What does the term "algorithm complexity" refer to in coding?

The term "algorithm complexity" refers specifically to the time and space resources required by an algorithm as it relates to the size of the input data. This concept helps in assessing how the performance of an algorithm scales when faced with larger datasets. Time complexity measures how the execution time increases with the input size, while space complexity focuses on how much memory an algorithm consumes as the input size grows.

Understanding these complexities is crucial for developers when choosing the most efficient algorithm for a given problem, as it can significantly impact the performance of applications, especially as they scale. High efficiency in both time and space can lead to quicker and more responsive applications.