DIVIDE AND CONQUER VS DYNAMIC PROGRAMMING The huge rise in computing power over the last few decades has greatly improved our capacity to solve complicated problems and evaluate their effectiveness in a variety of scientific and technical fields. These strategies have become more profitable to make selections as a result of recent advancements in the field of optimization. Divide and conquer algorithms are well-suited to current parallel computers because they contain a lot of inherent parallelism and perform well with caches and deep memory hierarchies. Dynamic Programming is a strong tool for producing classic algorithms for a range of optimization problems. It is one of the elegant algorithm design standards. This blog explains the differences/similarities between both the approaches with the help of two examples: Fibonacci series and binary search. Table of Contents : Divide and Conquer Divide and Conquer Algorithm steps: When & Where to use Divide and Conquer...