1/10			12											17
			2
								15		16														19
		3
		4										5
				13													18
			6
							14
						7
	11		8
9

Across

1. The scenario in which an algorithm takes an average amount of time to solve a given problem.

2. It is the process of visiting all the nodes in a binary search tree in a specific order, such as in-order, pre-order and post-order.

3. A method for solving a problem by dividing it into progressively smaller subproblems.

4. An individual item in a list or array.

5. The amount of time an algorithm takes to solve a problem as a function of the size of the input.

6. The scenario in which an algorithm takes the least amount of time to solve a given problem.

7. The scenario in which an algorithm takes the longest time to complete.

8. The process of repeating a set of instructions until a specific condition is met or a particular outcome is achieved.

9. The process of improving the performance of an algorithm by reducing its time or space complexity.

Down

10. The scenario in which an algorithm's execution time falls between the best-case and worst-case scenarios.

11. The number of times two elements are swapped during the sorting process.

12. The time taken to execute an algorithm or program.

13. A function or algorithm that calls itself with a smaller version of the problem until a base case is reached.

14. It is an array where the elements are arranged in increasing order.

15. An ordered collection of data.

16. A sorting algorithm that does not require extra space for temporary arrays or data structures.

17. A measure of time complexity in which the execution time increases linearly with the size of the input.

18. Algorithm that repeatedly compares adjacent items in a list or array and swaps them until everything is sorted.

19. It is a traversing method for binary search trees where the left and right subtrees are first recursively traversed, followed by the root.

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