DEV Community: Darshan Raval

Why Inclusive Tech Teams Build Better Software 🚀

Darshan Raval — Wed, 11 Mar 2026 16:25:49 +0000

This is a submission for the 2026 WeCoded Challenge: Echoes of Experience

When people think about software development, the first things that come to mind are usually code, algorithms, architecture, and performance. 💻

But after spending a few years working in tech, I realized something important:

Great software is not only built by great code — it’s built by great teams.

And the strongest teams are inclusive teams.

Inclusive teams bring together people with different perspectives, backgrounds, and experiences. And interestingly, this diversity doesn’t just make the workplace better — it actually helps build better software.

In this article, I want to share a few observations and lessons from my journey as a developer, and why inclusion in tech teams matters more than we often realize.

Software Is Built for Humans 👥

At the end of the day, every application we build is used by real people.

People from different:

genders
cultures
backgrounds
abilities
experiences

But if the team building the product lacks diversity, something important gets missed: perspective.

A team where everyone thinks similarly might unintentionally design products that only work well for people like them.

Inclusive teams reduce this problem because they bring multiple viewpoints into discussions.

For example, even something simple like a signup form can raise questions like:

Is the language inclusive?
Is the UI easy for first-time users?
Is the design accessible?

When teams include different perspectives, these questions come naturally — and the product becomes better for everyone.

Different Perspectives Improve Problem Solving 🧠

One of the biggest advantages of inclusive teams is better problem solving.

When developers from different backgrounds approach a problem, they often think differently. That leads to richer discussions and better solutions.

In engineering conversations, I’ve seen moments where someone’s perspective completely changed the direction of the solution.

Sometimes someone asks a simple question like:

“Why are we doing it this way?”

And suddenly the whole team starts rethinking the approach. 😄

Other times someone notices a usability issue developers missed, or suggests a simpler approach based on past experience.

These moments are powerful because they challenge assumptions — and challenging assumptions is where innovation begins.

Inclusion Builds Psychological Safety 🤝

Inclusion is not just about who is present in the room.

It’s about who feels comfortable speaking in the room.

When teams encourage respect, openness, and collaboration, people feel safer sharing their ideas.

And when people feel safe, something amazing happens:

More ideas are shared 💡
More questions are asked ❓
More problems are caught early 🔍

In engineering, this matters a lot.

A team where someone feels comfortable saying “Hey, I think something might be wrong here” will always outperform a team where people stay silent.

Inclusive teams create an environment where learning and improvement happen naturally.

Better Teams Build Better Products 🛠️

Technology influences how people live, work, communicate, and learn.

So as engineers, we’re not just writing code — we’re shaping experiences used by millions of people.

Inclusive teams help ensure that the products we build:

consider different user needs
avoid harmful assumptions
support accessibility and usability

When diverse teams collaborate, the product becomes more thoughtful and more adaptable.

In many ways, inclusive teams act like a built-in quality improvement system for software.

Small Actions That Create Inclusive Teams 🌱

Building inclusive teams doesn’t always require big policies or major changes.

Often, it starts with small everyday actions.

Some simple things that help create inclusive environments include:

✨ Encouraging every voice in discussions
Give quieter team members space to share ideas.

✨ Being mindful of assumptions
Not everyone has the same experiences.

✨ Supporting mentorship and learning
Helping others grow strengthens the whole team.

✨ Listening actively
Sometimes the most powerful thing we can do is simply listen.

Inclusion grows slowly through daily behavior — not just company policies.

The Future of Engineering Is Collaboration 🌍

Software systems are becoming more complex every year.

No single developer can know everything anymore.

The best solutions come from collaboration between people with different strengths and perspectives.

As developers, we spend a lot of time improving our technical skills:

learning new frameworks
mastering system design
optimizing performance

But the future of engineering will also depend on something equally important:

How well we work with people who think differently from us.

Inclusion isn’t just a social goal.

It’s an engineering advantage.

Teams that embrace diverse perspectives make better decisions, build stronger systems, and create products that work for more people.

And honestly, that’s what great software is all about.

💬 Let’s keep building technology that reflects the diversity of the people who use it.

🚨 AI Will Not Replace Developers – Lazy Developers Will Be Replaced

Darshan Raval — Sun, 22 Feb 2026 10:55:09 +0000

AI is not coming for your job.
It’s coming for your excuses. 😌

Every week on LinkedIn I see:

Coding is dead 💀
AI writes better code than humans 🤖
Don’t learn programming in 2026 😱

Relax.

Take a breath.

AI is not replacing developers.

AI is replacing developers who only know how to Google + copy + paste.

And that’s uncomfortable to hear. 👀

🤖 What AI Is Actually Good At

AI is amazing at:

Writing CRUD APIs in 30 seconds
Generating boilerplate
Explaining regex (finally 😭)
Creating unit tests
Refactoring messy functions

Basically…

AI is the ultimate intern who never sleeps.

But here’s the twist.

🧨 Real-Life Scenario #1 – The 2 AM Production Incident

Production server is down.
Customers are angry.
Revenue is bleeding. 💸

Error log says:

Memory leak – Node process crashed

You open AI and ask:

Fix memory leak in Node app

AI gives 300 lines of suggestion.

But…

Do you understand event loop?
Do you know how garbage collection works?
Can you trace heap usage?
Do you know which dependency is leaking?

AI gives suggestions.

You still need understanding.

And at 2 AM, AI won’t join your Teams war room call. 😅

You will.

🧠 Real-Life Scenario #2 – “It Works on My Machine”

Junior dev:

“AI generated this. It works.”

Senior dev:

“Why did you choose this architecture?”

Junior dev:

“… because AI said so.”

That’s not engineering.
That’s dependency.

📉 Who Is Actually in Danger?

Let’s be brutally honest.

If your workflow is:

Copy from Stack Overflow
Paste
Pray it compiles
Push to production

Then yes.

AI is faster than you.

Much faster. ⚡

Because AI is EXTREMELY good at average work.

📈 Who Is Becoming Powerful?

The developer who:

Understands fundamentals
Knows system design
Uses AI for speed
Reviews output critically
Can explain why something works

AI is not replacing them.

AI is making them 5x faster. 🚀

🏗️ Real-Time Corporate Example

Let’s say you work in a big IT company.

Client says:

“We need to scale from 10k to 1M users.”

AI can generate microservices.

But can it:

Understand business SLA?
Design failover strategy?
Plan caching layers?
Decide between vertical vs horizontal scaling?
Handle cost optimization?

That’s engineering.

Not prompting.

🧃 Meme Time

Old Developer:

I write everything from scratch.

Average Developer:

I copy from GitHub.

Lazy Developer:

AI write everything.

Smart Developer:

AI write draft. I improve it.

Elite Engineer:

I design system. AI accelerates execution.

⚔️ The New Developer Hierarchy (2026)

Level 1 – Prompt Typers 🤖
Level 2 – AI-Dependent Devs
Level 3 – AI-Assisted Engineers
Level 4 – System Thinkers 🧠
Level 5 – Problem Owners 💼

Guess who survives long-term?

Level 3 and above.

🎯 The Real Shift

Before:

You were paid to write code.

Now:

You are paid to reduce uncertainty.

Typing speed is irrelevant.

Thinking clarity is currency. 💰

🔥 The Brutal Truth

AI doesn’t remove jobs.

It removes:

Comfort zones
Low effort
Shallow understanding
Tutorial dependency

AI exposes who actually understands what they’re building.

And that scares people.

🧩 The Real Competition

AI is not your enemy.

The developer who:

Understands architecture
Communicates clearly
Uses AI better than you
Learns faster than you

That person is your competition.

🧨 Final Punchline

The industrial revolution didn’t remove workers.

It removed workers who refused to adapt.

AI is not replacing developers.

It is replacing lazy developers.

So ask yourself honestly:

If AI disappears tomorrow…
Can you still build, debug, and design confidently?

If yes — you’re safe.
If no — start today.

If this triggered you a little…

Good. Growth starts with discomfort. 😉

Thanks :) See you soon :)

🧠 Mastering VS Code Debugger for Node.js: A Real-World Guide to Fixing Production Bugs Faster 🚀

Darshan Raval — Fri, 30 Jan 2026 16:56:26 +0000

Let’s understand how we can debug in Advanced Mode.

🔎 1️⃣ Variables

👉 What is it?

When the debugger stops at a line (breakpoint), it shows the current value of all variables at that exact moment.

👉 Example:

function add(a, b) {
  const sum = a + b;
  return sum;
}

add(5, 3);

If you put a breakpoint on: const sum = a + b; ( Line 2 )

In the Variables panel, you’ll see:

👉 What is it used for?

To check if values are as expected
To inspect object structure
To examine API responses

In production debugging, this is a lifesaver.

2️⃣ Watch

👉 What is it?

In Watch, you manually add an expression, and the debugger shows its value at every step.

Now, let's take same example and let's put express there and check what it'll give output,

In this -> I added one expression that is "a+b" and Enter so output would be this,

👉 When to use it?

When you want to track a specific variable
When you need to repeatedly check a condition
When inspecting deep properties inside complex objects

Another Example is,

I want to get the length of one array so just put "a.length" and we will get output,

📚 3️⃣ Call Stack

👉 What is it?

It shows the function call chain.

🔍 What This Means

The stack shows the execution path:

main() started everything
main() called processOrder()
processOrder() called validatePayment()
Error occurred inside validatePayment()

This is the exact function chain.

🎯 Why This Is Powerful

Imagine in production:

You only see: Payment validation failed
You don’t know which API triggered it
You don’t know which middleware called it

Call stack tells you:

👉 Where the error started
👉 Who called it
👉 How execution reached there

No guessing. No extra logs.

📜 4️⃣ Loaded Scripts

👉 What is it?

It shows which JavaScript files are currently loaded in the debugger.

In a Node app, this includes:

Your source files
node_modules files
Compiled/transpiled files

👉 What is it used for?

To check if the correct file is loaded
To verify the correct build version is running
To debug source map issues

You will see:

index.js
math.js
Node internal files
Files from node_modules (if any installed)

🔍 What This Means

Loaded Scripts shows all JavaScript files currently active in memory during debugging.

In a real Node app, this includes:

✅ Your source files
✅ node_modules packages (Express, Redis, etc.)
✅ Internal Node.js files
✅ Compiled/transpiled files (if using TypeScript or Babel)

🎯 Why This Is Useful

1️⃣ Check if the Correct File Is Loaded
2️⃣ Verify Correct Build Version
3️⃣ Debug Source Map Issues (TypeScript Case)

🛑 5️⃣ Breakpoints

Let's create one file call test.js

function getUser(id) {
  console.log("Fetching user...");

  const users = [
    { id: 1, name: "Darshan", role: "ADMIN" },
    { id: 2, name: "Rahul", role: "USER" },
  ];

  const user = users.find((u) => u.id === id);

  if (!user) {
    throw new Error("User not found");
  }

  return user;
}

function resolver(args, context) {
  console.log("Inside resolver...");

  const user = getUser(args.id);

  if (context.role !== "ADMIN") {
    throw new Error("Unauthorized access");
  }

  return user;
}

function main() {
  const args = { id: 1 };
  const context = { role: "USER" }; // Change to ADMIN later

  const result = resolver(args, context);

  console.log("Result:", result);
}

main();

🔴 1️⃣ Normal Breakpoint

Now, put the debug point at here,

const user = getUser(args.id);

And run the code in Javascript Debug Terminal and once debug point reach to that place then you will see,

👉 Execution will stop there.
Now check:

Variables Panel:

args
context

You can inspect:

args = { id: 1 }
context = { role: "USER" }

Press ▶ Continue — it will move forward.

🟡 2️⃣ Conditional Breakpoint

Now put breakpoint on:

const user = users.find((u) => u.id === id);

Right-click → Add Condition:

id === 2

Now change in main():

const args = { id: 2 };

Debugger will stop only when id = 2.

This is powerful in loops or bulk processing.

🎮 Debug Controls (Test Them Now)

⏭ Step Over

Moves to next line
(Does NOT enter function)

⏬ Step Into

Goes inside function

If paused at:

const user = getUser(args.id);

Press Step Into → you enter getUser.

⏫ Step Out

If you're inside getUser, press Step Out → it exits and returns to resolver.

▶ Continue

Runs until next breakpoint or error.

Thanks :)

🚀 How We Reduced API Response Time by 60% in Node.js Using Caching, Query Optimization & Performance Profiling

Darshan Raval — Wed, 28 Jan 2026 18:11:30 +0000

Performance issues in backend systems rarely come from one obvious bug.

In our production system, a high-traffic API showed:

📉 P95 latency ~ 820ms
📈 Frequent database CPU spikes
⛔ Increased timeout rates during traffic bursts

After a structured optimization process, we reduced:

⚡ P95 latency: 820ms → 310ms
🧠 Database CPU usage reduced by ~40%
📊 Timeout rate reduced by ~70%

Here’s the exact breakdown of what we did.

1️⃣ Step One: Measure Before Optimizing

Before touching any code, we collected:

P50 / P95 / P99 latency
Slow query logs
DB execution plans
CPU & memory metrics
Event loop lag

We added a lightweight response-time logger:

app.use((req, res, next) => {
  const start = process.hrtime.bigint();

  res.on("finish", () => {
    const duration =
      Number(process.hrtime.bigint() - start) / 1_000_000;

    console.log(`${req.method} ${req.url} - ${duration.toFixed(2)}ms`);
  });

  next();
});

🔎 Observation

~68% latency was database time
~20% was repeated identical queries
Remaining was serialization + network overhead

Conclusion:
🧩 Primary bottleneck = Database layer.

2️⃣ Query Optimization (Biggest Impact 🔥)

❌ Problem 1: Missing Composite Index

Original query:

SELECT * 
FROM orders
WHERE user_id = $1
AND status = 'completed'
ORDER BY created_at DESC
LIMIT 20;

Execution plan showed:

Sequential scan
High disk I/O
Large row filtering

✅ Fix: Composite Index

CREATE INDEX idx_orders_user_status_created
ON orders(user_id, status, created_at DESC);

📊 Result

Query time: 180ms → 35ms
Removed full table scan
Reduced disk reads significantly

Indexing alone reduced endpoint latency by ~25%.

❌ Problem 2: Over-Fetching Data

Original:

SELECT * FROM users WHERE id = $1;

But API only needed:

name
profile_picture

✅ Optimized Query

SELECT name, profile_picture
FROM users
WHERE id = $1;

*🎯 Impact *

Reduced payload size
Lower memory allocation
Faster JSON serialization

Small change. Measurable gain.

❌ Problem 3: N+1 Query Pattern

Original logic:

const orders = await getOrders(userId);

for (const order of orders) {
  order.items = await getItems(order.id);
}

Under 20 orders → 21 queries.

✅ Optimized Join Query

SELECT o.id, o.created_at, i.product_id, i.quantity
FROM orders o
LEFT JOIN order_items i ON i.order_id = o.id
WHERE o.user_id = $1;

📈 Result

Drastically reduced DB round trips

Improved P95 latency stability

3️⃣ Introducing Multi-Layer Caching 🧠

Important principle:

⚠️ Do NOT cache blindly.
Cache only:

Read-heavy endpoints
Expensive aggregations
Low-volatility data

🟢 Layer 1: In-Memory Cache (Short TTL)

Used for ultra-hot endpoints.

import NodeCache from "node-cache";

const cache = new NodeCache({ stdTTL: 30 });

async function getUserProfile(userId) {
  const key = `user:${userId}`;

  const cached = cache.get(key);
  if (cached) return cached;

  const data = await fetchFromDB(userId);
  cache.set(key, data);

  return data;
}

Use case:

Frequently accessed profile endpoints
Dashboard metadata

Latency improvement: ~10–15%

🟡 Layer 2: Redis Distributed Cache

Used for:

Aggregated stats
Leaderboards
Expensive computations

async function getDashboardStats(userId) {
  const key = `dashboard:${userId}`;

  const cached = await redis.get(key);
  if (cached) return JSON.parse(cached);

  const data = await computeStats(userId);

  await redis.set(key, JSON.stringify(data), "EX", 120);

  return data;
}

📊 Impact

Significant DB load reduction
Improved P95 & P99 latency
Reduced spike sensitivity

4️⃣ Cache Invalidation Strategy ⚠️

Caching without invalidation creates stale data problems.

We used:

Event-based invalidation after writes
Short TTL for volatile data
Versioned keys when necessary

Example:

await redis.del(`dashboard:${userId}`);

Triggered immediately after order creation.

We avoided:

Long-lived static caches
Global flushes
Blind TTL-only approaches

5️⃣ Connection Pool Optimization 🔌

We observed:

DB pool exhaustion during spikes
Increased wait time for connections

Original pool size: 10
Optimized to: 25 (after validating DB capacity)

📈 Result

Reduced queuing delay
Stabilized latency under burst traffic

6️⃣ JSON Serialization Optimization ⚡

Large nested objects increased serialization cost.

Instead of returning deeply populated objects, we:

Reduced unnecessary fields
Flattened response structure
Avoided over-population

Serialization overhead dropped ~8–10%.

7️⃣ Final Optimized Flow 🏗️

Client
  ↓
Load Balancer
  ↓
Node.js (Clustered)
  ↓
In-Memory Cache
  ↓
Redis
  ↓
Optimized Indexed Queries
  ↓
Database

Thanks :).....

🤖 AI DevOps Debugger — Turning Production Logs into Actionable Insights with Copilot CLI

Darshan Raval — Fri, 23 Jan 2026 20:17:19 +0000

This is a submission for the GitHub Copilot CLI Challenge

What I Built

As a backend engineer, I’ve spent a lot of time debugging production issues — memory leaks, Redis disconnections, unhandled promise rejections, timeout errors, and mysterious crashes that only appear in production.

Logs usually tell us what happened, but not why.

So I built AI DevOps Debugger, a terminal-based CLI tool that transforms raw production logs into structured, actionable insights using GitHub Copilot CLI.

🔍 What It Does

📂 Analyzes Node.js application logs

🧠 Detects common production failure patterns

📊 Categorizes issues (Memory, Network, Async, Database, CPU blocking)

🧮 Calculates a Production Stability Score

🤖 Uses Copilot CLI to generate root cause explanations and fix suggestions

Instead of manually scanning thousands of log lines, you can now run:

ai-debug analyze logs.txt --env=prod

And get structured output like:

⚠️ Detected Issues:

Possible Memory Leak
- Heap usage growth detected
- Redis connection not properly closed
Unhandled Promise Rejection
- payment.service.js:84
Event Loop Blocking Risk
- Synchronous crypto operation detected

Production Stability Score: 72%

This project combines log analysis + AI-powered reasoning directly in the terminal — where DevOps workflows actually happen.

Demo

CLI Output

Interactive AI Suggestions

My Experience with GitHub Copilot CLI

Copilot CLI helped me quickly generate root cause explanations and actionable fixes for detected issues.
While Windows requires interactive mode, using WSL/Linux allowed fully automated AI-assisted debugging.

GitHub Repo

🚀 The Rise of Vibe Coding — Is AI Changing What Coding Even Means? 🤖✨

Darshan Raval — Fri, 23 Jan 2026 15:16:57 +0000

There was a time when programming meant:

1 Writing every line manually 👨‍💻
2 Debugging for hours 🐛
3 Reading documentation like scripture 📖
4 Arguing with Stack Overflow at 2-3 AM 🌙

It's Totally changed now, In 2026, something strange is happening…

Now Days, Whatever we need, we just entering the our English prompt and tadaa... AI writes code for you...

Welcome to the era of Vibe Coding 🎧⚡

Now, Let's Understand First This Term -> "Vibe Coding"

🎧 What Is Vibe Coding?

Vibe coding is when you ->

Explain what you want in natural language 🗣️
Let AI generate the implementation 🤖
Iterate by refining prompts instead of writing logic ✍️

Instead of thinking -> “How do I implement this algorithm?”

You think -> “What outcome do I want?”

It’s less about syntax.
More about intent.. 🎯

Letzz See one more thing -> the way of Engineer to Orchestrator....

🧠 From Engineer to Orchestrator?

What we did before is ->

Me → Code → Compiler → Output

What this Vibe coding is doing ->

You → AI → Code → You Review → Output

Now Days, we all developer's role almost changed -> before we code writer and now days code reviewer, System thinker, do Prompt design,

this line hits more - "The keyboard is still there… but the cognitive load has moved."

Now, Let's understand

⚡ Why Developers Love It?

🚀 Speed

-> Prototype in minutes, not days.
🧪 Boilerplate Elimination

-> CRUD APIs, validation, schemas — gone in seconds.
📚 Knowledge Compression

-> AI remembers docs so you don’t have to.
💡 Exploration

-> You can test 5 architectural ideas in an hour.

For startups and solo devs?
This feels like superpowers. 🦸‍♂️

Now, Let's understand the what are the dark side for it also,

⚠️ But Here’s the Dark Side…

🧨 1. Shallow Understanding

If you don’t understand what AI generated,
you can’t debug it when production burns 🔥

🧱 2. Hidden Technical Debt

AI optimizes for “working code” — not always “good architecture”.

🔒 3. Security Risks

Generated code may:

Expose secrets
Use unsafe libraries
Miss edge cases

🧩 4. Illusion of Productivity

You ship fast…
until scaling exposes weak foundations.

🏗️ What Happens to Craftsmanship?

Is coding becoming:

🎨 A craft?
🧠 A thinking discipline?
🤖 Or prompt engineering?

There’s a big difference between:

“Generate a REST API”

and

“Design a scalable, observable, resilient system.”

AI can generate functions.
It cannot yet own accountability.

That’s still human territory. 👀

🔥 The Real Shift: From Writing Code → Designing Systems

The best developers in the vibe era will:

Understand system architecture 🏛️
Review AI output critically 🔎
Write strong tests 🧪
Think about scalability 📈
Enforce standards 📏

In other words…

AI doesn’t replace engineers.
It exposes weak ones.

🛠️ How to Use Vibe Coding Wisely

Here’s a healthy framework:

✅ Use AI for boilerplate
✅ Use AI for brainstorming
✅ Use AI for refactoring suggestions
❌ Don’t blindly ship generated logic
❌ Don’t skip learning fundamentals

Think of AI as:

A junior developer who types very fast
but still needs supervision 👶⚡

📈 So… Is Coding Dead?

No.

But it is evolving.

We’re moving from:

Syntax mastery 📝 to Intent clarity 🎯
Architectural thinking 🧠
Critical evaluation 🔍

The developers who survive this shift
won’t be the fastest typists.

They’ll be the best thinkers.

Moral is,

Vibe coding isn’t the end of programming.

It’s the beginning of a new relationship between humans and machines.

The question isn’t:

“Will AI replace developers?”

The real question is:

“Will developers who ignore AI replace themselves?” 😏

See Ya Soon in Next Blog :)

Letzz Understand Temporal Dead Zone in JS ( TDZ ) ;)

Darshan Raval — Thu, 27 Jun 2024 17:43:16 +0000

Let's Understand What is TDZ ;)

What is the Temporal Dead Zone (TDZ)?

The Temporal Dead Zone refers to a period of time during the execution of your code where variables declared with let and const cannot be accessed before they are actually declared. This period starts from the beginning of the enclosing scope (e.g., a function or a block) and ends when the variable is declared.

Let's understand in easier way.

we have one code below,
Now, What happened - Javascript Code will execute line by line so it runs line number 1 and at line no 1 variable "a" is not declared so it will throw the error of "ReferenceError".

So Now Line No 1 and 2 is called "Temporal Dead Zone"

Now, let's use the same code with "var" variable. so, it'll not throw any error.

Why it's not throwing an error??

variables declared with var are hoisted to the top of their scope and initialized with undefined. This can lead to subtle bugs, which is why let and const were introduced with the TDZ to avoid such issues.

Now, Let's See How to Avoid it,

How to Avoid Issues with the TDZ

Declare Variables at the Top: To prevent running into the TDZ, declare your variables at the top of their scope.

Use const When Possible: If you don't plan to reassign a variable, use const to make your intentions clear and avoid accidental reassignments.

Conclusion

The Temporal Dead Zone is a concept that ensures variables declared with let and const are not accessed before they are defined. It helps in catching errors early and makes your code more reliable. By understanding and leveraging the TDZ, you can write cleaner and more predictable JavaScript code.

Thanks...

Computer Science Challenge: Recursion

Darshan Raval — Sat, 22 Jun 2024 17:24:40 +0000

This is a submission for DEV Computer Science Challenge v24.06.12: One Byte Explainer.

Explainer

Recursion: Recursion is a programming method that involves a function calling itself to address versions of an issue until it reaches a base scenario. This technique plays a role, in activities such as navigating trees and organizing data making the code more straightforward and less complicated, by dividing challenges into easier-to-handle components.

Additional Context

Recursion, in programming, involves a technique where a function calls itself to address instances of a problem. This method continues until it reaches a base case, which is a condition where the problem becomes simple enough to be solved stopping further recursive calls. The use of recursion is crucial in tasks such as navigating trees, where each node's subtrees are processed sequentially, and in sorting algorithms like quicksort and mergesort which divide arrays into segments for sorting. Through recursion complex problems are broken down into parts resulting in code that is often simpler and easier to understand. It is important to use recursion to prevent issues like loops and stack overflow errors, which can arise when the base case is not reached or the recursion depth becomes too high. Having a grasp of recursion aids, in developing elegant solutions for various computational challenges.

Letz Understand NPM Versioning: A Beginner's Guide

Darshan Raval — Sat, 22 Jun 2024 10:00:00 +0000

Introduction

In This Blog, We will understand more about the versioning of npm packages or any application.

[ Hello Buddies ]

Let's get started...

Now, Let's take an example of one npm package called "express".

We have an npm called "express" and its version is "^4.19.2".
Now, let's break down that version with the use of dot(.) and understand each part individually.

"^4.19.2"

First Part = 4
Second Part = 19
Third Part = 2

The first part we can call a major part of the version.

1 - First Part > [ MAJOR ] = [ 4 ]

If in the future, "4" will become "5" it means that a major update will be there which might break the backward compatibility.

2 - Second Part > [ MINOR ] = [ 19 ]

It means that, if the current version is "19" and it will be 20 or more then it will have some minor fixes and it's recommended to update to the new version.

3 - Third Part > [ PATCH ] = [ 2 ]

It means that, if the current version is "2" and it will be 3 or more then it means that some small bug fixed will be there which will not affect any functionality and it's optional also so if we need to update then update it or it'll not affect anything.

Now, Let's understand the what is the meaning of "^" symbol in the version.

The caret (^) symbol means that it will accept only minor and patch updates. If there is a change in the MAJOR version, it will not accept it.

Thanks!!

Install Particular Version of Package - NPM

Darshan Raval — Tue, 10 Mar 2020 16:59:33 +0000

We all know normally Install npm package like this.
$ npm install express

express@4.17.1 added 50 packages from 37 contributors and audited 126 packages in 3.262s found 0 vulnerabilities This method install a newer version or latest version of that package. But if we want to install particular version of package then follow it. Synax: npm install [package]@[version]

$ npm install express@4.16.1

express@4.16.1 added 48 packages from 36 contributors and audited 121 packages in 2.986s found 0 vulnerabilities