steps

Step 1: Understand the problem

• Read the problem description at least twice to fully grasp the requirements
  • Identify the input and output
  • Note the constraints (e.g., input size, value ranges)
  • Study the examples to understand the expected behavior

Step 2: Analyze and develop an approach

• Determine the problem's core essence (e.g., array manipulation, dynamic programming)
• Test the problem with a small example to uncover patterns or rules
• Brainstorm a solution approach (e.g., brute force, optimized method)
• Classify the problem category (e.g., DP, graph, binary search)
• Validate your idea by mentally running it on examples, including edge cases

Step 3: Write pseudocode

• Outline your solution in pseudocode to clarify the logic and steps before coding

Step 4: Analyze time and space complexity

• Estimate the time complexity (e.g., O(n²))
• Estimate the space complexity (e.g., O(n))
• Check if the solution meets the problem's constraints

Step 5: Write the code

• Implement the solution in your chosen language, ensuring clarity and correctness

Step 6: Test and debug

• Run your code on the provided examples and edge cases
• Debug any issues by tracing the code and fixing errors

Step 7: Optimize the solution

• Look for ways to reduce time or space complexity
• Minimize constant factors (e.g., avoid redundant operations)
• Compare with other solutions to learn better approaches