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

Across

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

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

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

4. A sorting algorithm that rearranges the original array without using additional memory.

5. It is the point in the search interval that divides it into two equal halves.

6. The process of combining two or more sorted sub-arrays into a single sorted array.

7. The time or space complexity of an algorithm when it receives average inputs.

8. An informal high-level description of the operating principle of a computer program is a non-specific outline that summarizes how the program functions.

9. The time or space complexity of an algorithm when it receives the worst input possible.

10. A position number indicating the location of an element within an array or list.

11. The speed and effectiveness with which a task is completed, measured in terms of time and resources used.

12. 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.

Down

13. A mathematical notation used to describe the time complexity of an algorithm.

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

15. A sorting order in which the items are arranged from smallest to largest.

16. The amount of memory used by an algorithm as the input size increases.

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

18. It is a traversing method for binary search trees where the left subtree is recursively traversed, followed by the root, and then the right subtree.

19. It is the range of elements in which the binary search algorithm looks for the target element.

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