> For the complete documentation index, see [llms.txt](https://catherine-leung.gitbook.io/data-strutures-and-algorithms/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://catherine-leung.gitbook.io/data-strutures-and-algorithms/algorithms-analysis.md).

# Algorithms Analysis

## What is Algorithms Analysis

When you write a program or subprogram you should be concerned about the resource needs of the program. The two main resources to consider are time and memory. These are separate resources and depending on the situation, you may end up choosing an algorithm that uses more of one resource in order to use less of the other. Understanding this will allow you to produce better code. The resource to optimize for depends on the application and the computing system. Does the program need to finish execution within a restricted amount of time? Does the system have a limited amount of memory? There may not be one correct choice. It is important to understand the pros and cons of each algorithm and data structure for the application at hand.

The amount of resources consumed often depends on the amount of data you have. Intuitively, it makes sense that if you have more data you will need more space to store the data. It will also take more time for an algorithm to run.   

{% hint style="info" %}
Algorithms Anaylsis does not answer the question "How much of a resource is consumed to process ***n*** pieces of data"... the real question it answers is "How much ***more*** of the same resource will it consume to process n+1 pieces of data"
{% endhint %}

In other words what we really care about is the growth rate of resource consumption with respect to the data size.

And with this in mind, let us now consider the growth rates of certain functions.

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