Heap memory 2026-10-24
Storage used for heap allocation, with software object lifetimes not necessarily nested like procedure calls on a call stack. Garbage collection can reclaim unreachable software objects; keeping references to every allocated software object prevents that reclamation regardless of how little of each software object's data a program still needs.
Constructing channel implementations, decorators and adapters allocates software objects that hold state and references to other software objects. As configurations and temporary processing chains are replaced, some old software objects become unreachable. A typical Scala program on a managed runtime relies on garbage collection to recycle that storage; otherwise unreclaimed allocation can exhaust the available heap memory.
A reachable wrapper keeps its wrapped component reachable. Sharing a channel among several wrappers can extend its lifetime until all relevant references disappear. Many software objects alone do not imply that collection can free them: if the program deliberately retains every channel, those software objects remain live. The reason garbage collection is useful is repeated allocation combined with changing reachability, not an assumption that the integer-returning
apply operation allocates a fresh channel on every call.Garbage collection automatically reclaims allocated memory that is no longer reachable by the running program. Garbage collection roots such as active references and static storage lead through object-reference fields to reachable software objects in heap memory. A tracing garbage collection implementation preserves reachable software objects and can reclaim unreachable ones, including unreachable cycles.
An software object becoming unreachable is different from its state being old or its last object method call having finished. A retained reference can keep it live indefinitely. Collection timing is an implementation matter; automatic reclamation does not promise that an software object is reclaimed immediately when the final useful reference disappears.
Use the trait and node definition above. The reference to a “stack” in this part is a wording error: the declared class and operations implement a FIFO queue.
class ListQueue extends Queue[Int] {
private var first: QueueNode = null
private var last: QueueNode = null
private var size = 0
def enqueue(x: Int): Unit = {
require(size < Int.MaxValue, "queue size limit")
val fresh = new QueueNode(x, null)
if (last == null) first = fresh
else last.next = fresh
last = fresh
size += 1
}
def dequeue(): Int = {
require(first != null, "empty queue")
val answer = first.value
first = first.next
size -= 1
if (first == null) last = null
answer
}
def clear(): Unit = {
first = null
last = null
size = 0
}
def isEmpty: Boolean = size == 0
def length: Int = size
}Appending links the fresh node after the old tail, or establishes both endpoints when empty. Removing the head preserves the tail unless the final node was removed, in which case both endpoints become null. Clearing only discards the endpoint references; it need not visit or overwrite unreachable nodes. Thus all operations are in the usual pointer-operation/allocation cost model, with later garbage collection excluded from an individual operation's bound. The representation invariant and abstraction function show the specified sequence changes, including empty/singleton transitions.