The Setup-Cleanup problem

A comparison of programming idioms for doing cleanup work
A picture of the Sorcerer's apprentice enchanting brooms to fetch water

A fully automated cleanup strategy.

This is a comparison of different programming idioms for performing cleanup work.

Common use cases where this is used include:

A naive solution: Cluttered cleanups

int frobnicate() {

        int err = foo();
        if (err) {
                clean_up();  // <-- 1.
                return err;

        if (!bar()) {
                clean_up();  // <-- 2.
                return ERROR_ACCESS;


        clean_up();          // <-- 3.
        return SUCCESS;

There are now three places where clean_up() is being called (Code duplication), and they are all far away from the call to set_up(). When the code changes a bit, it’s easy to miss one and introduce cleanup issues. This is not a well-maintainable approach.

Linux kernel style (C)

The Linux kernel uses gotos to coordinate a function’s cleanup:

int frobnicate()
        int rc = 0;


        rc = foo();
        if (rc)
                goto out;

        if (!bar()) {
                rc = EACCES;
                goto out;


        clean_up();  // <--
        return rc;

All function exits happening after set_up() need to jump to the label where the clean_up() is done.

Note that this pattern can be nested: With multiple independent setup and cleanup steps, the function ends with a sequence of multiple cleanup operations and multiple exit labels (example).

A longer explanation is at Eli Bendersky’s website.

Resource Acquisition is Initialization (C++)

In C++, setup and cleanup is frequently bound to object lifetimes, which are deterministic there. This is an example using Abseil’s absl::MutexLock class:

void MyClass::Frobnicate() {
  absl::MutexLock l(&mutex_);

  Foo();  // under lock
  Bar();  // under lock
  Baz();  // under lock

The lifetime of the l variable ends with the function scope, and absl::MutexLock’s constructor and destructor are locking and unlocking the mutex.

This pattern can also be nested. C++ guarantees that variable destruction happens in the inverse order of construction.

The RAII pattern (Wikipedia) is also used in other languages like Rust (Drop trait).

To a similar extent, similar functionality to RAII is also available in C, when using the GCC-specific __attribute__((__cleanup__(f))) language extension. This extension lets you attach a cleanup function to a variable scope, but the cleanup is defined in the place where the variable is defined, not in the type.

As readers pointed out, a newer variant of C#’s using statement implements a similar non-nested cleanup bound to variable lifetime as well. See the documentation comment by Morgens Heller Gabe below for examples.

“Defer” statement (Go)

Go has a language feature for cleanup:

func (m *MyClass) Frobnicate() {
  defer m.mu_.Unlock()

  Foo()  // under lock
  Bar()  // under lock

The defer statement defers a function call until the current function exits.

The Zig language has syntactically similar defer and errdefer statements. Other than in Go, Zig executes the cleanup when leaving the current scope rather than when leaving the function.

“With” blocks and friends (Python, C#, Java)

Python implements a syntax which makes it easy to acquire resources during the execution of a nested block of commands.

def readfullfile(filename):
  with open(filename) as f:
    print("opened", filename)

The object returned by open() implements the context manager protocol, which means that it can be used in a with statement. When the with-scope exits, the cleanup functions will automatically get invoked (e.g. to close a file).

Cleanups get invoked in all cases when execution leaves the scope, no matter whether it happens through a regular exit, an early return or an exception.

Update: Multiple readers have pointed out that both C# and Java now support equivalent scoped statements as well:

In all of these cases, the used object must implement a special interface with a cleanup method, such as IDisposable in C# and AutoCloseable in Java.

Macros (Lisp)

Lisp macros are used similarly as Python’s with statements, but offer more ways to shoot yourself in the foot (Example from the book Practical Common Lisp by Peter Seibel):

(with-open-file (stream "/some/file/name.txt" :direction :output)
  (format stream "Some text."))  ; while file is opened

Here, with-open-file is a macro caring about opening and closing (spec). The user of the macro provides a sequence of commands to be executed with the opened file stream, e.g. (format stream "Some text.").

These macros are often named to start with the word with, but there are exceptions, e.g. save-excursion in Emacs Lisp.

From the caller perspective, this behaves similar as Python’s with statements, but they are usually expanded into a use of unwind-protect or a similar primitive depending on the Lisp dialect (comparable to tryfinally).

Try-Finally blocks (Java, C#, Python, …)

try blocks are primarily used for catching exceptions but in many languages they offer a finally clause as well, which is guaranteed to execute whenever the try scope exits, including on early returns and exceptions.

try {
  doWork();  // between setup and cleanup
} finally {

The construct tends to lead to deeper nesting when multiple cleanups need to be done.

Some languages have finally-like constructs which are independent of exceptions, like Smalltalk with Block»ensure:, unwind-protect in Common Lisp (on C2 wiki) and dynamic-wind in Scheme. (Scheme has the additional complication that it needs to deal with continuations.)

Todo lists (languages with closures)

In languages with closures or higher order functions, one way to defer work for later is to save functions to be executed later in a list:

def frobnicate():
  todos = []


  doWork()  # between setup and cleanup

  for f in todos:

One variant of this is addCleanup in Python’s unittest library for deferring work to be done after the test execution. Note that similarly to defer in Go, this lets us place the cleanup right together with the setup code, so that we can easily keep them in sync:

class FooTest(unittest.TestCase):
  # ...

  def test_service(self):
    srv = StartService()

    self.assertEqual(42, srv.Invoke())  # while running
Update: Since version 1.14, Go supports the same with T.Cleanup() to simplify test cleanup.

Passing higher-order functions (Ruby, Lisp?)

In Ruby, it’s common to pass down functions to other functions, as a way of structuring control flow and also for cleanup purposes. This invocation of executes the passed function (in between doend) with the opened file and closes the file afterwards."output.txt", "a") do |f|
  f.puts("Hello, world!")  # while file is open

This general technique is possible in all languages where passing down higher order functions is cheap, such as Ruby and Smalltalk. Smalltalk takes it to another level by expressing all control flow as method invocations, including loops and ifTrue:.

I’m not sure to what extent the Smalltalks use higher order functions for cleanup purposes as Ruby does. More imperative Lisps like CL expose mostly macros to users, but these will in turn use closure-passing unwinding primitives under the hood.

There is a technical twist here in that languages need special guarantees for these so-called downward funargs to be cheap.

A downward funarg is a higher-order function which is only passed down the stack but does not outlive the stack frame in which it was created. The captured variables referenced by a downward funarg can happily stay on the stack. This is in contrast to upward funargs which outlive their own stack frame and which require invisible heap allocations or similar tricks in the language.

setUp() and tearDown() in (JUnit, xUnit, …)

In the xUnit family of unit testing frameworks, tests are part of classes which get executed by a test runner. Each test class may optionally override setUp() and tearDown() hooks which get executed around every test execution, independent of whether that test succeeded or not.

In languages which provide a sane way of cleanup, I think that overriding the tearDown() hook should not be necessary and probably discouraged. I suspect the same is true for code in setUp(), but that is more related to ambient shared state which becomes tricky to modify when multiple tests rely on a subset of it in implicit ways.


These approaches are quite different to each other. In practice, the programming language is often already fixed, and then only a limited number of options exists.

In general, I found that in practice it helps to have setup and cleanup close to each other, so that it’s easy to keep them in sync. Go’s defer really shines there.

It’s even nicer to have them represented by the same construct as with Python’s with or C++’s RAII idiom. With these, the usage becomes safer, but you trade that for more effort in implementing classes that are with- and RAII-enabled. (In Python, this is somewhat mitigated with the contextlib module.)

Downward funargs are both safe, easy to use and simple to implement, but have a little overhead. That’s fair in most scripting cases, but wouldn’t work for the Linux kernel.

In terms of reasoning about performance, the Linux kernel has the approach where it’s most obvious what this translates to at the machine level, but the same amount of control is usually not needed in user space programs.

At a higher level, I believe it pays off to care about symmetric setup and cleanup steps as part of the same function wherever possible. It makes it easier to track where setups and cleanups are done across the codebase, and refactoring to such a design reduces state that has to be tracked across multiple functions.

Update (2020-01-13)

Thanks for all the positive feedback, particularly to everyone who pointed out related language features:

For Haskell, lgas mentioned the Bracket pattern, and dwohnitmok is mentioning linear types. Superficially this looks similar to dynamic-unwind and friends in Scheme and Lisp (see above), but my Haskell-fu is too weak to judge it. I suspect it would be hard to compare programming idioms between Haskell’s lazy purely functional evaluation and imperative programs.