Saturday, April 27, 2024

Old Code, New Tricks: A C++ Coder’s Journey from Vim to Vibes

 

Old Code, New Tricks: A C++ Coder’s Journey from Vim to Vibes

60++ coders view of the Gen z coder

Hey there, fellow keyboard warriors! It’s Srini here, your neighborhood C++ old-timer, ready to spin you a yarn about the coding clashes of generations. I've been in the trenches long enough to see punch cards go out of style, and yet here I am, trying to understand why my terminal doesn’t support emoji.

Let’s dive into the delightful chaos of coding styles, where the venerable Unix shell meets the snap-and-go ethos of Gen Z. Brace yourself for a lighthearted romp through code blocks and TikTok clocks!

Chapter 1: Greetings, System!

Back in my day, we greeted each other with a handshake firm enough to affirm your C++ credentials. In code? It was no different:

include <iostream>

int main() {

    std::cout << "Hello, World!" << std::endl;

    return 0;

}

But enter Gen Z, and suddenly my "Hello, World!" looks as ancient as the floppy disks gathering dust in my attic. Here’s how the new kids might do it:

include <iostream>

using namespace std;

auto main() -> int {

    cout << "Heyyy 🌍!" << endl;

}

Yes, emojis. In terminal output. Where will they show up next? Commit messages?

Chapter 2: Comments and Commitments

Now, let’s talk about commenting. My comments used to be a meticulous affair, much like crafting a fine watch. Here’s an example:

// Function: Calculate the factorial of a number

// Input: int - The number for which to calculate the factorial

// Output: long long - The factorial of the number

long long factorial(int n) {

    // Base case

    if (n == 0) return 1;

    // Recursive case

    return n * factorial(n - 1);

}

Fast forward to today, and Gen Z’s comments look like they were typed with one thumb while skateboarding:

// idk man, it just works 🤷‍♂️

auto fact(auto n) -> decltype(n) {

    return (n < 2) ? 1 : n * fact(n - 1);

}

I mean, who needs detailed comments when you have swagger and autocorrect?

Chapter 3: Compilation Showdown

Here’s where it gets interesting. Compiling code in my day was akin to a sacred ritual. The command line was our altar, and GCC our high priest. A typical compile command?

g++ -Wall -Werror -O2 -o program program.cpp

Today’s Gen Z coder slaps a Docker container together faster than I can say “linker error.” And their compile commands? It's all about shorthand:

g++ -o prog prog.cpp && ./prog

Simple, sleek, and oh, did I mention they run it inside an Alpine Linux container spun up on their Kubernetes cluster managed through a cloud IDE? Phew!

Chapter 4: Optimization Olympics

Optimization? My era was obsessed. We’d spend days squeezing every bit of performance from our code like it was a lemon on my free salad . Check out this snippet for calculating primes:

for (int i = 2; i < n; i++) {

    bool isPrime = true;

    for (int j = 2; j * j <= i; j++) {

        if (i % j == 0) {

            isPrime = false;

            break;

        }

    }

    if (isPrime) primes.push_back(i);

}

Cut to Gen Z, and here’s their version, leveraging every library and framework under the sun:

vector<int> getPrimes(int n) {

    vector<bool> is_prime(n+1, true);

    for (int i = 2; i * i <= n; i++) {

        if (is_prime[i]) {

            for (int j = i * i; j <= n; j += i)

                is_prime[j] = false;

        }

    }

    return vector<int>(is_prime.begin() + 2, is_prime.end());

}

They call it “modern C++.” I call it “Why reinvent the wheel when there’s Stack Overflow?”

Epilogue: Embracing the New, Respecting the Old

As much as I poke fun at these young coders, there’s something to be said for the sheer speed and adaptability of Gen Z programmers. They’ve got the tools, the tech, and the TikTok to do things in ways we never dreamed of.

So, whether you’re an old school coder like me or a fresh-faced dev with a penchant for memes, remember: the best code is the code that works. And sometimes, it even has emojis.

Keep coding, and keep laughing, folks! Until next time, this is Srini signing off. 👋🧑‍💻


BTW don't compile any of the code here. I have no clue if it even compiles, let alone work. 😀

Friday, April 19, 2024

Busted by the Professor: How I Learned AI codes just by visual inspection;)

 


Busted by the Professor: How I Learned AI codes just by visual inspection;)

Ah, the allure of the instant code genie. In the pressure-cooker world of big data courses, where wrangling Spark DataFrames feels like herding cats, AI-generated code can sound like a dream come true. But dear data wrangling students, we professors have a secret weapon: the eagle eye honed through years of battling spaghetti code and syntax errors.

Let's be honest, there's a certain satisfaction in crafting clean, efficient code yourself. But before you dive headfirst into the world of AI-generated scripts, let's brush up on how to spot code that wasn't exactly written with human sweat and tears.

Fun Fact - 92% of all code submissions in my current course were at first cut “pure” AI. When asked to explain the code, you know what happened. 

The Ten Signs of the AI Coder

Remember that group project where your partner mysteriously produced a perfectly sparkly DataFrame named 'sparklifyAndCleanseDataFrame'? Yeah, that wasn't them. Here's how to sniff out AI-generated code in the wild:

  1. Unnecessary Parameter Palooza: AI scripts love including every single parameter under the sun, even the ones the function already defaults to.

  2. Variable Names That Outshine Shakespeare: If you find variable names longer than your professor's lectures, like 'transformedAndEnrichedForMachineLearningPipelineDataframe,' the AI might be the culprit.

  3. Comments that Leave You Confused: Overly generic comments or strangely specific ones that don't match the code's complexity are red flags.

  4. Code Rube Goldberg Machines: AI code might solve simple problems in overly complex ways, like using ten lines to do what one line could achieve.

  5. Redundancy Redundant: Repetitive functions or data cleaning steps that echo each other scream "AI shortcut!"

  6. Library Labyrinth: Does the code import a whole symphony of libraries for a simple task? The AI might be trying to brute force its way through.

  7. Style Inconsistency Symphony: Mixing indentation styles like a musical mashup is a sign of AI's indecisiveness.

  8. Unnecessary Type Casting: AI might cast every variable to a specific data type, even if it's not strictly necessary.

  9. Overly Cautious Error Handling: Exception handling for every possible error under the sun might be a sign of overzealous AI.

  10. Missing Comments for Complex Logic: If there are complex functions without clear comments, it could be a sign the code was generated by AI that doesn't understand the nuances of human coding conventions.


Beyond Busting Bots: How AI Can Enhance Learning


Now, hold on a minute! While AI-generated code might not win any coding contests, it doesn't mean it's all bad. Consider AI as a helpful study buddy, not a replacement for your own coding skills.

There are fantastic AI tools out there that can suggest code completions or generate documentation, which can be a huge time-saver, especially for beginners. Think of it as having a built-in coding cheerleader in your corner.


The Human Touch: Why Professors Still Rule


But here's the real kicker: AI might be a whiz at mimicking code, but it can't replace human understanding. Professors are there to guide you through the why behind the what. They can explain complex big data concepts and help you develop critical thinking skills, which are essential for success in any data-driven field.


So, the next time you're tempted to let AI do the coding heavy lifting, remember: understanding the code itself is a valuable skill. Besides, wouldn't it be more rewarding to impress your professor with your own sparklingly clean code, crafted by your own two hands (and maybe with a little help from your friendly AI study buddy)?


Thursday, April 11, 2024

In the Stripes of Leadership: The Untamed Wisdom of Tigers

 In the Stripes of Leadership: The Untamed Wisdom of Tigers

Imagine this: you've spent years hoping to see a tiger in the wild, with countless safaris through several sanctuaries proving fruitless. Then, on a whim, you decide to try Ranthambore National Park. Not only do you see a tiger, but you witness a spectacle that leaves you breathless - five magnificent Royal Bengal Tigers, lounging by a waterhole, playful cubs frolicking nearby. This was my incredible experience at Ranthambore, and it served as a profound lesson in leadership.

Tigers, the apex predators of the jungle, embody calmness, power, and strategic thinking. Let's delve into these qualities and explore how they translate into the realm of corporate leadership:

Composure Under Pressure: A Leader's Calm Demeanor

In the wild, a tiger's movements are deliberate and measured. They stalk their prey with patience, conserving energy for the final burst. Similarly, a leader should project composure during challenging situations. Frantic energy can be contagious, unsettling the team. Instead, channel your inner tiger – assess the situation calmly, strategize thoughtfully, and make decisions with a clear head.

The Power of Presence: Commanding Respect Without Force

A tiger's presence inspires awe. Their majestic stature and piercing gaze command respect. As a leader, cultivate a similar power of presence. It's not about brute force or intimidation; it's about radiating confidence, conviction, and the quiet strength that inspires trust and followership.

Strategic Prowess: Leading with Foresight

Tigers are ambush predators, planning their attacks meticulously. They exploit the environment, using camouflage and surprise to their advantage. Leaders can emulate this strategic thinking. Analyze situations, anticipate challenges, and devise well-thought-out plans. Don't be afraid to leverage your team's strengths and expertise to achieve optimal outcomes.

Adaptability: Leading Through Change

The jungle is an ever-changing environment. Tigers adapt their hunting strategies based on prey availability and habitat conditions. Leaders must also be adaptable. Embrace change as a constant, be open to new ideas, and adjust your approach when necessary.

The Thrill of the Hunt: Embracing Challenges with Passion

For a tiger, the hunt is not just about survival; it's an instinctive drive. They approach it with focus and determination. Leaders should share this passion. Approach challenges with a similar drive to succeed, inspiring your team to work together with unwavering commitment towards a shared goal.

The Collective Power of the Pack: Collaboration Breeds Success

While tigers are solitary creatures, they exhibit a remarkable social intelligence. Mothers raise their cubs together, and males sometimes share territories. Leaders can learn from this concept of collaboration. Nurture a supportive team environment, delegate tasks effectively, and leverage the collective strengths of your team to achieve success.

Beyond the Tiger: The Symphony of the Jungle

The jungle is a complex ecosystem, where every creature plays a vital role. It's a reminder that leadership is not a solo performance. It's about creating a harmonious environment where everyone thrives. Foster open communication, celebrate individual contributions, and create a culture of mutual respect and support.

The Final Roar: Lessons Learned

My tiger sighting was a life-changing experience, offering profound leadership wisdom. By emulating the tiger's composure, power, and strategic brilliance, we can all become more effective leaders, fostering thriving teams and achieving remarkable success. So, the next time you're in the wild, take a moment to observe the majestic tiger. You might just discover your next leadership lesson.