Unit 10 Vocabulary: Algorithms and Concepts

Algorithm

a finite set of instructions that accomplish a task.

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.

Brute Force

relying on or achieved through the application of force, effort, or power in usually large amounts instead of more efficient, carefully planned, or precisely directed methods.

Decision Problem

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

Distributed Computing

a model in which programs are run by multiple devices.

Algorithmic Efficiency

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

Heuristic

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

Iteration

a repetitive portion of an algorithm which repeats a specified number of times or until a given condition is met.

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.

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?).

Parallel Computing

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

Problem

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

Reasonable Time

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

Selection

deciding which steps to do next.

Sequencing

the application of each step of an algorithm in the order in which the code statements are given.

Sequential Computing

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

Speedup

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

Undecidable Problem

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

Unreasonable Time

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