Programming is an intricate puzzle, where lines of code are stacked upon each other, forming a tower that we hope won’t come crashing down. But inevitably, it does. Code never works perfectly on the first try, which is why debugging is such a crucial skill for programmers. Debugging is like being a detective, searching for clues and deciphering what they mean. It can be both frustrating and satisfying at the same time.
As a programmer, I do a lot of debugging. It’s not only because code rarely works flawlessly from the start, but also because it helps me understand how the code is running and make necessary adjustments. However, while debugging requires its own set of skills, it is ultimately just part of the programming process. Once you identify why a block of code isn’t functioning correctly, you have to figure out how to fix it.
Recently, I decided to put ChatGPT to the test in a real-world coding scenario. Instead of using it to generate test code, I wanted to see if it could be a useful tool for my regular programming work. Test scenarios often feel contrived and simplistic, whereas real-world coding involves tackling customer support tickets and addressing user experience issues. So, I set out to see how ChatGPT would perform in this context.
The first task I tackled was rewriting regular expression code. Regular expressions are used to find patterns in text, and while they are a powerful tool, they can also be tedious and error-prone. A bug report informed me that a part of my code was only allowing integers when it should have allowed for dollar amounts as well. Since I find writing regular expressions tiresome, I turned to ChatGPT for assistance. I provided the prompt, and ChatGPT quickly generated the code I needed. It saved me hours of frustration and hair-pulling.
Next, I attempted to reformat an array using ChatGPT. Unfortunately, this time the results were disappointing. Despite trying multiple prompts, the code generated by ChatGPT either crashed, produced errors, or didn’t achieve the desired outcome. After an hour of unsuccessful attempts, I resorted to my usual method of searching through GitHub and StackExchange for examples and writing my own code.
Undeterred by the previous setback, I decided to raise the challenge and see if ChatGPT could help me identify an error in my code. I was working on a new function that required two parameters, and the calling statement was also passing two parameters. However, I kept encountering an error message stating that “1 passed” at one point and “exactly 2 expected” at another. It was baffling. After struggling with it for 15 minutes, I turned to ChatGPT for assistance. I showed it the relevant lines of code, and within seconds, ChatGPT provided me with a solution. It suggested updating a specific parameter, and when I implemented the change, the code worked perfectly. ChatGPT’s ability to analyze code segments and provide insights was impressive.
In conclusion, my experience with ChatGPT in real-world coding scenarios was a mixed bag. It proved invaluable in rewriting regular expression code, saving me hours of tedious work. However, it fell short when it came to reformatting an array. Nonetheless, its ability to help identify errors in code was impressive and provided a quick resolution to a frustrating problem. While ChatGPT is not a perfect solution for all coding challenges, it certainly has the potential to be a valuable tool in a programmer’s arsenal.