Set-6

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Across
  1. 1. Visual representation of recursive calls)
  2. 9. Efficiency, correctness, finiteness)
  3. 10. Growth rate as input size increases)
  4. 11. Converting recursive code to iterative)
  5. 12. Strategies for algorithm development)
  6. 13. Evaluating algorithm execution speed and resource use)
  7. 14. Solving recurrences by direct substitution)
  8. 16. Solving recurrences using loop-based approach)
Down
  1. 2. Problem-solving technique using self-reference)
  2. 3. Precise steps to solve a problem)
  3. 4. Theorem for analyzing divide-and-conquer recurrences)
  4. 5. Efficient sorting algorithm using heap data structure)
  5. 6. Shorthand notations for growth trends)
  6. 7. Mathematical equation describing recursion)
  7. 8. Natural language or pseudocode)
  8. 15. Analyzing an algorithm's efficiency)