ISSUE#1.2- Santiago - ISSUE DEVELOPMENT

[ba-00001]

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Algorithm Development Template

ISSUE#: [Issue Number]
Title: [Issue Title]
Prepared by: [Developer Name]
Date: [MM/DD/YYYY]

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1. Problem Definition and Clarification

• Objective: Clearly state the problem that the algorithm needs to solve.
• Key Questions:
  • What is the problem to be solved?
  • What are the expected outcomes?
• Sub-tasks: Break down the issue into smaller tasks.

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2. Input/Output Specifications

• Input Data:
  • Define the required input data types, format, and constraints.
• Expected Output:
  • Specify what the algorithm should return or produce after execution.

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3. Constraints and Requirements

• Time Complexity: What is the acceptable time complexity for the solution?
• Space Complexity: Define memory usage constraints.
• Resource Constraints:
  • CPU, memory, and other hardware limitations.
• Ethical Considerations (if applicable):
  • How will the algorithm ensure fairness, privacy, or comply with legal requirements?

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4. Data Structures

• Chosen Data Structures: List the data structures (arrays, trees, hash maps, etc.) that are ideal for solving the problem and why.
• Justification: Explain why these data structures will improve efficiency.

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5. Algorithm Design Approach

• Design Paradigm:
  • Choose one or more design paradigms (e.g., Greedy, Divide and Conquer, Dynamic Programming, etc.).
  • Explain why the paradigm is suitable for this problem.
• Modular Design:
  • Break down the algorithm into reusable functions or components for clarity and maintainability.

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6. Edge Cases and Error Handling

• Edge Cases:
  • Identify possible edge cases (e.g., null values, empty inputs, extreme data).
• Error Handling:
  • Include strategies to handle invalid input or unexpected behavior.

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7. Optimization

• Initial Version: Describe the basic working version of the algorithm.
• Optimization Techniques: List any steps taken to optimize the algorithm for better performance (e.g., memoization, pruning, parallelization).

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8. Testing and Debugging

• Test Cases:
  • Typical input cases.
  • Boundary cases.
  • Edge cases.
• Debugging Tools: Specify the tools or strategies used for debugging.

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9. Documentation and Maintenance

• Documentation:
  • Provide clear explanations of the algorithm, its functions, and how to use it.
• Maintenance Plan:
  • Outline plans for future updates, bug fixes, and ongoing improvements.

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Comments/Notes

[Additional notes or comments regarding the issue development.]

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Version History

Date	Changes Made	Version
MM/DD/YYYY	Initial Draft	1.0
MM/DD/YYYY	[Describe subsequent changes]	X.X

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[santycarbahol]

What would you like to share? I would use trees with a Best-First search algorithm or Depth-First Search to construct an algorithm that can determine and select the shortest path for the code in order to solve this problem. With this strategy, you might identify the shortest path and reach your goal by comparing the distances between cities and choosing the one with the lowest cost.

Additional information I would like to utilize more than one algorithm for this problem, but the one that provides the best result in the shortest amount of time is the one I would choose.