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Bellman Ford and negative weights algorithm graph.
  • Dr. Ingrid Falk-Weller
  • April 6, 2026
  • (0)
  • Algorithms

Slower on Purpose, Because It Checks Every Edge Again

I remember sitting in a windowless lab during my first year in industry, staring at a production trace that made absolutely no sense. We were using Dijkstra’s for everything because it was fast, but our cost metrics were behaving like…

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Dijkstra and its assumptions with negative edges.
  • Dr. Ingrid Falk-Weller
  • April 4, 2026
  • (0)
  • Algorithms

One Negative Edge Breaks the Whole Guarantee

I remember sitting in a windowless server room during my second year in industry, staring at a routing table that made absolutely no sense. We were chasing a phantom bug for three days, assuming our shortest-path logic was flawless, only…

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Backtracking and depth first search applications.
  • Dr. Ingrid Falk-Weller
  • March 26, 2026
  • (0)
  • Algorithms

Dfs Is Not About Depth, It Is About Backtracking

I remember sitting in a windowless lab during my postdoc, staring at a simulation that refused to converge, feeling the distinct, cold frustration of realizing that the textbook implementation I was using was completely ill-suited for our actual data topology.…

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Breadth first search in practice for shortest paths.
  • Dr. Ingrid Falk-Weller
  • March 16, 2026
  • (0)
  • Algorithms

Bfs Finds the Shortest Path When Every Edge Costs the Same

I remember sitting in a windowless server room three years ago, watching a cluster slowly choke to death because someone decided to implement a massive, unoptimized graph traversal using a textbook definition of BFS. They had the theory perfectly right,…

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Graph representations compared: matrix vs list.
  • Dr. Ingrid Falk-Weller
  • March 13, 2026
  • (0)
  • Algorithms

Dense Graphs Want a Matrix, Sparse Graphs Want a List

I spent three weeks of my life in a graduate research lab trying to optimize a GNN, only to realize I had wasted hundreds of compute hours because I’d chosen an adjacency matrix for a graph that was almost entirely…

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Exchange argument proving greedy correctness.
  • Dr. Ingrid Falk-Weller
  • March 6, 2026
  • (0)
  • Algorithms

An Exchange Argument Is the Only Honest Proof

I remember sitting in a windowless graduate lab at 2:00 AM, staring at a trace of a scheduling algorithm that looked perfect on paper but was failing spectacularly in production. I had spent weeks convinced that my logic was sound,…

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Greedy algorithms and when they fail.
  • Dr. Ingrid Falk-Weller
  • February 27, 2026
  • (0)
  • Algorithms

Greedy Works Until Somebody Constructs the Counterexample

I remember sitting in a windowless lab during my second year of grad school, staring at a distributed scheduler that was eating its own tail. We had implemented a classic greedy approach, convinced that picking the shortest task first was…

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Memoisation versus tabulation memory profile comparison.
  • Dr. Ingrid Falk-Weller
  • February 21, 2026
  • (0)
  • Algorithms

Same Answer, Different Memory Profile

I spent three years in academia watching brilliant students lose sleep over textbook definitions that felt more like religious dogma than engineering principles. Most tutorials treat the debate of memoisation versus tabulation as a simple choice between “top-down” and “bottom-up,”…

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Learning dynamic programming from scratch with recursion.
  • Dr. Ingrid Falk-Weller
  • February 12, 2026
  • (0)
  • Algorithms

Recursion With a Notebook Is Dynamic Programming

I remember sitting in a windowless grad student lounge at 3:00 AM, staring at a whiteboard covered in recursive calls that felt more like a fever dream than actual logic. Everyone around me was treating dynamic programming like some mystical…

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Visualizing divide and conquer patterns.
  • Dr. Ingrid Falk-Weller
  • February 6, 2026
  • (0)
  • Algorithms

Cutting the Problem in Half Twice Is Not the Same as Cutting It in Four

I spent three weeks in my late twenties trying to optimize a distributed sorting routine, only to realize I had fallen into the classic trap of applying divide and conquer patterns where they didn’t belong. I was so enamored with…

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