How many coding questions per day?

Preparing for coding interviews, especially with top-tier companies like Google, requires a strategic and disciplined approach to practicing coding problems. One common question aspiring candidates ask is: "How many coding questions should I solve per day?" The answer isn't one-size-fits-all, as it depends on various personal and situational factors. However, understanding these factors and following tailored guidelines can help you optimize your preparation effectively.

1. Factors to Consider

a. Current Skill Level

• Beginner: If you're new to coding interviews or have limited experience with data structures and algorithms, you might need a more gradual approach.
• Intermediate: With some background in coding interviews, you can adopt a more intensive practice routine.
• Advanced: If you're already comfortable with a wide range of problems, you might focus on refining your skills and tackling higher-difficulty questions.

b. Time Before the Interview

• Short-Term Preparation (1-2 months): Requires a more intensive daily commitment.
• Medium-Term Preparation (3-6 months): Allows for a balanced approach with steady progress.
• Long-Term Preparation (6+ months): Offers flexibility and the opportunity to cover topics thoroughly.

c. Available Daily Time

• Full-Time Preparation: If you can dedicate 4-6 hours daily, you can cover more problems and topics.
• Part-Time Preparation: Allocating 1-2 hours daily necessitates a more focused and efficient study plan.

d. Quality vs. Quantity

• Understanding Over Numbers: It's crucial to deeply understand each problem rather than merely solving a high volume of questions.
• Balanced Practice: Ensure a mix of problem difficulties and topics to build comprehensive skills.

e. Learning Style and Efficiency

• Active Learning: Engaging actively with problems, such as writing code by hand or explaining solutions aloud, can enhance retention.
• Passive Learning: Simply reading solutions without active engagement is less effective.

f. Physical and Mental Well-Being

• Avoid Burnout: Overloading yourself with too many problems can lead to fatigue and decreased performance.
• Maintain Balance: Incorporate breaks and leisure activities to sustain long-term productivity.

2. Recommended Daily Coding Questions

a. Beginners (New to Coding Interviews)

• Daily Target: 1-2 coding problems
• Focus Areas: Start with easy-level problems to build confidence and understand fundamental concepts.
• Approach:
  • Weekdays: Solve 1 problem each day.
  • Weekends: Dedicate extra time to review and understand solutions, perhaps solving a second problem.

b. Intermediate (Some Coding Interview Experience)

• Daily Target: 2-3 coding problems
• Focus Areas: Transition from easy to medium-level problems, covering a broader range of topics.
• Approach:
  • Weekdays: Solve 2 problems each day.
  • Weekends: Solve 1-2 additional problems and engage in mock interviews or group study sessions.

c. Advanced (Comfortable with Most Topics)

• Daily Target: 3-5 coding problems
• Focus Areas: Tackle medium to hard-level problems, focusing on optimizing solutions and mastering complex algorithms.
• Approach:
  • Weekdays: Solve 3 problems each day.
  • Weekends: Solve 2 additional problems and participate in timed mock interviews to simulate real interview conditions.

3. Structuring Your Daily Practice

a. Diversify Problem Types

Ensure you cover a wide array of topics to build versatility:

• Data Structures: Arrays, Linked Lists, Trees, Graphs, Stacks, Queues, Hash Tables, Heaps.
• Algorithms: Sorting, Searching, Dynamic Programming, Recursion, Backtracking, Greedy Algorithms, Graph Traversal.

b. Allocate Time for Each Problem

• Understand the Problem (10-15 minutes): Read the problem statement carefully, identify inputs, outputs, and constraints.
• Devise a Plan (10-15 minutes): Think of possible approaches and select the most efficient one.
• Implement the Solution (20-30 minutes): Write clean, readable code.
• Test and Debug (10-15 minutes): Run test cases to ensure correctness and optimize if necessary.

c. Review and Reflect

• Post-Solution Analysis: After solving, review optimal solutions and alternative approaches to enhance understanding.
• Identify Patterns: Recognize common problem patterns to apply similar strategies in future problems.

d. Track Your Progress

• Maintain a Log: Document the problems you've solved, noting the difficulty level, key learnings, and areas needing improvement.
• Set Milestones: Define weekly and monthly goals to monitor your advancement and stay motivated.

4. Sample Study Schedules

a. 3-Month Preparation Plan

Month 1: Foundation Building

• Weeks 1-2:
  • Daily: 1 easy problem (Arrays, Strings).
  • Focus: Understanding basic data structures and simple algorithms.
• Weeks 3-4:
  • Daily: 1 easy + 1 medium problem (Linked Lists, Stacks, Queues).
  • Focus: Building confidence and tackling slightly more complex topics.

Month 2: Intermediate Mastery

• Weeks 5-6:
  • Daily: 2 medium problems (Trees, Graphs).
  • Focus: Deepening understanding of complex data structures.
• Weeks 7-8:
  • Daily: 2 medium + 1 hard problem (Dynamic Programming, Recursion).
  • Focus: Enhancing problem-solving speed and tackling challenging algorithms.

Month 3: Advanced Preparation

• Weeks 9-10:
  • Daily: 3 medium problems.
  • Focus: Refining solutions and optimizing code.
• Weeks 11-12:
  • Daily: 2 medium + 2 hard problems.
  • Focus: Simulating interview conditions with timed problems and mock interviews.

b. 1-Month Intensive Plan

Weeks 1-4:

• Daily: 3-4 coding problems (mix of medium and hard).
• Focus: Covering all Blind 75 topics, optimizing problem-solving speed, and engaging in daily mock interviews.

5. Additional Tips for Success

a. Prioritize Quality Over Quantity

• Deep Understanding: Ensure you thoroughly comprehend each problem and its solution rather than rushing through many problems.
• Error Analysis: Learn from mistakes by analyzing why a particular approach didn’t work and how to improve.

b. Embrace a Growth Mindset

• Continuous Improvement: View each problem as an opportunity to learn and grow, even if you find it challenging.
• Stay Persistent: Don't get discouraged by setbacks; perseverance is key to mastering coding interviews.

c. Leverage Multiple Resources

• Books: Utilize resources like Cracking the Coding Interview by Gayle Laakmann McDowell and Elements of Programming Interviews by Adnan Aziz et al.
• Online Platforms: Engage with platforms like LeetCode, HackerRank, and CodeSignal for diverse problem sets.
• Study Groups: Join or form study groups to gain different perspectives and collaborative learning.

d. Simulate Real Interview Conditions

• Timed Practice: Regularly practice solving problems within a set time to build speed and manage pressure.
• Mock Interviews: Participate in mock interviews to enhance communication skills and receive constructive feedback.

e. Focus on Communication

• Articulate Your Thought Process: Clearly explain your reasoning and approach while solving problems, as this is crucial during interviews.
• Collaborative Problem-Solving: Treat mock interviews as collaborative sessions where you engage with the interviewer to refine solutions.

f. Maintain Balance and Well-Being

• Regular Breaks: Incorporate short breaks to prevent burnout and maintain mental clarity.
• Healthy Lifestyle: Ensure adequate sleep, nutrition, and physical activity to support cognitive function and overall well-being.

6. Conclusion

There is no definitive number of coding questions you should solve each day, as it varies based on individual circumstances. However, by considering factors like your current skill level, available time, and the intensity of your preparation, you can tailor a daily problem-solving routine that maximizes your effectiveness without leading to burnout.

Key Takeaways:

• Assess Personal Factors: Understand your starting point and adjust your daily target accordingly.
• Emphasize Understanding: Focus on deeply comprehending each problem and its solution.
• Stay Consistent: Regular, disciplined practice is more beneficial than sporadic, intensive bursts.
• Engage in Active Learning: Explain your solutions, seek feedback, and learn from mistakes.
• Maintain Balance: Prioritize your well-being to sustain long-term preparation efforts.

Remember: The goal is not just to solve as many problems as possible but to build a robust problem-solving framework that can adapt to various challenges presented during coding interviews. By adopting a thoughtful and strategic approach, you can enhance your chances of clearing a Google coding interview and securing your desired role.

Additional Resources:

• LeetCode Blind 75 List: A curated list of 75 essential coding problems.
• DsignGurus.io: Anonymous mock interviews with engineers from top companies, including Google.
• System Design Primer: Comprehensive resource for system design interview preparation.