| arrow_right_alt | a general description of a task that can (or cannot) be solved with an algorithm |
| arrow_right_alt | a finite set of instructions that accomplish a task. |
| arrow_right_alt | putting steps in an order. |
| arrow_right_alt | deciding which steps to do next. |
| arrow_right_alt | doing some steps over and over |
| arrow_right_alt | a measure of how many steps are needed to complete an algorithm |
| arrow_right_alt | 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. |
| arrow_right_alt | 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. |
| arrow_right_alt | Algorithms with a polynomial efficiency or lower (constant, linear, square, cube, etc.) are said to run in a reasonable amount of time. |
| arrow_right_alt | Algorithms with exponential or factorial efficiencies are examples of algorithms that run in an unreasonable amount of time. |
| arrow_right_alt | provides a "good enough" solution to a problem when an actual solution is impractical or impossible |
| arrow_right_alt | a problem with a yes/no answer (e.g., is there a path from A to B?) |
| arrow_right_alt | a problem with the goal of finding the "best" solution among many (e.g., what is the shortest path from A to B?) |
| arrow_right_alt | a problem for which no algorithm can be constructed that is always capable of providing a correct yes-or-no answer |
| arrow_right_alt | a model in which programs run in order, one command at a time. |
| arrow_right_alt | a model in which programs are broken into small pieces, some of which are run simultaneously |
| arrow_right_alt | a model in which programs are run by multiple devices |
| arrow_right_alt | the time used to complete a task sequentially divided by the time to complete a task in parallel |