DEV Community

Cover image for Learning Algorithms by Watching Them Run (A Visual Walkthrough with Learn-Algo)
satya subudhi
satya subudhi

Posted on

Learning Algorithms by Watching Them Run (A Visual Walkthrough with Learn-Algo)

#algorithms #tooling #showdev #learning

Most of us learned algorithms the same way:

  • Read a definition
  • Look at pseudocode
  • Try to memorize the steps
  • Hope it “clicks” later

For simple cases, that works. But once you hit sorting edge cases, recursion, trees, or ML concepts, things get fuzzy fast.

I built Learn-Algo to fix exactly that problem.

👉 https://learn-algo.com/

Instead of reading about algorithms, Learn-Algo lets you watch them execute step by step, pause them, rewind them, and experiment with inputs — the same way you’d debug real code.

In this post, I’ll walk through:

  • How Learn-Algo visualizes algorithms internally
  • A concrete example (sorting / traversal / ML flow)
  • Why visual execution leads to better algorithm intuition

No theory overload. No math walls. Just how algorithms actually behave.

Why “Seeing the Algorithm” Changes Everything

Algorithms aren’t static — they’re processes.

When we only read code like this:

for i in range(n):
  for j in range(0, n - i - 1):
    if arr[j] > arr[j + 1]:
      swap(arr[j], arr[j + 1])
Enter fullscreen mode Exit fullscreen mode

we have to mentally simulate:

  • Comparisons
  • Swaps
  • Loop boundaries
  • State changes

That mental simulation is the hard part.

Learn-Algo offloads that cognitive load by rendering each step visually:

  • Which elements are compared
  • Which values move
  • How many operations actually occur

You stop guessing and start observing.

A Quick Walkthrough: Understanding Sorting Visually

Let’s take a simple example.

When you open a sorting algorithm in Learn-Algo, you don’t just click “Run”.

You can:

  • Choose or generate input data
  • Start execution step by step
  • Pause after each comparison or swap
  • Replay specific moments

As the algorithm runs, you see:

  • Active indices highlighted
  • Swaps animated
  • Progress across iterations

This instantly answers questions like:

  • Why is this algorithm slow for large inputs?
  • Where does the extra time complexity come from?
  • What changes when input is nearly sorted?

These are things most tutorials say, but rarely show.

From DSA to ML: Same Visual Philosophy

The same idea applies beyond classic DSA.

For machine learning concepts like:

  • Linear regression
  • Clustering
  • Optimization

Learn-Algo visualizes:

  • How data points move
  • How models adjust step by step
  • What “convergence” actually looks like

This is especially helpful if you’re coming from a programming background and find ML math intimidating at first.

Who This Walkthrough Is For

This walkthrough is for you if:

  • You understand syntax but struggle with intuition
  • You’ve memorized algorithms but can’t explain them
  • You’re preparing for interviews and want deeper clarity
  • You learn better by doing than by reading

You don’t need advanced math or deep CS theory to get value — just curiosity.

If algorithms ever felt abstract or “magical”, this is about making them predictable and understandable.

👉 Explore the playground: https://learn-algo.com/

Top comments (0)