<aside> 💡 Asymptotic Analysis

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This is just the the beginning of my journey learning Data Structures.

What is relevant to keep in mind and worry about in an algorithm?

Readability, simplicity and modularity are strong fundamentals to think about when writing code, but in this aspect nothing beats its performance.

• Breaking down the concepts

Obviously, test it make sure it works the way you expect. It must be correct.

Whats is there to be analyzed?

Analyzing means the quantity of resources that your algorithm uses to operate. It separates the inefficient code from good code, making your program smoother and helping you make decisions about which algorithm to use.

The short answer as of right now is: Execution Time. However, you can analyse other areas, such as processing power and memory.

Comparing

Don’t underestimate seeing the algorithm behavior for different scenarios and inputs.

Comparing different solutions is a must.

Empirical Analysis

X (execution time) and Y (Input’s size) comparing different algorithms implementation.

This is a very expensive in terms of time and money way of comparing algorithms.