GitHub CoPilot Is Ruining Code Quality | Prime Reacts
GitHub CoPilot, the AI-powered code completion tool released by GitHub, has been causing quite a stir in the programming community. While some developers hail it as a game-changer that can speed up development and improve productivity, others are raising concerns about its impact on code quality.
At Prime Reacts, we believe that GitHub CoPilot is ruining code quality. Here’s why:
1. Lack of Understanding
GitHub CoPilot can generate code snippets based on context and previous patterns. While this can be helpful in speeding up development, it also means that developers may not fully understand the code they are writing. This lack of understanding can lead to bugs, security vulnerabilities, and overall poor code quality.
2. Over-reliance on Tooling
With GitHub CoPilot, developers may become too dependent on the tool to write code for them. This can lead to a lack of critical thinking and problem-solving skills, as developers simply rely on the tool to do the work for them. This can result in a decline in code quality as developers may not fully understand the logic behind the code they are writing.
3. Code Duplication
GitHub CoPilot has access to a vast repository of code snippets, which it uses to generate code suggestions. However, this can lead to code duplication, where the same or similar code snippets are reused across projects. This can result in bloated codebases, increased maintenance costs, and difficulty in debugging and refactoring code.
4. Security Risks
By relying on an AI tool to generate code, developers may inadvertently introduce security vulnerabilities into their codebase. GitHub CoPilot may suggest insecure coding practices or introduce vulnerabilities that developers may not be aware of. This can pose a significant risk to the security of applications and data.
In conclusion, while GitHub CoPilot may offer some advantages in terms of productivity and speed of development, we believe that it ultimately has a negative impact on code quality. Developers should exercise caution when using the tool and ensure they have a solid understanding of the code they are writing. In the end, it is essential to prioritize code quality over speed and convenience.
9:24 You're welcome
Tried copilot through our company, and it just doesn't work. Wrong almost all the time and the only thing it seems to get right is repeating what I just wrote.
No way to make you 55% faster may be 10-20% but 55 no way. Most of time giving irrelevant suggestions.
Students should read K&R and the OpenGL Programming Guide and write terrain generators in vi for at least the first 6 months
Writing code is definitely not 1% of devs, would be wild if that was true
If ai will be the only coding and debugging code eventually ,the quality/readability/maintainability of the code wont matter, machines dont need those
Data for 2024 is insignificant, because we're barely at the beginning of the year.
🤖💬AI is future 👀… 😂
Tried using it for Unity, it's somehow worse with Quaternions than I am
Dude, fix your hair color. What is this, girls night out? 😀
Is the rant about the fact that it could have been a blog post instead really necessary ? Does the format of the document where the ideas are presented really mater that much?
about the 10% time on writing code; if you consider debug, compiling and reading docs, I'd guess it is a decent guess
refactoring is disappearing because all the senior devs who can refactor are stuck reading code reviews of CoPilot newbies
Honestly, I use it for “advanced rubber ducking” at work. Maybe it generates some worth while code or boilerplate but ultimately I fall back to reading vendor docs or peeking the class. Sometimes it’s good for quickly summarizing your code in a comment…sometimes!
So uploading Spagetti code to Githut is an act of AI resistance now?
It feels like something I finally have an advantage on. People seem to be trying to use it the wrong way. My code is still my code, just accelerated in being complete
The 55% increase in coding speed is most likely due to the delegation of the design/thinking about a funciton's internals rather than typing speed.
Prime spends more time writing code than reading because Netflix creates a new microservice for every feature
I am afraid about when absolutely technically non experienced managers use chatgpt tools to estimate how much time development will need or do some other estimations. And then blaming programmers that they not in time or whatever.
From someone with 4yrs of exp, Copilot is very good at repetitive tasks like wiriting something similar to what you've already written (i.e. DB access layer of a program), it's also good at writing base documentation to build upon.
For actual code it's: 5% amazing code, 10% serviceable, 20% a little bug in there that you won't notice until you've read it 10 times 50% not really what I want and 15% "go home you're drunk"