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Traversal of a singly linked list is simple, beginning at the first node and following each next link until reaching the end: node := list.firstNode while node not null (do something with node.data) node := node.next The following code inserts a node after an existing node in a singly linked list. The diagram shows how it works.
A non-blocking linked list is an example of non-blocking data structures designed to implement a linked list in shared memory using synchronization primitives: Compare-and-swap; Fetch-and-add; Load-link/store-conditional; Several strategies for implementing non-blocking lists have been suggested.
Linked list implementations, especially one of a circular, doubly-linked list, can be simplified remarkably using a sentinel node to demarcate the beginning and end of the list. The list starts out with a single node, the sentinel node which has the next and previous pointers point to itself. This condition determines if the list is empty.
Expressions are written as lists, using prefix notation. The first element in the list is the name of a function, the name of a macro, a lambda expression or the name of a "special operator" (see below). The remainder of the list are the arguments. For example, the function list returns its arguments as a list, so the expression
The first and last nodes of a doubly linked list for all practical applications are immediately accessible (i.e., accessible without traversal, and usually called head and tail) and therefore allow traversal of the list from the beginning or end of the list, respectively: e.g., traversing the list from beginning to end, or from end to beginning, in a search of the list for a node with specific ...
Perhaps the simplest persistent data structure is the singly linked list or cons-based list, a simple list of objects formed by each carrying a reference to the next in the list. This is persistent because the tail of the list can be taken, meaning the last k items for some k, and new nodes can be added in front of it. The tail will not be ...
A stack may be implemented as, for example, a singly linked list with a pointer to the top element. A stack may be implemented to have a bounded capacity. If the stack is full and does not contain enough space to accept another element, the stack is in a state of stack overflow. A stack is needed to implement depth-first search.
Selection sort can also be used on list structures that make add and remove efficient, such as a linked list. In this case it is more common to remove the minimum element from the remainder of the list, and then insert it at the end of the values sorted so far. For example: