Lecture Notes on Competitive Programming Problem Solving

Introduction to Problem Complexity

• Acknowledgement that the problem is extremely challenging; likely of a different class than typical problems.
• Mention of Scott Woo, a renowned competitive programmer, and his approach to problem-solving.
  • Noted that competitive programming is generally harder than typical coding challenges.

Insights from Scott Woo's AMA

• Interesting perspective on the time spent before looking at solutions:
  • Immediate reference to solutions if stuck, focusing on understanding the motivation behind solutions rather than just the solution itself.
  • Importance of understanding the 'why' behind algorithms like sliding window, backtracking, DFS, etc.
  • Encouragement not to reinvent well-known algorithms but to focus on understanding and mastering them.

Approach to Tackling Problems

• Begin by attempting to solve the problem with a methodical approach.
• Attempt a LeetCode hard problem as a demonstration, recognizing its complexity.
• Initial steps in problem-solving include reading the problem thoroughly and understanding constraints and examples.
• Emphasize the importance of understanding the problem fully before coding.

Problem Example: Minimum Reverse Operations

• Initial understanding of the problem involves manipulating a binary array with constraints.
• Realization that the problem requires more strategic thinking due to constraints like fixed subarray size k and banned positions.

Thought Process and Strategy

• Attempt to understand the potential movements of a '1' in a binary array through subarray reversals.
• Consideration of the problem as a graph traversal, potentially using BFS, due to its shortest path nature.
• Recognition of the need to possibly look at solutions if stuck after a reasonable effort.

Analysis of Solution

• Examination of a provided solution, noting its complex and mathematical nature.
• Understanding the use of algorithms and data structures like sorted lists to optimize solving.
• Acknowledgment of the high difficulty, comparing it to known hard problems on competitive programming platforms.

Reflection on Problem Difficulty

• Personal reflection on the problem's difficulty, acknowledging it as possibly the hardest attempted.
• Emphasizing the learning process and the acceptance of challenging problems as part of growth.
• Reminder that mastery in competitive programming often involves significant practice, possibly thousands of hours.

Conclusion

• Encouragement to not compare oneself too harshly against experts who have invested significant time.
• Recognizing the enjoyment and practical benefits of engaging in such problem-solving activities.
• Acceptance of not solving the problem as a learning experience and motivation to improve.