MrComputerScience.com
Blog For Marketing And Tech Nerds
Algorithms are the core of computer science, and this category is where I explore the ideas that make software efficient, scalable, and elegant. You will find articles on algorithms, data structures, time complexity, graph algorithms, optimization, and the tradeoffs that shape real software systems.
I enjoy studying why one solution outperforms another, how complexity changes design decisions, and which techniques still hold up as problems grow larger. If you like efficient thinking and clever problem solving, this category should feel like home.
Browse the articles below to explore algorithms in a deeper and more practical way.
A cache-oblivious algorithm achieves optimal cache performance without knowing the cache size, line size, or memory hierarchy at design time. By recursively dividing problems until sub-problems fit in …
Continue Reading about What Is a Cache-Oblivious Algorithm and Why Does It Matter? →
Both Quicksort and Mergesort have O(n log n) average time complexity, but Quicksort is faster in practice on most hardware. The reason is cache behavior. Quicksort operates in-place and accesses …
Continue Reading about Why Does Quicksort Beat Mergesort in Real-World Software? →
Dijkstra's algorithm finds the shortest path but explores nodes in every direction equally, which is expensive on a road network with millions of nodes. A* uses a heuristic to bias the search toward …
Continue Reading about Why Does Google Maps Use A* Instead of Dijkstra for Routing? →
