Unit 6 ✔️ Flashcards
Problem
a general description of a task that can (or cannot) be solved with an algorithm
Algorithm
a finite set of instructions that accomplish a task.
Efficiency
a measure of how many steps are needed to complete an algorithm
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.
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.
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.
Heuristic
provides a “good enough” solution to a problem when an actual solution is impractical or impossible
Undecidable problem
a problem for which no algorithm can be constructed that is always capable of providing a correct yes-or-no answer
Sequential computing
a model in which programs run in order, one command at a time.
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. Used in tandem with parallel computing.
Speedup
the time used to complete a task sequentially divided by the time to complete a task in parallel
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?)
Sequencing
the application of each step of an algorithm in the order in which the code statements are given
Selection
deciding which steps to do next
Iteration
doing some steps over and over
