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Advent of Code 2019 - Day 1 - Calculate fuel mass

The full problem statement can be found on the Advent of Code 2019 page. I recommend reading the description on their page as the context of the problem is quite fun. However, you can find the relevant portions below.

NOTE: All the code in this post, including this write-up itself, can be found or generated from the GitHub repository.

Problem 1a

At the first Go / No Go poll, every Elf is Go until the Fuel Counter-Upper. They haven’t determined the amount of fuel required yet.

Fuel required to launch a given module is based on its mass. Specifically, to find the fuel required for a module, take its mass, divide by three, round down, and subtract 2.

Problem 1b

During the second Go / No Go poll, the Elf in charge of the Rocket Equation Double-Checker stops the launch sequence. Apparently, you forgot to include additional fuel for the fuel you just added.

Fuel itself requires fuel just like a module - take its mass, divide by three, round down, and subtract 2. However, that fuel also requires fuel, and that fuel requires fuel, and so on. Any mass that would require negative fuel should instead be treated as if it requires zero fuel; the remaining mass, if any, is instead handled by wishing really hard, which has no mass and is outside the scope of this calculation.

So, for each module mass, calculate its fuel and add it to the total. Then, treat the fuel amount you just calculated as the input mass and repeat the process, continuing until a fuel requirement is zero or negative.


The solutions to both problems are quite simple. The full source code is available at the above link.

However, I will highlight a realization I had - and repeatedly have, so maybe I need to do a better job of learning my lesson the first time!

First, here is the source code from my solution to Problem 1a.

pub fn calculate_fuel(mass: u64) -> u64 {
  let denominator = 3u64;
  let subtract_from = 2u64;

  (mass.div_euclid(denominator)) - subtract_from

While this code is simple, it contains an insidious bug. It has to do with an invariant of u64, specifically around subtraction.

The problem is that when a subtraction occurs with two u64 values, it can result in an overflow if the second number is larger than the first (e.g. 1u64 - 2u64). This causes a panic.

Now, when I was testing Problem 1a, I only used the samples provided in the problem statement. None of the samples exhibited this behavior, so I thought the solution was correct. Based on this belief, I wrote the solution to Problem 1b using the logic from Problem 1a. Hoever, as you can see from the problem statement for Problem 1b, it is guaranteed to trigger the panic because we continually look for smaller fuel values until we don’t need any more fuel.

Avoiding the problem

There is a very easy way I could have avoided this problem - by using property-based testing. I have used the proptest crate in the past, and it has been very helpful in finding exactly these kinds of bugs - by ensuring that type-level invariants are not violated. However, in this case, I foolishly thought that this wasn’t needed for the first Advent of Code problem.

When I hit the issue with Problem 1b, I re-wrote the same algorithm as follows:

pub fn calculate_fuel(mass: u64) -> u64 {
  // Safe helper to calculate fuel needed for a single mass while avoiding a
  // panic with `u64` subtraction.
  fn calculate_single_fuel(mass: u64) -> u64 {
    let denominator = 3u64;
    let subtract_from = 2u64;

    // Ensure that there is no overflow for `u64`.
    let div_result: u64 = mass.div_euclid(denominator);
    if div_result < subtract_from {
    } else {
      div_result - subtract_from

  // Tail-recursive helper to calculate total fuel needed.
  fn cf_helper(acc: u64, mass: u64) -> u64 {
    if mass == 0 {
    } else {
      let fuel = calculate_single_fuel(mass);
      cf_helper(acc + fuel, fuel)

  cf_helper(0, mass)

The cf_helper function is unique to Problem 1b. However, calculate_single_fuel is the new version of the previous calculate_fuel. Even though the function is small, it is twice the size of the original with a new conditional check.

This check prevents the aforementioned issue with the code. After I found this problem, I added property-based testing to the codebase. I already knew about the issue with the solution to Problem 1a, so I limited property-based testing to Problem 1b.

As you can imagine, proptest immediately identified the obvious mirror to the problem, i.e. calculating a required fuel that is so large that it overflows the maximum value of u64. This issue was found when performing property-based testing on calculate_fuels, whose source code is below.

pub fn calculate_fuels(mass: Vec<u64>) -> u64 {
    .map(|e| calculate_fuel(*e))
    .fold(0, |acc, e| acc + e)

And quite helpfully, proptest identified a minimal test case to cause the overflow.

t = [

However, I did not fix this problem programmatically and for good reason (I believe). First, dealing with this problem will potentially add significant complexity to the solution. Based on my understanding of the problem statement, this is not a realistic occurrence. Thus, I added an assumption to the function and, if that assumption is violated, then the program will panic.

What does this mean from a “real-world” perspective? If this was a function in a real-world solution, then the first question to ask the domain experts would be whether they consider this situation to be an issue. If it is identified as a domain-level problem with some expected behavior, then it must be addressed explicitly in the code (e.g. creating an internal type with its own invariants, returning a Result, etc.). However, if it is not, then a panic is a valid response and if the panic occurs when someone is using the library, the situation should be discussed with those same experts to understand how it should be handled. This article from Scott Wlaschin makes a good case against protecting against such errors when there is a need to “fail fast” so that problems can be quickly identified and addressed up front. There is no obvious way for the program to continue and for Santa to get back to Earth if fuel cannot be calculated. As such, failing is the best option so that assumptions and designs can be re-reviewed and re-discussed thoroughly.

In this instance, I have left the code as-is and have not addressed the issue with Problem 1b’s calculate_fuels method.


I seem to always be re-learning a lesson when it comes to property-based testing. And that lesson is - just do it. At worst, it will validate parts of the design. But more often than not, it will highlight issues ranging from logic errors to implicit assumptions. And that can only help the code improve and be of higher quality when it is delivered.

As for the “bug” that has been left in the program, I do believe that attempting to handle this problem programmatically with incomplete information would be a case of incorrect over-engineering. Maybe if this library were exposed as a web service with wide-ranging use cases that cannot be anticipated during initial development, the response might be slightly different. However, in the end, libraries should deal with expected situations gracefully. Unexpected situations that result in errors should fail fast so that problems can be recognized and the defect can be reported and handled appropriately. Please note that I’m not referring to how end users of a program (i.e. non-technical folks) are presented with this issue. I am referring to other developers who are making use of a library.

See you in the next one!