DEV Community: Robin Nayak

The Difference Between Reading an Algorithm and Understanding It

Robin Nayak — Fri, 01 May 2026 03:54:40 +0000

You read the explanation. Every sentence makes sense. Then you close the tab, open a problem, and the u
understanding is gone.
This experience is so common it should have a name.
It happens because reading and understanding are two different cognitive activities, and most DSA resources only support the first.
Why reading is not enough
When you read an algorithm explanation, you follow a sequence of sentences in order. Each one makes sense. The logic holds together. But this creates surface-level comprehension: the ability to follow, not the ability to apply.
To apply an algorithm to a new input, you need a behavioral model. You need to know not just what the algorithm is, but what it does. What happens to a specific array at step 4? Why did the pointer move in that direction? What does the data structure look like right now?
That behavioral model does not come from reading. It comes from watching.
The behavioral layer
Think about how the best DSA teachers actually explain concepts. They do not just read a definition aloud. They trace execution on a specific example, step by step, narrating what changes and why.
That trace is the behavioral layer. It is where the mental model forms. It is what makes the explanation stick.
Almost every self-study resource skips this layer entirely. You go from definition to pseudocode to problems, with nothing in between that shows how the algorithm actually behaves.
A practical approach
Before starting a new algorithm:

Find an animated walkthrough, not a fast, pre-built animation, but one where you can control the pace and move step by step.
Trace a small, specific example manually before looking at code.
Ask at every step: what changed, why, and what does the structure look like right now?

That slow, visual, state-focused process is what builds the mental model that makes practice productive.
DsaVisual is built specifically for this phase: step-by-step visual execution with full state visibility at every move, plain-language annotations explaining why each step happens, and full offline support so it works anywhere.

📲 Download on Google Play: https://play.google.com/store/apps/details?id=com.robin_nayak.dsavisualmobile&pcampaignid=web_share

The Difference Between Reading an Algorithm and Understanding It

Robin Nayak — Thu, 30 Apr 2026 01:08:31 +0000

You read the explanation. Every sentence makes sense. Then you close the tab, open a problem, and suddenly the understanding is gone.
This experience is so common it should have a name.
It happens because reading and understanding are two different cognitive activities — and most DSA resources only support the first one.
Why reading is not enough
When you read an algorithm explanation, you follow a sequence of sentences in order. Each one makes sense. The logic holds together. But this only creates surface-level comprehension — the ability to follow, not the ability to apply.
To apply an algorithm to a new input, you need a behavioral model. You need to understand not just what the algorithm is, but what it does. What happens to a specific array at step 4? Why did the pointer move in that direction? What does the structure look like right now?
That behavioral model does not come from reading. It comes from watching.
The behavioral layer
Think about how the best DSA teachers actually explain things. They do not just read a definition out loud. They trace execution on a specific example — step by step — narrating what changes and why.
That trace is the behavioral layer. It is where the mental model forms. It is what makes the explanation stick.
Almost every self-study resource skips this layer entirely. You go from definition to pseudocode to problems, with nothing in between that shows how the algorithm actually behaves.
A practical approach
Before starting a new algorithm:

Find an animated walkthrough — not a fast, pre-built animation, but one where you can control the pace and go step by step.
Trace a small, specific example manually before looking at code.
At every step, ask: what changed? Why? What does the structure look like right now?

Day 1 — Why 70% of Learners Struggle With DSA (And It's Not What You Think)

Robin Nayak — Mon, 27 Apr 2026 02:15:41 +0000

Most articles about struggling with DSA will tell you to practice more, study harder, or find better resources.
That advice misses the actual problem.
Over 70% of learners report struggling with DSA not because the concepts are too complex — but because they cannot picture how algorithms work internally. It is a representation problem, not an intelligence problem.
The format mismatch

Algorithms are dynamic. They have state that changes at every step. They make decisions based on what happened before. The value of a variable at step 7 depends on what happened at steps 1 through 6.
This is an inherently time-based, visual thing.
And yet the standard format for teaching it is: a block of code, a paragraph of text, a static diagram. None of these can show what is actually happening inside the algorithm as it runs.
What actually helps
The learners who get good at DSA quickly almost always found a way to see it:

Drawing arrays on paper and tracing execution manually
Finding the specific YouTube video where someone animates the algorithm slowly
Working with a tutor who traces execution on a whiteboard in real time

These are workarounds. They work because they provide something the standard format does not: a live, step-by-step view of what the algorithm is doing.

The fix is a format change, not more content
More explanation does not close this gap. More problems do not either — at least not before the mental model is solid.

What closes it is seeing the execution. Watching the array change. Observing which elements move and why. Following the pointer across the structure. Step by step, with full state visible at every move.
That is what DsaVisual is built to provide — a visual, interactive DSA tutorial platform where every algorithm runs step by step, works offline, and includes a built-in interview checklist.

The representation is the missing piece. Fix the representation, and the understanding follows.
📲 Try DsaVisual on Google Play: [Comming Soon]

I built an open-source tool to visualize React/Next.js component hierarchy

Robin Nayak — Fri, 24 Apr 2026 00:30:53 +0000

The Problem

As React and Next.js apps grow, it becomes hard to answer simple questions:

Which component uses which hook?
Where is this API being called?
What breaks if I change this file?
Which components are duplicated across pages?

You end up jumping between 10 files just to trace one data flow.

What I Built

ReactGraph is an open source developer tool that analyzes your React/Next.js project and renders it as an interactive hierarchy graph.

Pages → Components → Hooks → APIs

Every node is clickable. Every connection is visible. Props and TypeScript types are shown inline on each node.

Features

Interactive graph — zoom, pan, click any node to inspect it
Props & types — see exactly what each component expects
Impact Analysis — click a node to see everything that breaks if you change it
Health Check — run a TypeScript check and see errors mapped onto the graph
Circular Dependency Detection — automatically flags components in circular render loops
Prop Drilling Detection — finds props passed more than 3 levels deep
Move to Shared — detects components used in multiple pages that should be in your shared folder
Unused Component Detection — surfaces dead code you can safely delete

How to Use It

Option 1 — npm package (run from any project):

npm install @reactgraph-ui/core
npx reactgraph serve .

Then open http://127.0.0.1:4174 in your browser.

Option 2 — VS Code extension:

Install from the marketplace, open any React project, and run:

Ctrl+Shift+P → ReactGraph: Open Graph

Works With

Next.js App Router
Next.js Pages Router
Create React App
Vite + React
Any TypeScript React project

DEV Community: Robin Nayak

The Difference Between Reading an Algorithm and Understanding It

The Difference Between Reading an Algorithm and Understanding It

Day 1 — Why 70% of Learners Struggle With DSA (And It's Not What You Think)

I built an open-source tool to visualize React/Next.js component hierarchy

The Problem

What I Built

Features

How to Use It

Works With

Links