Brute Force vs Greedy

Brute Force vs Greedy: two approaches compared

Algorithmic problem solving is a fundamental element in computer science, requiring the application of efficient strategies to obtain optimal or acceptable solutions in terms of time and space. Two distinct approaches in this context are known as Brute Force and Greedy. These represent two ends of the algorithmic complexity spectrum, each with its own advantages and limitations.

Fibonacci Series three algorithms

The Fibonacci Series: three different algorithms compared

The efficiency of algorithms plays a central role in software development, directly influencing the performance and responsiveness of applications. In this context, the Fibonacci series provides fertile ground for exploring and comparing different implementation strategies, from the classic recursive approach to more optimized solutions such as iteration and dynamic programming.

Recursive Algorithms

Recursive Algorithms

A recursive algorithm is an algorithm that solves a problem by dividing it into smaller sub-problems of the same nature. The solution of the overall problem is obtained by combining the solutions of the sub-problems. The recursive approach is based on recursive calling, which consists of invoking the same function (or procedure) within the very definition of that function.

Mergesort & Quicksort

Mergesort and Quicksort: Two Dominant Approaches for Efficient Sorting

Sorting data is one of the fundamental operations in computing, and choosing an appropriate sorting algorithm can significantly affect the performance of an application. Two of the best-known and widely used algorithms are Mergesort and Quicksort. These two approaches, both based on the “divide and conquer” principle, are capable of ordering sequences of data efficiently, but they adopt different strategies to achieve this goal.