4 posts tagged with "Algorithms"

I've always been more interested in the plumbing of the internet than the web pages sitting on top of it. Every time you load a page, your packets hop across a patchwork of independent networks called Autonomous Systems (ASes), each with its own ASN (Autonomous System Number). Who connects to whom, and how, is what I wanted to map. Now that it's so easy to vibe code with AI, any idea or interest can be turned into a project in minutes. So I built an interactive map of the internet's AS-level topology, and here's how it works and what it shows.

More than just an interview question​

I've sat on both sides of countless technical interviews over my years in networking. There's this familiar dance that happens when discussing OSPF: the candidate confidently states "OSPF uses Dijkstra's algorithm for route calculation," and I'll nod approvingly. But here's the thing - in hundreds of these exchanges, I've never once asked a candidate to explain what that actually means, and no one's ever asked me to explain it either.

Introduction: Beyond the Basics​

FizzBuzz has long been a staple of programming interviews. The problem is deceptively simple: print numbers from 1 to n, but replace multiples of 3 with "Fizz", multiples of 5 with "Buzz", and multiples of both with "FizzBuzz". It's not meant to be a challenging algorithmic puzzle; most candidates with basic programming knowledge should solve it without difficulty.

So why does this trivial problem persist in the interview landscape? Because I believe FizzBuzz's true value isn't in filtering out candidates who can't code—it's in opening discussions about complexity, language characteristics, optimisation, and the subtle costs of different operations. The best interviewers don't just ask candidates to solve FizzBuzz; they use it as a starting point for a deeper technical conversation.

I've put together a summary of some common search algorithms and how they work. This post covers key search algorithms used in computer science, explaining their approaches, strengths, weaknesses, and showing Python implementation examples.