Lecture Notes on Algorithmic Thinking

Key Concepts

• Algorithmic Thinking: Identifying individual steps needed to create an algorithm that leads to a solution.
  • Example: Algorithms for multiplication learned in school.
  • Enables automation of solutions.

Relation to Word Searches

• Ineffective Approach: Randomly searching for words in a grid.
• Effective Approach:
  • Identify the word to search for (e.g., "algorithm").
  • Look for the first letter (A) systematically rather than randomly.
  • Check adjacent letters to find the next letter in the word.

Systematic Search Example

1. Start from the top-left corner and check each letter.
2. Move to the next letter if not found.
3. Continue until finding all letters that spell out the word.

Outline Algorithm for Word Search

1. For every word to find in the word search:
   • Check every letter in the grid.
   • If a letter matches the first letter of the word:
     • Check adjacent letters for the second letter.
     • If the second letter is found, continue checking in that direction.
     • If letters do not match, the word is not found.
2. Output whether the word was found.

Data Storage Considerations

• Abstraction: Focus on important data for the algorithm.
  • Store letters and their connections.
  • Use X and Y coordinates for easier referencing.
• Simplification: Grid size, words, and individual letters are irrelevant for solving the algorithm.

Data Structures in Programming (Using Python)

• Use lists (nested lists) to store grid data.
• Use variables to store the word being searched for.
• Looping Technique: Utilize two for loops to check every letter in the grid:
  • Efficient for known grid sizes.
  • Can be adjusted for single or multiple occurrences of the word.

Matching Letters in the Grid

• Use string indices to check if grid letters match the first letter of the word.
• Expand search to adjacent letters (considering their coordinates):
  • Check top-left, top, top-right, left, right, bottom-left, bottom, bottom-right.

Boundary Checks

• Ensure searches do not go out of grid bounds to avoid errors:
  • Check if X and Y positions are within valid ranges.

Continuation of Search

• If a second letter is found, keep checking in that direction until the word is fully matched or bounds of the grid are reached.
• Introduce new variables to manage search direction.

Final Algorithm Steps

• Provide output detailing the location of the first letter and direction of search for subsequent letters.
• Scalability: Algorithm can adapt to any word or grid size with minor adjustments.

Conclusion

• Apply algorithmic thinking by breaking down problems, determining important data, and using appropriate data structures.
• Note: Learning this skill takes practice and logical thinking.

Tips for Success

• Keep refining your approach to problem-solving through experience.
• Perseverance is key in programming.
• Always think about how a computer processes information.