TL;DR: ChatGPT generates terrible buggy code faster than the average software developer.
For those of you who have been living under a rock in the last couple of weeks, here's Wikipedia's definition of ChatGPT:
ChatGPT, which stands for Chat Generative Pre-trained Transformer, is a chatbot developed by OpenAI. ChatGPT is built on top of OpenAI's GPT-3.5 family of large language models and is fine-tuned with both supervised and reinforcement learning techniques.
ChatGPT was launched as a prototype in November 2022 and quickly garnered attention for its detailed responses and articulate answers across many domains of knowledge. Its uneven factual accuracy was identified as a significant drawback.
After reading about it online non-stop, I was very curious to test this new amazing AI. It took only a short period of time before I was extremely impressed with the results. Yet, that made me think... Is this the end of engineering? Can ChatGPT take requirements and implement them into code?
To test this, I decided to ask ChatGPT to solve the Advent of Code 2022 - Day 10 puzzle. Since I usually write my solutions in functional programming, I decided to add this to the requirements as well.
Iteration 1
Write me code in Kotlin using functional programming that solves this puzzle:
<puzzle description...>
After a few seconds, I received the following code:
fun solvePuzzle(program: List<Instruction>): List<Int> {
// Initialize X register with value 1
var x = 1
// Initialize a list to store signal strengths
val signalStrengths = mutableListOf<Int>()
// Loop through the program, executing each instruction
program.forEachIndexed { index, instruction ->
when (instruction) {
is Noop -> {
// Do nothing
}
is AddX -> {
x += instruction.v
}
}
// Check if the current cycle is the 20th, 60th, 100th, etc.
if (index % 40 == 19) {
// Calculate the signal strength for this cycle and add
// it to the list
signalStrengths.add(index * x)
}
}
return signalStrengths
}
Iteration 2
While the code is really nice, I noticed that it does not match the input of the puzzle. So, I asked ChatGPT to accept the input as a List<String> instead.
Please replace the input of the function with a List of strings where each string represents a single operation in the input file.
The response was very quick:
fun solvePuzzle(program: List<String>): List<Int> {
// Initialize X register with value 1
var x = 1
// Initialize a list to store signal strengths
val signalStrengths = mutableListOf<Int>()
// Loop through the program, executing each instruction
program.forEachIndexed { index, instruction ->
when (instruction) {
"noop" -> {
// Do nothing
}
else -> {
// Split the instruction string into the operation
// and value
val parts = instruction.split(" ")
val operation = parts[0]
val value = parts[1].toInt()
// Increment the X register by the value
x += value
}
}
// Check if the current cycle is the 20th, 60th, 100th, etc.
if (index % 40 == 19) {
// Calculate the signal strength for this cycle and add it
// to the list
signalStrengths.add(index * x)
}
}
return signalStrengths
}
Iteration 3
Next, I noticed that the output is wrong. We want to receive the sum of all signals, not a list of them.
There's a bug in the code. The solution should return the sum of all signals, not a list of integers.
This time, ChatGPT quickly updated the solution:
fun solvePuzzle(program: List<String>): Int {
// Initialize X register with value 1
var x = 1
// Initialize a variable to store the sum of the signal strengths
var signalSum = 0
// Loop through the program, executing each instruction
program.forEachIndexed { index, instruction ->
when (instruction) {
"noop" -> {
// Do nothing
}
else -> {
// Split the instruction string into the operation
// and value
val parts = instruction.split(" ")
val operation = parts[0]
val value = parts[1].toInt()
// Increment the X register by the value
x += value
}
}
// Check if the current cycle is the 20th, 60th, 100th, etc.
if (index % 40 == 19) {
// Calculate the signal strength for this cycle and add
// it to the sum
signalSum += index * x
}
}
return signalSum
}
Iteration 4
Note that this version already includes some unnecessary code. val operation = parts[0] is not used anywhere in this function. This can be easily solved by using an anonymous variable. For example:
// Split the instruction string into the operation and value
val (_, value) = instruction.split(" ")
Moreover, I noticed another bug in the code. addx operations should take 2 cycles, while noop takes only 1. No panic, let's ask ChatGPT to fix the issue!
There is a bug in your solution. The
addxoperation should take 2 cycles, whilenooptakes only 1.
The solution quickly arrived:
fun solvePuzzle(program: List<String>): Int {
// Initialize X register with value 1
var x = 1
// Initialize a variable to store the sum of the signal strengths
var signalSum = 0
// Initialize a variable to keep track of the current cycle
var currentCycle = 0
// Loop through the program, executing each instruction
program.forEach { instruction ->
when (instruction) {
"noop" -> {
// Increment the current cycle by 1
currentCycle++
}
else -> {
// Split the instruction string into the operation
// and value
val parts = instruction.split(" ")
val operation = parts[0]
val value = parts[1].toInt()
// Increment the current cycle by 2
currentCycle += 2
// Increment the X register by the value
x += value
}
}
// Check if the current cycle is the 20th, 60th, 100th, etc.
if (currentCycle % 40 == 19) {
// Calculate the signal strength for this cycle and add
// it to the sum
signalSum += currentCycle * x
}
}
return signalSum
}
Iteration 5
After that, I noticed yet another bug in the code. Since addx takes 2 cycles, we need to check if the signal sum should be currentCycle * x or currentCycle * (x + value) depending on the schedule of the cycle. I asked ChatGPT to fix the issue:
There is another bug in the code. Since
addxtakes 2 cycles, you should either include or exclude the new value when calculating the signal sum depending on the schedule of it.
Quickly, I received an updated version of the code:
fun solvePuzzle(program: List<String>): Int {
// Initialize X register with value 1
var x = 1
// Initialize a variable to store the sum of the signal strengths
var signalSum = 0
// Initialize a variable to keep track of the current cycle
var currentCycle = 0
// Loop through the program, executing each instruction
program.forEach { instruction ->
when (instruction) {
"noop" -> {
// Increment the current cycle by 1
currentCycle++
// Check if the current cycle is the 20th,
// 60th, 100th, etc.
if (currentCycle % 40 == 19) {
// Calculate the signal strength for this cycle
// and add it to the sum
signalSum += currentCycle * x
}
}
else -> {
// Split the instruction string into the operation
// and value
val parts = instruction.split(" ")
val operation = parts[0]
val value = parts[1].toInt()
// Increment the current cycle by 2
currentCycle += 2
// Check if the current cycle is the 20th, 60th,
// 100th, etc.
if (currentCycle % 40 == 19) {
// Calculate the signal strength for this cycle
// and add it to the sum
signalSum += currentCycle * x
}
// Increment the X register by the value
x += value
}
}
}
return signalSum
}
Iteration 6
Let's avoid the obvious code duplication we have here. The solution is still wrong. addx does not take into account whether it should include the value in the calculation.
fun solvePuzzle(program: List<String>): Int {
// Initialize X register with value 1
var x = 1
// Initialize a variable to store the sum of the signal strengths
var signalSum = 0
// Initialize a variable to keep track of the current cycle
var currentCycle = 0
// Loop through the program, executing each instruction
program.forEach { instruction ->
when (instruction) {
"noop" -> {
// Increment the current cycle by 1
currentCycle++
// Check if the current cycle is the 20th, 60th,
// 100th, etc.
if (currentCycle % 40 == 19) {
// Calculate the signal strength for this cycle
// and add it to the sum
signalSum += currentCycle * x
}
}
else -> {
// Split the instruction string into the operation
// and value
val parts = instruction.split(" ")
val operation = parts[0]
val value = parts[1].toInt()
// Increment the current cycle by 2
currentCycle += 2
// Check if the current cycle is the 19th or the
// 20th, 59th or 60th, 99th or 100th, etc.
if (currentCycle % 40 == 19 || currentCycle % 40 == 0) {
// Calculate the signal strength for this cycle
// and add it to the sum
signalSum += currentCycle * x
}
// Increment the X register by the value
x += value
}
}
}
return signalSum
}
While the code finally checks which iteration we are in for addx, it still doesn't take the value evaluation into account. At this point, I was already exhausted, and I realized that I was debugging someone else's messy code.
Moreover, ChatGPT lost the connection to my browser, and I didn't want to start all over again.
For comparison, this is the code I wrote to solve the task. While it's far from perfect, it's simpler, easier to reason about, and it works:
fun solvePuzzle(program: List<String>): Int {
var register = 1
var cycle = 1
return program
.filter { it.isNotBlank() }
.map { instruction ->
cycle++
var signal = cycle.getCycleSignal(cycle, register)
if (instruction.startsWith("addx")) {
// addx operation takes 2 cycles
cycle++
val (_, value) = instruction.split(" ")
register += value.toInt()
signal += cycle.getCycleSignal(cycle, register)
}
signal
}
.sum()
}
private fun Int.getCycleSignal(cycle: Int, register: Int): Int =
if (cycle % 40 == 20) cycle * register
else 0
Conclusion
While ChatGPT seems to work nicely for human interactions, it works poorly when generating code from requirements. It can be used as inspiration for your code, but as you have seen, at some point, I just started debugging someone else's code, and the code became very messy. That's why I don't believe that ChatGPT will replace us any time soon. We're safe. For now.
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Top comments (2)
That's the point. And describing requirements in human language is not easy at all. I think this itself is an exponetial Problem as soon as your requirements are getting more complex...
I fully agree, but if everyone talking about ChatGPT (or any other AI for that matter) replacing engineers it means that for example product owners could “write” code alone.
Currently we’re not there and indeed that’s not an easy problem to solve.
I do see a lot of value with this, but also find it a bit scary how confident it is when showing wrong results (for example, I’ve seen an article that was generated by ChatGPT about why eating glass improves your productivity)