Bugs that the Rust compiler catches for you

Over the decades, Humans have proved to be pretty bad at producing bug-free software. Trying to apply our approximative, fuzzy thoughts to perfectly logical computers seems doomed.

While the practice of code reviews is increasing, especially with the culture of Open Source becoming dominant, the situation is still far from perfect: it costs a lot of time and thus money.

What if, instead, we could have a companion, always available, never tired, and the icing on the cake, that doesn’t cost the salaray of a developer that would help us avoid bugs in our software before they reach production?

Let’s see how a modern compiler and type system helps prevent many bugs and thus helps increase the security for everyone and reduces the costs of software production and maintenance.

Resources leaks

It’s so easy to forget to close a file or a connection:

resp, err := http.Get("")
if err != nil {
    // ...
// defer resp.Body.Close() // DON'T forget this line

On the other hand, Rust enforces RAII (Resource Acquisition Is Initialization) which makes it close to impossible to leak resources: they automatically close when they are dropped.

  let wordlist_file = File::open("wordlist.txt")?;
  // do something...

  // we don't need to close wordlist_file
  // it will be closed when the variable goes out of scope

Unreleased mutexes

Take a look at this Go code:

type App struct {
  mutex sync.Mutex
  data  map[string]string

func (app *App) DoSomething(input string) {
  defer app.mutex.Unlock()
  // do something with data and input

So far, so good. but when we want to process many items, things can go very bad fast

func (app *App) DoManyThings(input []string) {
  for _, item := range input {
      defer app.mutex.Unlock()
      // do something with data and item

We just created a deadlock because the mutex lock is not released when expected but at the end of the function.

In the same way, RAII in Rust helps to prevent unreleased mutexes:

for item in input {
  let _guard = mutex.lock().expect("locking mutex");
  // do something
  // mutex is released here as _guard is dropped

Missing switch cases

Let’s imagine we are tracking the status of a product on an online shop:

const (
  StatusUnknown   Status = 0
  StatusDraft     Status = 1
  StatusPublished Status = 2

switch status {
    case StatusUnknown:
        // ...
    case StatusDraft:
        // ...
    case StatusPublished:
        // ...

But then, if we add the StatusArchived Status = 3 variant and forget to update this switch statement, the compiler still happily accepts the program and lets us introduce a bug.

While in Rust, a non-exhaustive match produces a compile-time error:

#[derive(Debug, Clone, Copy)]
enum Platform {

impl fmt::Display for Platform {
    fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
        match self {
            Platform::Linux => write!(f, "Linux"),
            Platform::Macos => write!(f, "macOS"),
            // Compile time error! We forgot Windows and Unknown

Invalid pointer dereference

As far as I know, it’s not possible to create a reference to an invalid address in safe Rust.

type User struct {
    // ...
    Foo *Bar // is it intended to be used a a pointer, or as an optional field?

And even better, because Rust has the Option enum, you don’t have to use null pointer to represent the absence of something.

struct User {
    // ...
    foor: Option<Bar>, // it's clear that this field is optional

Uninitialized variables

Let’s say that we are processing users accounts:

type User struct {
  ID          uuid.UUID
  CreatedAt   time.Time
  UpdatedAt time.Time
  Email       string

func (app *App) CreateUser(email string) {
    // ...
    now := time.Now().UTC()

    user := User {
      ID: uuid.New(),
      CreatedAt: now,
      UpdatedAt: now,
      Email: email,
    err = app.repository.CreateUser(app.db, user)
    // ...

Good, but now, we need to add the field AllowedStorage int64 to the User structure.

If we forget to update the CreateUser function, the compiler will still happily accept the code without any changes and use the default value of and int64: 0, which may not be what we want.

While the following Rust code

struct User {
  id: uuid::Uuid,
  created_at: DateTime<Utc>,
  updated_at: DateTime<Utc>,
  email: String,
  allowed_storage: i64,

fn create_user(email: String)
    let user = User {
      id: uuid::new(),
      created_at: now,
      updated_at: now,
      email: email,
      // we forgot to update the function to initialize allowed_storage

produces a compile-time error, preventing us from shooting ourselves in the foot.

Unhandled exceptions and errors

It may sound stupid, but you can’t have unhandled exceptions if you don’t have exceptions…

panic!() exists in Rust, but that’s not how recoverable errors are handled.

Thus, by imposing the programmers to handle each and every error (or the compiler refuses to compile the program), all while providing good tools to handle errors (the Result enum and the ? operator), the Rust compiler helps to prevent most (if not all) errors related to error handling.

Data races

Thanks to the Sync and Send traits, Rust’s compiler can statically assert that no data race is going to happen.

How does it work? You can learn more in the good write-up by Jason McCampbell.

In Go, data streams are hidden behind the io.Writer interface. On one hand, it allows to simplify its usage. On the other hand, it can reserve some surprise when used with types we don’t expect to be a stream, bytes.Buffer for example.

And that’s exactly what happened to me a month ago: a bytes.Buffer was reused in a loop to render templates which leads the templates to be appended to the buffer instead of the buffer to be cleaned and reused.

It would have never happened in Rust as Streams are a very specific type and would never have been used in this situation.

Some Closing Thoughts

Are smart compilers the end of bugs and code reviews?

Of course not! But a strong type system, and the associated compiler are a weapon of choice for anyone who wants to drastically reduce the number of bugs in their software and make their users / customers happy.

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