Unit 6- Algorithms

Reasonable Time

Algorithms with a polynomial efficiency or lower (constant, linear, square, cube, etc.) are said to run in a reasonable amount of time.

Unreasonable Time

Algorithms with exponential or factorial efficiencies are examples of algorithms that run in an unreasonable amount of time.

Algorithm

a finite set of instructions that accomplish a task.

Problem

a general description of a task that can (or cannot) be solved with an algorithm

Efficiency

a measure of how many steps are needed to complete an algorithm

Parallel Computing

a model in which programs are broken into small pieces, some of which are run simultaneously

Distributed Computing

a model in which programs are run by multiple devices

Sequential Computing

a model in which programs run in order, one command at a time.

Undecidable Problem

a problem for which no algorithm can be constructed that is always capable of providing a correct yes-or-no answer

Decision Problem

a problem with a yes/no answer (e.g., is there a path from A to B?)

Optimization Problem

a problem with the goal of finding the "best" solution among many (e.g., what is the shortest path from A to B?)

Binary Search

a search algorithm that starts at the middle of a sorted set of numbers and removes half of the data; this process repeats until the desired value is found or all elements have been eliminated.

Linear Search

a search algorithm which checks each element of a list, in order, until the desired value is found or all elements in the list have been checked.

Selection

deciding which steps to do next.

Iteration

doing some steps over and over

Heuristic

provides a "good enough" solution to a problem when an actual solution is impractical or impossible

Sequencing

putting steps in an order.

Speedup

the time used to complete a task sequentially divided by the time to complete a task in parallel