Algorithm characterizations
An algorithm is like a set of instructions that tell you how to do something. Imagine if you wanted to cook a cake, but didn't know how to do it. An algorithm would tell you every step you need to take, like measuring ingredients, mixing them together, and baking in the oven.
Now, when we talk about characterizing an algorithm, we mean describing what kind of steps the instructions are made up of. There are different ways we can do this!
One way is to look at how long the algorithm takes to finish, or how many steps it takes to complete. Some algorithms might be really quick and only take a few steps, while others could take a long time and have many steps. We call this the "time complexity" of the algorithm.
Another way to characterize an algorithm is to look at how much memory it needs to work. Memory is like a workspace where the algorithm can keep track of things. Some algorithms might need a lot of memory, while others can work with very little. We call this the "space complexity" of the algorithm.
Finally, we can also describe algorithms based on the kinds of steps they use. Some algorithms might use a lot of repeating steps, or loops, while others might use a lot of branching steps that depend on certain conditions being true or false. We call these "control structures."
So, to summarize: characterizing an algorithm means describing how long it takes to finish, how much memory it needs, and what kinds of steps it uses.
Now, when we talk about characterizing an algorithm, we mean describing what kind of steps the instructions are made up of. There are different ways we can do this!
One way is to look at how long the algorithm takes to finish, or how many steps it takes to complete. Some algorithms might be really quick and only take a few steps, while others could take a long time and have many steps. We call this the "time complexity" of the algorithm.
Another way to characterize an algorithm is to look at how much memory it needs to work. Memory is like a workspace where the algorithm can keep track of things. Some algorithms might need a lot of memory, while others can work with very little. We call this the "space complexity" of the algorithm.
Finally, we can also describe algorithms based on the kinds of steps they use. Some algorithms might use a lot of repeating steps, or loops, while others might use a lot of branching steps that depend on certain conditions being true or false. We call these "control structures."
So, to summarize: characterizing an algorithm means describing how long it takes to finish, how much memory it needs, and what kinds of steps it uses.