MrComputerScience.com
Blog For Marketing And Tech Nerds
Algorithms are the skeleton key of computer science. Strip away frameworks, languages, and trends, and you are left with computation. What can be solved, how efficiently, and at what fundamental cost. This category exists for people who want to understand why software behaves the way it does, not just how to make it work today.
This section contains some of my best guides on algorithms, computational complexity, asymptotic analysis, lower bounds, and the deep structure of computation itself. We go far beyond Big O flashcards and interview trivia. You will find real discussions of amortized analysis, cache aware and cache oblivious algorithms, reductions, NP completeness, randomness, impossibility results, and the hidden constants that quietly dominate real systems.
I write about algorithms the way they are actually used, embedded in hardware, constrained by memory hierarchies, and shaped by adversarial inputs. You will learn why theoretically worse algorithms often win in practice, why some problems resist optimization no matter how much compute you throw at them, and why AI does not magically escape computational limits.
If you care about performance, scalability, or truth over hype, this category gives you mental models that last decades rather than release cycles.
Self-taught developers learn to build things. Algorithms courses teach you to analyze things. These are different skills built on different foundations. Most self-taught developers hit the algorithms …
Continue Reading about Why Do Self-Taught Developers Struggle With Algorithms and Data Structures? →
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? →
LeetCode prepares you for interviews. It does not prepare you for the work you do after you get hired. The algorithms that appear constantly in production engineering, especially in LLM tooling and …
Continue Reading about The Algorithms You Actually Use vs What LeetCode Tests →
You can get genuinely good at algorithms and data structures without a professor, a textbook, or a CS degree. LeetCode's free tier, NeetCode's free YouTube curriculum, and a local or free AI model for …
Continue Reading about Master Algorithms and Data Structures Without a Degree →
NISQ (Noisy Intermediate-Scale Quantum) devices cannot run Shor's or Grover's algorithms at meaningful scale today, let alone more complex fault-tolerant algorithms. The core challenges are qubit …
Continue Reading about Fault-Tolerant Quantum Algorithms Beyond Shor’s on NISQ Devices →
Cache-oblivious algorithms outperform cache-aware ones because they optimize for every level of the memory hierarchy simultaneously without being tuned for any specific one. Cache-aware algorithms are …
Continue Reading about How Cache-Oblivious Algorithms Beat Cache-Aware Design →
