Bottlenecks
Optimization may include finding a bottleneck, a critical part of the code that is the primary consumer of the needed resource — sometimes known as a hot spot. Often, the Pareto principle is applied. i.e., 20% of the code is responsible for 80% of the results.
In computer science, the Pareto principle can be applied to resource optimization by observing that 80% of the resources are typically used by 20% of the operations. In software engineering, it is often a better approximation that 90% of the execution time of a computer program is spent executing 10% of the code (known as the 90/10 law in this context).
More complex algorithms and data structures perform well with many items, while simple algorithms are more suitable for small amounts of data — the setup, initialization time, and constant factors of the more complex algorithm can outweigh the benefit.
In some cases, adding more memory can help to make a program run faster. For example, a filtering program will commonly read each line and filter and output that line immediately. This only uses enough memory for one line, but performance is typically poor. Performance can be greatly improved by reading the entire file then writing the filtered result, though this uses much more memory. Caching the result is similarly effective, though also requiring larger memory use.
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