| Algorithm |
A step-by-step process for solving a problem or achieving a specific goal. |
| Array |
A collection of elements of the same data type, stored in contiguous memory locations. |
| Average-Case Scenario |
The scenario in which an algorithm's execution time falls between the best-case and worst-case scenarios. |
| Best-Case Scenario |
The scenario in which an algorithm takes the shortest time to complete. |
| Big O Notation |
A mathematical notation used to describe the time complexity of an algorithm. |
| Boolean |
A data type that can have one of two possible values, usually true or false. |
| Comparison |
An operation used in a linear search to compare each element of the list with the specified value. |
| Complexity |
A measure of how much time and/or space is required to execute an algorithm or program. |
| Efficiency |
A measure of how well an algorithm uses time and/or space resources. |
| Element |
A single item in an array or list. |
| Index |
A position number indicating the location of an element within an array or list. |
| Linear Search |
Algorithm that searches for a specific element in a list or array by checking each element one at a time. |
| Linear Time Complexity |
A measure of time complexity in which the execution time increases linearly with the size of the input. |
| List |
An ordered collection of data. |
| O(N) |
The notation used to indicate linear complexity, where n is the size of the input. |
| Runtime |
The time taken to execute an algorithm or program. |
| Search |
The process of finding a specific value within an array or list. |
| Sequential Search |
Algorithm that searches a list or array one item at a time in a linear fashion. |
| Unordered |
A list that is not sorted according to any specific criterion. |
| Worst-Case Scenario |
The scenario in which an algorithm takes the longest time to complete. |
