Everyone is buzzing about ChatGPT, the most recent version of OpenAI’s machine learning language model. One major concern that has risen as a result of this development is this – Can ChatGPT write code?
Is it possible for ChatGPT to use programming languages like Python and Java more effectively than a human programmer? More importantly, will it replace software developers?
ChatGPT is a ML model built mostly on Python. The deep learning framework PyTorch, which is likewise written in Python, is used to implement the model.
What exactly can you accomplish as a programmer with ChatGPT? Beyond the fanfare, how can you use the AI chatbot in your day-to-day programming workflows?
We went ahead and did a couple of programming attempts on ChatGPT to see how efficient the AI tool is when it comes to programming languages.
Algorithm generation
Many programmers outsource the entire programming process to ChatGPT, but this can result in critical errors. This isn’t to say that the AI tool can’t write a good code. However, it is best to use it as a supplementary tool while human programmers maintain control of the majority of the development process.
We asked the AI tool to lay out an efficient basic algorithm and let the programmer do the rest of the more robust job.
Placeholder Data
Programmers frequently require placeholder data to work with. ChatGPT can produce several types of dummy data to meet your needs, whether it’s database data to test your APIs or long-form text to populate webpages.
Filler content can be generated in SQL, JSON, CSV, and a variety of other forms via ChatGPT. It can even generate native data structures such as arrays and lists in any popular programming language.
This isn’t something that can be easily generated with other free dummy data-generating tools you can find online.
Data management
Programmers frequently work with large amounts of raw text that must be turned into an appropriate data type, such as a CSV or a JavaScript object, such as an array. Alternatively, data structures in one language must be converted or formatted into data structures in another.
We provided instructions in English to ChatGPT to convert a large amount of contact-related data and asked it to format it in the form of a table.
Code Language Conversion
A good number of times, programmers come across a solution to a complex programming issue in one language but need it only in the language they are writing the programme code in.
I wrote a simple Python code for a marketing campaign and tried converting it into C++ and guess what, the result was accurate.
Similarly, when you have a large set of code in a programming code to convert, ChatGPT can do a decent job of converting it into your preferred language.
The AI chatbot has been trained in a variety of programming languages and can port code between them with excellent accuracy. We can also port deprecated or legacy code in the same language to newer, more stable code. All we need to do is provide the tool with accurate and unambiguous prompts.
Code optimization
Whether it is a large resource-intensive application or a smaller project, there is always a possibility that can generate better results if it is optimized.
We wrote a summation code in JavaScript; the code works but it could use a few optimizations too. We asked ChatGPT to optimize the code for better results –
A programmer can also ask the AI tool to optimize specific parts of the code to meet their specific requirements. They can ask the AI chatbot to either recommend ways to optimize a block of code or to generate an optimized version of the code.
Unit tests for Code
Writing unit tests for your code is one of the best ways to ensure it is bug-free, can handle a variety of exceptions, and can handle edge cases. Of course, writing examinations can be a time-consuming and even a perplexing endeavour at times.
We ran a unit test for the same code written in JavaScript and it didn’t disappoint. It can also execute unit tests on more complex codes too, but programmers shouldn’t delegate the whole task to ChatGPT.
Code documentation
For all the programmers, code documentation remains an essential part of software development. ChatGPT can generate extensive documentation for code written in a variety of computer languages.
We had a C++ code for generating the largest number possible if we feed it with several numbers.
We also asked ChatGPT to create its documentation in HTML format and it provided an accurate result.
Bug Detection
It is not uncommon for programmers to accidentally write faulty codes and all of us are aware that finding these bugs is a really tiresome task. From misplaced brackets to incorrect symbols, ChatGPT can spot errors within seconds that could take you minutes to identify.
We played a little trick and put the “larger than” symbol instead of “smaller than” against the “i” variable. Let’s see if ChatGPT can spot the error.
Since this was a simple bug, ChatGPT identified the error and put out the correct code within 10 seconds.
Logic problems are often more difficult to detect. If so, simply paste the problematic code and explain to ChatGPT what you’re attempting to accomplish with it and the current results.
For the best results, provide as many details about the error as possible. Relevant details may include the language, frameworks, and libraries used by your code, as well as information on the server on which it is running.
Will ChatGPT take away jobs?
Programming is a complex task with many moving components that must be perfect. ChatGPT may be a valuable ally, helping you to streamline the process of creating these delicate parts by instantly accessing large amounts of knowledge and expertise. You should, however, avoid employing the AI chatbot to write all of the computer code.
We would like to emphasize that ChatGPT won’t eliminate the need for programmers. Professional programmers with the correct foundations will undoubtedly find it useful in speeding up the end-to-end development process.
The larger concern is whether it will assist non-programmers in coding and hence, reduce their dependency on programmers. For now, the answer is in the negative because its code needs constant supervision.
ChatGPT frequently generates inaccurate and, more often than not, wasteful code for basic issues. This still necessitates the user having a basic understanding of programming to determine if the code is sound.
AI code generators, such as ChatGPT, will however certainly raise the entry barrier into the field because AI can generate most of the repetitive boilerplate code more readily.
But when it comes to real-world solutions, specification documents with hundreds of pages cannot be fed into ChatGPT that instantaneously generates an accurate code with millions of lines.
Earlier, languages such as Python made the job of programmers quicker and easier but they did not eliminate the need for programmers. It’s going to be the same story with ChatGPT. It will undoubtedly speed up the task, but it cannot do everything on its own.
