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In computer science, best, worst, and average casesof a given algorithmexpress what the resourceusage is at least, at mostand on average, respectively. Usually the resource being considered is running time, i.e. time complexity, but could also be memory or some other resource. Best case is the function which performs the minimum number of steps ...
In computer science, the analysis of algorithms is the process of finding the computational complexity of algorithms —the amount of time, storage, or other resources needed to execute them. Usually, this involves determining a function that relates the size of an algorithm's input to the number of steps it takes (its time complexity) or the ...
Graphs of functions commonly used in the analysis of algorithms, showing the number of operations N as the result of input size n for each function. In theoretical computer science, the time complexity is the computational complexity that describes the amount of computer time it takes to run an algorithm. Time complexity is commonly estimated ...
Event chain diagrams are visualizations that show the relationships between events and tasks and how the events affect each other. Event chain diagrams are introduced as a part of event chain methodology. Event chain methodology is an uncertainty modeling and schedule network analysis technique that is focused on identifying and managing events ...
A discrete-event simulation ( DES) models the operation of a system as a ( discrete) sequence of events in time. Each event occurs at a particular instant in time and marks a change of state in the system. [1] Between consecutive events, no change in the system is assumed to occur; thus the simulation time can directly jump to the occurrence ...
In theoretical computer science and mathematics, computational complexity theory focuses on classifying computational problems according to their resource usage, and explores the relationships between these classifications. A computational problem is a task solved by a computer. A computation problem is solvable by mechanical application of ...
Amortized analysis. In computer science, amortized analysis is a method for analyzing a given algorithm's complexity, or how much of a resource, especially time or memory, it takes to execute. The motivation for amortized analysis is that looking at the worst-case run time can be too pessimistic. Instead, amortized analysis averages the running ...
Algorithmic efficiency. In computer science, algorithmic efficiency is a property of an algorithm which relates to the amount of computational resources used by the algorithm. Algorithmic efficiency can be thought of as analogous to engineering productivity for a repeating or continuous process. For maximum efficiency it is desirable to ...