Google’s Carbon Copy: Is Google’s Carbon Programming language the Right Successor to C++?

Carbon Programming language

AI Dashboard is available on the Web, Apple, Google, and Microsoft, PRO version

Is Google’s Carbon Programming language the Right Successor to C++?

For years, C++ has been the go-to language for high-performance systems programming. But with the rise of multicore processors and GPUs, the need for a language that can take advantage of parallelism has never been greater. Enter Carbon, Google’s answer to the problem. But is it the right successor to C++?

Google has been in the news a lot lately for their new programming language, Carbon. It’s being billed as the successor to C++, but is it really? Let’s take a closer look.

Google's Carbon Copy: Is Google's Carbon Programming language the Right Successor to C++?
Google’s Carbon Copy: Is Google’s Carbon Programming language the Right Successor to C++?

On the surface, Carbon and C++ have a lot in common. They’re both statically typed, object-oriented languages with a focus on performance. They both have a learning curve, but once you know them, you can write code that is both readable and maintainable. However, there are some key differences that make Carbon a more attractive option for modern programmers.

For one, Carbon is garbage collected. This means that you don’t have to worry about manually managing memory, which can be a pain in C++. Carbon also has better support for concurrency than C++. With the rise of multicore processors, this is an important consideration. Finally, Carbon has a more modern standard library than C++. This includes features like string interpolation and pattern matching that make common tasks easier to accomplish.

According to Terry Lambert, Carbon Programming language is probably not the successor of C++. His reason are:

Single inheritance is a deal-breaker for me, even though the eC++ utilized by IOKit in macOS and iOS has the same restrictions.

Although it specifies stronger type enforcement, which would — in theory — also eliminate RTTI and the reflection, which eC++ has historically eliminated as well, it’s doing it via expression-defined typing, rather than explicitly eliminating it. I expect that it would also prevent use of dynamic_cast, although that’s not explicitly called out.

Let’s see if Linus approves of someone compiling the Linux kernel with Carbon, and then starting to add Carbon syntax code, into that port of Linux.”

On the surface, Carbon seems like a great choice to replace C++. It is designed to be more reliable and easier to use than C++. In addition, it is faster and can be used for a variety of applications. However, there are some drawbacks to using Carbon. First, it is not compatible with all operating systems. Second, it does not have all of the features of C++. Third, it is not as widely used as C++. Finally, it is still in development and has not been released yet.

These drawbacks may seem like deal breakers, but they don’t necessarily mean that Carbon is not the right successor to C++. First, while Carbon is not compatible with all operating systems, it is compatible with the most popular ones. Second, while it does not have all of the features of C++, it has the most important ones. Third, while it is not as widely used as C++, it is gaining popularity rapidly. Finally, while it is still in development, it is expected to be released soon.

What Is Carbon?
Carbon is a statically typed systems programming language developed by Google. It is based on C++ and shares a similar syntax. However, Carbon introduces several new features that make it better suited for parallelism. For example, Carbon provides first-class support for threads and synchronization primitives. It also offers a number of built-in data structures that are designed for concurrent access. Finally, Carbon comes with a toolchain that makes it easy to build and debug parallel programs.

Why Was Carbon Created?
Google’s primary motivation for developing Carbon was to improve the performance of its search engine. To do this, they needed a language that could take advantage of multicore processors and GPUs. C++ was not well suited for this purpose because it lacked support for threading and synchronization. As a result, Google decided to create their own language that would be purpose-built for parallelism.

Is Carbon The Right Successor To C++?
In many ways, yes. Carbon addresses many of the shortcomings of C++ when it comes to parallelism. However, there are some drawbacks. First, Carbon is still in its infancy and lacks many of the features and libraries that have made C++ so popular over the years. Second, because it is designed specifically for parallelism, it may be less suitable for other purposes such as embedded systems programming or network programming. Overall, though, Carbon looks like a promising successor to C++ and is worth keeping an eye on in the future.

Conclusion:
So, is Google’s new Carbon programming language the right successor to C++? We think that Google’s Carbon programming language has the potential to be a great successor to C++.

With its garbage collection, better support for concurrency, and modern standard library, Carbon has everything that today’s programmer needs.

It is designed to be more reliable and easier to use than its predecessor. In addition, it is faster and can be used for a variety of applications. However, there are some drawbacks to using Carbon that should be considered before making the switch from C++.

So if you’re looking for a new language to learn, we recommend giving Carbon a try.

Programming paradigms 2022-2023

Programming paradigms are a way to classify programming languages based on their features. Languages can be classified into multiple paradigms.

Some paradigms are concerned mainly with implications for the execution model of the language, such as allowing side effects, or whether the sequence of operations is defined by the execution model. Other paradigms are concerned mainly with the way that code is organized, such as grouping a code into units along with the state that is modified by the code. Yet others are concerned mainly with the style of syntax and grammar.

Common programming paradigms include:

  • imperative in which the programmer instructs the machine how to change its state,
    • procedural which groups instructions into procedures,
    • object-oriented which groups instructions with the part of the state they operate on,
  • declarative in which the programmer merely declares properties of the desired result, but not how to compute it
    • functional in which the desired result is declared as the value of a series of function applications,
    • logic in which the desired result is declared as the answer to a question about a system of facts and rules,
    • mathematical in which the desired result is declared as the solution of an optimization problem
    • reactive in which the desired result is declared with data streams and the propagation of change

Six programming paradigms that will change how you think about coding

Get 20% off Google Google Workspace (Google Meet) Standard Plan with  the following codes: 96DRHDRA9J7GTN6
Get 20% off Google Workspace (Google Meet)  Business Plan (AMERICAS) with  the following codes:  C37HCAQRVR7JTFK Get 20% off Google Workspace (Google Meet) Business Plan (AMERICAS): M9HNXHX3WC9H7YE (Email us for more codes)

Active Anti-Aging Eye Gel, Reduces Dark Circles, Puffy Eyes, Crow's Feet and Fine Lines & Wrinkles, Packed with Hyaluronic Acid & Age Defying Botanicals

 

Practice Carbon Programming Language at Hackerrank or LeetCode or FreeCodeCamp

Leetcode and HackerRank coding tests don’t work in developer interviews.

Here’s the proof:

Research has shown that work sample tests are VERY effective at determining if someone will we a good fit for a job. But here’s the problem: Work sample tests require applicants to perform tasks or work activities that mirror the tasks employees perform on the job.


AI Unraveled: Demystifying Frequently Asked Questions on Artificial Intelligence (OpenAI, ChatGPT, Google Bard, Generative AI, Discriminative AI, xAI, LLMs, GPUs, Machine Learning, NLP, Promp Engineering)

When was the last time you had to “reverse an integer” or “find the longest substring without repeating characters”. These types of tests don’t mirror the tasks that software developers perform on the job.

It’s like testing an architect by having them build a house out of playing cards. Leetcode problems are just brain teasers.

If you want to administer a work sample test, have them do a code review, build a tiny feature in your product, or read and explain some part of your product code. (Every developer knows 90% of your time is spent reading code.)

If you are looking for an all-in-one solution to help you prepare for the AWS Cloud Practitioner Certification Exam, look no further than this AWS Cloud Practitioner CCP CLF-C02 book

Developers are tired of Leetcode interviews. It’s time to stop wasting everyone’s time.

Source: https://www.opm.gov/policy-data-oversight/assessment-and-selection/other-assessment-methods/work-samples-and-simulations/

Malbolge 2022 2023

Brooks Otterlake on Twitter: "In case you're curious, this is what a Hello  World program looks like in Malbolge. This is the code you would write to  display the words "Hello World"

RegEx is just Malbolge for Strings:

r/ProgrammerHumor - RegEx is just Malbolge for strings

What is the hardest programming language? For me, I say C++, C, and Malbolge. Out of all of these, Malbolge is the hardest

Replit Mobile App:  Code on Android and iOS.

Z-Library. The world’s largest ebook library

Top 50 Programming Languages Ranked by the Number of Influenced Languages

Top 50 Programming Languages Ranked by the Number of Influenced Languages
Top 50 Programming Languages Ranked by the Number of Influenced Languages

Programming Breaking News and Quiz

What are the Greenest or Least Environmentally Friendly Programming Languages?

How do we know that the Top 3 Voice Recognition Devices like Siri Alexa and Ok Google are not spying on us?

What are popular hobbies among Software Engineers?

Djamgatech: Build the skills that’ll drive your career into six figures: Get Djamgatech.

How do you make a Python loop faster?

How do you make a Python loop faster?

AI Dashboard is available on the Web, Apple, Google, and Microsoft, PRO version

How do you make a Python loop faster?

Programmers are always looking for ways to make their code more efficient. One way to do this is to use a faster loop. Python is a high-level programming language that is widely used by developers and software engineers. It is known for its readability and ease of use. However, one downside of Python is that its loops can be slow. This can be a problem when you need to process large amounts of data. There are several ways to make Python loops faster. One way is to use a faster looping construct, such as C. Another way is to use an optimized library, such as NumPy. Finally, you can vectorize your code, which means converting it into a format that can be run on a GPU or other parallel computing platform. By using these techniques, you can significantly speed up your Python code.

According to Vladislav Zorov, If not talking about NumPy or something, try to use list comprehension expressions where possible. Those are handled by the C code of the Python interpreter, instead of looping in Python. Basically same idea like the NumPy solution, you just don’t want code running in Python.

Example: (Python 3.0)

lst = [n for n in range(1000000)]
def loops():
    newlst = []
    for n in lst:
        newlst.append(n * 2)
    return newlst
def lstcomp():
    return [n * 2 for n in lst]
from timeit import timeit
print(timeit(loops, number=100))
#18.953254899999592 seconds
print(timeit(lstcomp, number=100))
#11.669047399991541 seconds
Or Do this in Python 2.0

How do you make a Python loop faster?
How do you make a Python loop faster?

Python list traversing tip:

Instead of this: for i in range(len(l)): x = l[i]

Use this for i, x in enumerate(l): …

TO keep track of indices and values inside a loop.

Twice faster, and the code looks better.

Another option is to write loops in C instead of Python. This can be done by using a Python extension module such as pyximport. By doing this, programmers can take advantage of the speed of C while still using the convenient syntax of Python.

Finally, developers can also improve the performance of their code by making use of caching. By caching values that are computed inside a loop, programmers can avoid having to recalculate them each time through the loop. By taking these steps, programmers can make their Python code more efficient and faster.

Very Important: Don’t worry about code efficiency until you find yourself needing to worry about code efficiency.

The place where you think about efficiency is within the logic of your implementations.

This is where “big O” discussions come in to play. If you aren’t familiar, here is a link on the topic

Get 20% off Google Google Workspace (Google Meet) Standard Plan with  the following codes: 96DRHDRA9J7GTN6
Get 20% off Google Workspace (Google Meet)  Business Plan (AMERICAS) with  the following codes:  C37HCAQRVR7JTFK Get 20% off Google Workspace (Google Meet) Business Plan (AMERICAS): M9HNXHX3WC9H7YE (Email us for more codes)

Active Anti-Aging Eye Gel, Reduces Dark Circles, Puffy Eyes, Crow's Feet and Fine Lines & Wrinkles, Packed with Hyaluronic Acid & Age Defying Botanicals

What are the top 10 Wonders of computing and software engineering?

How do you make a Python loop faster?
What are the top 10 most insane myths about computer programmers?

Programming, Coding and Algorithms Questions and Answers


AI Unraveled: Demystifying Frequently Asked Questions on Artificial Intelligence (OpenAI, ChatGPT, Google Bard, Generative AI, Discriminative AI, xAI, LLMs, GPUs, Machine Learning, NLP, Promp Engineering)

Do you want to learn python we found 5 online coding courses for beginners?

Python Coding Bestsellers on Amazon

https://amzn.to/3s3KXc3

https://coma2.ca

If you are looking for an all-in-one solution to help you prepare for the AWS Cloud Practitioner Certification Exam, look no further than this AWS Cloud Practitioner CCP CLF-C02 book

The Best Python Coding and Programming Bootcamps

We’ve also included a scholarship resource with more than 40 unique scholarships to provide additional financial support.

Python Coding Bootcamp Scholarships

Python Coding Breaking News

    Feed has no items.

What are the top 10 most insane myths about computer programmers?

What are the top 10 most insane myths about computer programmers?

AI Dashboard is available on the Web, Apple, Google, and Microsoft, PRO version

What are the top 10 most insane myths about computer programmers?

Programmers are often seen as a eccentric breed. There are many myths about computer programmers that circulate both within and outside of the tech industry. Some of these myths are harmless misconceptions, while others can be damaging to both individual programmers and the industry as a whole.

 Here are 10 of the most insane myths about computer programmers:

1. Programmers are all socially awkward nerds who live in their parents’ basements.
2. Programmers only care about computers and have no other interests.
3. Programmers are all genius-level intellects with photographic memories.
4. Programmers can code anything they set their minds to, no matter how complex or impossible it may seem.
5. Programmers only work on solitary projects and never collaborate with others.
6. Programmers write code that is completely error-free on the first try.
7. All programmers use the same coding languages and tools.
8. Programmers can easily find jobs anywhere in the world thanks to the worldwide demand for their skills.
9. Programmers always work in dark, cluttered rooms with dozens of monitors surrounding them.
10. Programmers can’t have successful personal lives because they spend all their time working on code.”

Another Top 10 Myths about computer programmers  in details are:

Myth #1: Programmers are lazy.

This couldn’t be further from the truth! Programmers are some of the hardest working people in the tech industry. They are constantly working to improve their skills and keep up with the latest advancements in technology.

Myth #2: Programmers don’t need social skills.

While it is true that programmers don’t need to be extroverts, they do need to have strong social skills. Programmers need to be able to communicate effectively with other members of their team, as well as with clients and customers.

Myth #3: All programmers are nerds.

There is a common misconception that all programmers are nerdy introverts who live in their parents’ basements. This could not be further from the truth! While there are certainly some nerds in the programming community, there are also a lot of outgoing, social people. In fact, programming is a great field for people who want to use their social skills to build relationships and solve problems.

Get 20% off Google Google Workspace (Google Meet) Standard Plan with  the following codes: 96DRHDRA9J7GTN6
Get 20% off Google Workspace (Google Meet)  Business Plan (AMERICAS) with  the following codes:  C37HCAQRVR7JTFK Get 20% off Google Workspace (Google Meet) Business Plan (AMERICAS): M9HNXHX3WC9H7YE (Email us for more codes)

Active Anti-Aging Eye Gel, Reduces Dark Circles, Puffy Eyes, Crow's Feet and Fine Lines & Wrinkles, Packed with Hyaluronic Acid & Age Defying Botanicals

Myth #4: Programmers are just code monkeys.

Programmers are often seen as nothing more than people who write code all day long. However, this could not be further from the truth! Programmers are critical thinkers who use their analytical skills to solve complex problems. They are also creative people who use their coding skills to build new and innovative software applications.

Myth #5: Anyone can learn to code.

This myth is particularly damaging, as it dissuades people from pursuing careers in programming. The reality is that coding is a difficult skill to learn, and it takes years of practice to become a proficient programmer. While it is true that anyone can learn to code, it is important to understand that it is not an easy task.

Myth #6: Programmers don’t need math skills.

This myth is simply not true! Programmers use math every day, whether they’re calculating algorithms or working with big data sets. In fact, many programmers have degrees in mathematics or computer science because they know that math skills are essential for success in the field.


AI Unraveled: Demystifying Frequently Asked Questions on Artificial Intelligence (OpenAI, ChatGPT, Google Bard, Generative AI, Discriminative AI, xAI, LLMs, GPUs, Machine Learning, NLP, Promp Engineering)

Myth #7: Programming is a dead-end job.

This myth likely comes from the fact that many people view programming as nothing more than code monkey work. However, this could not be further from the truth! Programmers have a wide range of career options available to them, including software engineering, web development, and data science.

Myth #8: Programmers only work on single projects.

Again, this myth likely comes from the outside world’s view of programming as nothing more than coding work. In reality, programmers often work on multiple projects at once. They may be responsible for coding new features for an existing application, developing a new application from scratch, or working on multiple projects simultaneously as part of a team.

Myth #9: Programming is easy once you know how to do it .

This myth is particularly insidious, as it leads people to believe that they can simply learn how to code overnight and become successful programmers immediately thereafter . The reality is that learning how to code takes time , practice , and patience . Even experienced programmers still make mistakes sometimes !

If you are looking for an all-in-one solution to help you prepare for the AWS Cloud Practitioner Certification Exam, look no further than this AWS Cloud Practitioner CCP CLF-C02 book

Myth #10: Programmers don’t need formal education

This myth likely stems from the fact that many successful programmers are self-taught . However , this does not mean that formal education is unnecessary . Many employers prefer candidates with degrees in computer science or related fields , and formal education can give you an important foundation in programming concepts and theory .

Myth #11: That they put in immense amounts of time at the job

I worked for 38 years programming computers. During that time, there were two times that I needed to put in significant extra times at the job. The first two years, I spent more time to get acclimated to the job (which I then left at age of 22) with a Blood Pressure 153/105. Not a good situation. The second time was at the end of my career where I was the only person who could get this project completed (due to special knowledge of the area) in the timeframe required. I spent about five months putting a lot of time in.

Myth #12: They need to know advanced math

Some programmers may need to know advanced math, but in the areas where I (and others) were involved with, being able to estimate resulting values and visualization skills were more important. One needs to know that a displayed number is not correct. Visualization skills is the ability to see the “big picture” and envision the associated tasks necessary to make the big picture correctly. You need to be able to decompose each of the associated tasks to limit complexity and make it easier to debug. In general the less complex code is, the fewer errors/bugs and the easier it is to identify and fix them.

Myth #13: Programmers remember thousands lines of code.

No, we don’t. We know approximate part of the program where the problem could be. And could localize it using a debugger or logs – that’s all.

Myth #14:  Everyone could be a programmer.

No. One must have not only desire to be a programmer but also has some addiction to it. Programming is not closed or elite art. It’s just another human occupation. And as not everyone could be a doctor or a businessman – as not everyone could be a programmer.

Myth #15: Simple business request could be easily implemented

No. The ease of implementation is defined by model used inside the software. And the thing which looks simple to business owners could be almost impossible to implement without significantly changing the model – which could take weeks – and vice versa: seemingly hard business problem could sometimes be implemented in 15 minutes.

Myth #16: Please fix <put any electronic device here>or setup my printer – you are a programmer! 

Yes, I’m a programmer – neither an electronic engineer nor a system administrator. I write programs, not fix devices, setup software or hardware!

As you can see , there are many myths about computer programmers circulating within and outside of the tech industry . These myths can be damaging to both individual programmers and the industry as a whole . It’s important to dispel these myths so that we can continue attracting top talent into the field of programming !

What are the top 10 most insane myths about computer programmers?
What are the top 10 most insane myths about computer programmers?

Google’s Carbon Copy: Is Google’s Carbon Programming language the Right Successor to C++?

What are the Greenest or Least Environmentally Friendly Programming Languages?

Djamgatech: Build the skills that’ll drive your career into six figures: Get Djamgatech.

What are popular hobbies among Software Engineers?

Pass the 2023 AWS Cloud Practitioner CCP CLF-C02 Certification with flying colors Ace the 2023 AWS Solutions Architect Associate SAA-C03 Exam with Confidence Pass the 2023 AWS Certified Machine Learning Specialty MLS-C01 Exam with Flying Colors

List of Freely available programming books - What is the single most influential book every Programmers should read



#BlackOwned #BlackEntrepreneurs #BlackBuniness #AWSCertified #AWSCloudPractitioner #AWSCertification #AWSCLFC02 #CloudComputing #AWSStudyGuide #AWSTraining #AWSCareer #AWSExamPrep #AWSCommunity #AWSEducation #AWSBasics #AWSCertified #AWSMachineLearning #AWSCertification #AWSSpecialty #MachineLearning #AWSStudyGuide #CloudComputing #DataScience #AWSCertified #AWSSolutionsArchitect #AWSArchitectAssociate #AWSCertification #AWSStudyGuide #CloudComputing #AWSArchitecture #AWSTraining #AWSCareer #AWSExamPrep #AWSCommunity #AWSEducation #AzureFundamentals #AZ900 #MicrosoftAzure #ITCertification #CertificationPrep #StudyMaterials #TechLearning #MicrosoftCertified #AzureCertification #TechBooks

Top 1000 Canada Quiz and trivia: CANADA CITIZENSHIP TEST- HISTORY - GEOGRAPHY - GOVERNMENT- CULTURE - PEOPLE - LANGUAGES - TRAVEL - WILDLIFE - HOCKEY - TOURISM - SCENERIES - ARTS - DATA VISUALIZATION
zCanadian Quiz and Trivia, Canadian History, Citizenship Test, Geography, Wildlife, Secenries, Banff, Tourism

Top 1000 Africa Quiz and trivia: HISTORY - GEOGRAPHY - WILDLIFE - CULTURE - PEOPLE - LANGUAGES - TRAVEL - TOURISM - SCENERIES - ARTS - DATA VISUALIZATION
Africa Quiz, Africa Trivia, Quiz, African History, Geography, Wildlife, Culture

Exploring the Pros and Cons of Visiting All Provinces and Territories in Canada.
Exploring the Pros and Cons of Visiting All Provinces and Territories in Canada

Exploring the Advantages and Disadvantages of Visiting All 50 States in the USA
Exploring the Advantages and Disadvantages of Visiting All 50 States in the USA


Health Health, a science-based community to discuss health news and the coronavirus (COVID-19) pandemic

Today I Learned (TIL) You learn something new every day; what did you learn today? Submit interesting and specific facts about something that you just found out here.

Reddit Science This community is a place to share and discuss new scientific research. Read about the latest advances in astronomy, biology, medicine, physics, social science, and more. Find and submit new publications and popular science coverage of current research.

Reddit Sports Sports News and Highlights from the NFL, NBA, NHL, MLB, MLS, and leagues around the world.

Turn your dream into reality with Google Workspace: It’s free for the first 14 days.
Get 20% off Google Google Workspace (Google Meet) Standard Plan with  the following codes:
Get 20% off Google Google Workspace (Google Meet) Standard Plan with  the following codes: 96DRHDRA9J7GTN6 96DRHDRA9J7GTN6
63F733CLLY7R7MM
63F7D7CPD9XXUVT
63FLKQHWV3AEEE6
63JGLWWK36CP7WM
63KKR9EULQRR7VE
63KNY4N7VHCUA9R
63LDXXFYU6VXDG9
63MGNRCKXURAYWC
63NGNDVVXJP4N99
63P4G3ELRPADKQU
With Google Workspace, Get custom email @yourcompany, Work from anywhere; Easily scale up or down
Google gives you the tools you need to run your business like a pro. Set up custom email, share files securely online, video chat from any device, and more.
Google Workspace provides a platform, a common ground, for all our internal teams and operations to collaboratively support our primary business goal, which is to deliver quality information to our readers quickly.
Get 20% off Google Workspace (Google Meet) Business Plan (AMERICAS): M9HNXHX3WC9H7YE
C37HCAQRVR7JTFK
C3AE76E7WATCTL9
C3C3RGUF9VW6LXE
C3D9LD4L736CALC
C3EQXV674DQ6PXP
C3G9M3JEHXM3XC7
C3GGR3H4TRHUD7L
C3LVUVC3LHKUEQK
C3PVGM4CHHPMWLE
C3QHQ763LWGTW4C
Even if you’re small, you want people to see you as a professional business. If you’re still growing, you need the building blocks to get you where you want to be. I’ve learned so much about business through Google Workspace—I can’t imagine working without it.
(Email us for more codes)

error: Content is protected !!