology and avoid jargon
Code Quality
Writing clean, readable code matters. Focus on:
- Meaningful variable names
- Proper indentation and formatting
- Breaking down complex functions
- Adding comments for clarity
- Handling edge cases
Handling Pressure
Technical interviews are stressful. Build resilience through:
- Regular mock interviews
- Timed practice sessions
- Mindfulness techniques
- Developing a consistent problem-solving approach
Behavioral Interview Preparation
Don’t neglect the behavioral aspects of interviews:
- Prepare stories about your projects
- Practice answering common behavioral questions
- Develop examples that showcase your technical and soft skills
Signs You’re Ready for Technical Interviews
How do you know when you’ve solved enough problems? Look for these indicators:
Pattern Recognition
- You can quickly identify the type of problem and applicable techniques
- When facing a new problem, you can relate it to problems you’ve solved before
- You recognize when to apply specific data structures or algorithms
Time Efficiency
- You can solve easy problems in 10-15 minutes
- You can solve medium problems in 20-40 minutes
- You can at least develop a working approach for hard problems within an hour
Confidence Indicators
- You can solve 80% of medium-level problems without hints
- You perform well in mock interviews
- You can explain your solutions clearly
- You can analyze time and space complexity accurately
Consistency
- Your performance is consistent across different problem types
- You have no major knowledge gaps in core topics
- You can perform well even when nervous or under pressure
If you meet most of these criteria, you’re likely ready, regardless of the exact number of problems you’ve solved.
Common Mistakes in Interview Preparation
Avoid these common pitfalls that can undermine your preparation:
Quantity Over Quality
Rushing through problems without understanding them deeply is counterproductive. It’s better to solve fewer problems thoroughly than many superficially.
Memorizing Solutions
Memorizing solutions without understanding the underlying patterns leads to failure when facing new problems. Focus on understanding approaches, not specific solutions.
Neglecting Mock Interviews
Many candidates practice in isolation and struggle in actual interviews. Regular mock interviews are essential for developing communication skills and handling pressure.
Ignoring Weak Areas
It’s natural to focus on topics you enjoy, but this creates knowledge gaps. Deliberately target your weak areas, even if they’re challenging.
Last-Minute Cramming
Trying to solve hundreds of problems in the week before your interview is ineffective. Consistent, spaced practice over weeks or months is far more beneficial.
Using Only One Resource
Relying solely on LeetCode or any single platform limits your exposure to different problem types and explanations. Use diverse resources for comprehensive preparation.
Resources for Practice
To help you reach your target number of problems, here are some high-quality resources:
Online Platforms
- LeetCode: The most popular platform with 2000+ problems and company-specific collections
- HackerRank: Good for beginners with clear explanations
- CodeSignal: Offers real interview questions from companies
- AlgoExpert: Curated set of 160+ problems with video explanations
- Pramp: Free peer-to-peer mock interviews
Books
- “Cracking the Coding Interview” by Gayle Laakmann McDowell: The classic resource with 189 problems
- “Elements of Programming Interviews”: More advanced problems with thorough explanations
- “Algorithm Design Manual” by Steven Skiena: Excellent for understanding the thought process
Courses
- Grokking the Coding Interview: Pattern-based approach to problem solving
- InterviewCamp.io: Structured curriculum focused on interview preparation
- Princeton’s Algorithms Course on Coursera: Great for building foundations
GitHub Repositories
- Blind 75 LeetCode Questions: A curated list of essential problems
- Tech Interview Handbook: Comprehensive guide with problem recommendations
- LeetCode Patterns: Problems organized by common patterns
Conclusion
The question “How many coding problems should I solve before feeling interview-ready?” doesn’t have a one-size-fits-all answer. While most successful candidates solve between 100 to 300 problems, the quality of your practice matters more than the quantity.
Focus on:
- Understanding problem patterns rather than memorizing solutions
- Covering all essential topics and algorithms
- Developing your communication and problem-solving process
- Consistent practice over time rather than cramming
- Regular self-assessment through mock interviews
Remember that interview readiness is about confidence and competence, not just hitting a specific number of problems. When you can approach new problems methodically, communicate your thought process clearly, and implement efficient solutions under pressure, you’re ready—regardless of whether you’ve solved 100 problems or 300.
The journey to interview readiness is personal and depends on your background, learning style, and target companies. Use the guidelines in this article to create a preparation plan tailored to your needs, and focus on continuous improvement rather than arbitrary milestones.
With deliberate practice and a strategic approach, you’ll develop the skills and confidence needed to succeed in technical interviews, opening doors to exciting opportunities in your software engineering career.