Reasons for Using Algorithms

Reasons for Using Algorithms

The term "algorithm" is widely used in computer science to describe a finite, deterministic, and effective method for solving problems, specifically for the implementation of computer programs. Algorithms are a core discipline within computer science and remain a primary subject of research in the field. Essentially, an algorithm is a problem-solving procedure expressed in a natural (human) language. These problem-solving steps are later translated into computer programs to accelerate or automate the resolution process. The choice of programming language used to express an algorithm depends largely on the programmer's preferences and expertise.

One of the key reasons to study algorithms from an academic standpoint is that algorithmic thinking provides the potential to solve even highly complex problems with minimal processing time. It can significantly streamline inefficient workflows by automating them. A single application might be responsible for processing millions of objects, where the functions or procedures involved represent the algorithmic steps. A program designed with an efficient algorithm can be exponentially faster—potentially millions of times faster—than one based on a poorly designed approach. The right algorithm significantly impacts both time and energy efficiency. Many companies are willing to invest in new computer systems not just for improved hardware, but also to purchase or license advanced algorithms that can enhance productivity.

From an academic and practical perspective, here are several reasons why adopting algorithms is essential:

1. Efficiency: Measuring the efficiency of an algorithm involves evaluating both CPU time and memory usage. Many programmers stop at obtaining the correct output, but fail to consider how much time and memory their algorithm consumes. The foundation of a good algorithm lies in time efficiency, memory efficiency, and output accuracy. Although each programmer may approach problem-solving differently, aiming for the same end result, the speed and memory use must be balanced to ensure a solution is both fast and accurate.

2. Abstraction: One of the strengths of algorithms is their ability to simplify complex problems. A highly intricate issue can be broken down into manageable, straightforward parts thanks to a well-structured and clearly defined algorithmic flow.

3. Reusability: An algorithm is a method, not a program. This means it should be applicable across different programming languages. A well-designed algorithm can be reused multiple times in various contexts, regardless of the programming language involved.

Reference:

KANI, Algorithms and Programming, 2024