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Across

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

2. A sorting algorithm that necessitates extra memory in order to arrange the array.

3. A problem-solving strategy that involves breaking a problem into sub-problems, solving each sub-problem independently, and then combining the solutions to solve the original problem.

4. A variant of merge sort that does not require extra space for temporary arrays or data structures.

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

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

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

8. Algorithm that searches a sorted list or array by repeatedly dividing in half until the desired item is found.

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

10. The amount of time it takes to complete a task as the input size increases.

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

12. The time or space complexity of an algorithm when it receives the best input possible.

Down

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

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

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