Tag Archives: avoidance

Naked Aggression with the Heap

MP900321198I’ll begin my Idiosyncratic C++ series with a discussion of the heap, its abuses, and its alternatives.

The Heap

The heap does not seem to be well understood among many C++ programmers.   I’m referring to the trade-offs involved with using it, not its underlying implementation.  Heap allocation should be a means of last resort, a necessary evil for getting the job done.   As a general pool of memory available for program use, it is slower and riskier to use than the stack.  And yet, many beginning C++ programmers are enamored with it.  Perhaps it’s a misappropriation of the ‘new’ keyword from managed languages like Java and C# – a conflation of the concepts of object creation and heap allocation.  In any case, it’s often the first tool the programmer reaches for in allocating memory.  And when it is deemed necessary, it is often used both “nakedly” and “aggressively”, leading to unnecessary risks for program safety.

The Stack

By contrast, the stack is the original, automatic, hardware-accelerated memory manager.  It’s impossible to leak stack memory, and difficult to double-delete it (or single-delete it, for that matter).  [The original purpose of the “auto” keyword in C/C++ was to designate an “automatic storage” variable with local block scope, in contrast to the “static” keyword.  But since the language provided “auto” as a default, the keyword found little use and has been re-purposed for type deduction.]  At its foundation, the computer is a stack-based machine.  Functional programmers know this and design their algorithms around it.  But it’s just as true for the object-oriented programmer.  Cultivating a “stack-based discipline” can vastly simplify designs, eliminate whole classes of bugs (heap-based), and improve efficiency and readability.


Many heap allocations are simply not necessary.  Examples include:

  • Locals
    Local variables newed and deleted entirely within a given block scope.   This must certainly be a holdover from managed languages.
  • Members
    Aggregate classes newing members in a constructor and delete-ing them in a destructor.  Sometimes this is necessary if a member does not have a public constructor (s obtained from a factory), is implementing the pimpl pattern, and so on.  However, I have seen many cases where member data is created on the heap with evidently no conscious thought.
  • Collections
    The (mistaken) belief that every collection must be implemented with a heap-based library template.  The corollary to this is that aggregate arrays are evil.  This is probably a misapplication of the good advice not to allocate raw arrays from the heap, preferring standard collections.  But this assumes that dynamic allocation is even needed in the first place.


Many heap allocations are made directly from client code.  Calls to new/malloc and delete/free are manually paired, and may be arbitrarily distant in code.  The risk of mismanaging these allocations is high.  Leaks can result from exceptions, or multiple function returns, or simply overlooking a terminal branch.  Double-deletes may result from pointer aliasing, or not having clear responsibility for ownership.

Avoiding the Heap

Now that we’ve identified a few risks of heap use, let’s discuss ways to avoid it.

  • Locals
    For local variables, the cure is simple – allocate the object directly on the stack, rather than through a pointer.
  • Members
    The same approach should be used for member data.  This does not guarantee the member will live on the stack.  Instead, it ties the allocation policy of the member to its containing class, so that it may live on the stack or on the heap.
  • Collections
    When dealing with simple, static collections, use an aggregate-initialized array.  There are some restrictions to this technique, when dealing with user-defined types.  However, these can usually be worked around, and should improve as the rules for POD types are revised and loosened.  There is virtually no advantage to dynamically allocating a collection of static (compile-time constant) objects, when a fixed array will do.
  • Algorithms
    Some heap allocations may indicate a flawed algorithm.  An example would be the creation or collection of data at a deeper level in the stack than where it is consumed.  In this case, the data must clearly be placed on the heap so it can “swim upstream”, against the call stack current.  The solution is to invert the pattern and use a more “functional” approach, passing  data down the call stack to where it is needed.  This can be generalized to multiple data flows.
  • Recursion
    Similar to the preceding is to use a recursive approach, over a loop-based approach.  This can be especially helpful in avoiding the creation of short-lived heap-based collections, where an element may depend on the computation of prior elements (e.g., Fibonacci).  A map-reduce pattern can then move the reducing logic to the terminal condition of the recursion.
  • alloca
    Finally, consider that “dynamic allocation” != “heap allocation”.  The CRT function alloca enables fast, safe, dynamic allocation on the stack.  This can be very effective in performance critical situations where many small objects are frequently allocated and freed, such as with 3D mesh processing algorithms.  [Note: there are some challenges to the effective use of alloca and its ilk, malloca and freea.  The scoping requirements are tricky, foiling attempts to wrap calls in an RAII pattern.  But the utility of the function outweighs these concerns.]

Holding the Heap at Arm’s Length

In the event the heap cannot be avoided, it should be “treated with modesty”.  Direct calls to new/delete should be avoided if possible, or their exposure minimized.  Smart pointers should be used systematically and universally, to ensure exception-safe unwind behavior.  Locals and members which require heap allocation (factory-based, pimpl) should be wrapped in smart pointers.

  • For shared (aliased) reference-counted smart pointers, std::shared_ptr  should be used.  The std::make_shared template function should be used to allocate std::shared_ptr objects safely and efficiently.
  • For simple, unshared “singleton” smart pointers, either as class members or local variables, std::unique_ptr should be used to manage heap calls in an exception-safe manner.  As with std::make_shared, std::make_unique may be offered in the future for creating std::unique_ptr objects safely.
  • [Note that with C++11, legacy smart pointer templates, such as auto_ptr, are now considered obsolete.]

In summary, my advice is to use the heap as sparingly and indirectly as possible.  Your peers, testers, and customers will appreciate it.