Algorithms

2. A problem where the answer is "yes" or "no" to a specific question.
5. A step-by-step procedure or formula for solving a problem.
6. A computing paradigm where tasks are distributed across multiple computers connected via a network.
10. A rule of thumb or educated guess that may not always lead to the optimal solution but is efficient and practical.
14. The ability of an algorithm to use the fewest resources (time, memory) to solve a problem.
15. A measure of time complexity that indicates an algorithm's performance is impractical for real-world applications.
17. The traditional computing paradigm where instructions are executed one after the other, in sequence.

1. A measure of time complexity that indicates an algorithm's performance is acceptable for practical use.
3. A problem that seeks to find the best solution among a set of feasible solutions.
4. The repetition of a process or set of instructions until a specific condition is met.
7. An efficient search algorithm that divides a sorted array into halves, eliminating half of the remaining elements in each step.
8. A measure of how much faster a parallel algorithm is compared to a sequential algorithm.
9. The overarching task or objective that needs to be addressed.
11. A simple search algorithm that checks every element in a list until the target element is found or the end of the list is reached.
12. The process of executing tasks or instructions in a specific order, one after another.
13. A computing paradigm where multiple tasks are executed simultaneously, potentially on multiple processors or cores.
16. The process of choosing between different options or paths based on certain conditions.