# A Memory-Efficient Doubly Linked List

In the quest to make small devices cost effective, manufacturers often need to think about reducing the memory size. One option is to find alternative implementations of the abstract data types (ADTs) we are used to for our day-to-day implementations. One such ADT is a doubly linked list structure.

In this article, I present a conventional implementation and an alternative implementation of the doubly linked list ADT, with insertion, traversal and deletion operations. I also provide the time and memory measurements of each to compare the pros and cons. The alternative implementation is based on pointer distance, so I call it the pointer distance implementation for this discussion. Each node would carry only one pointer field to traverse the list back and forth. In a conventional implementation, we need to keep a forward pointer to the next item on the list and a backward pointer to the previous item. The overhead is 66% for a conventional node and 50% for the pointer distance implementation. If we use multidimensional doubly linked lists, such as a dynamic grid, the savings would be even greater.

A detailed discussion of the conventional implementation of doubly linked lists is not offered here, because they are discussed in almost every data structure and algorithm book. The conventional and the distance pointer implementations are even used in the same fashion to have comparable memory and time usage statistics.

We define a node of pointer distance implementation like this:

typedef int T; typedef struct listNode{ T elm; struct listNode * ptrdiff; };

The ptrdiff pointer field holds the difference between the pointer to the next node and the pointer to the previous node. Pointer difference is captured by using exclusive OR. Any instance of such a list has a StartNode and an EndNode. StartNode points to the head of the list, and EndNode points to the tail of the list. By definition, the previous node of the StartNode is a NULL node; the next node of the EndNode also is a NULL node. For a singleton list, both the previous node and next node are NULL nodes, so the ptrdiff field holds the NULL pointer. In a two-node list, the previous node to the StartNode is NULL and the next node is the EndNode. The ptrdiff of the StartNode is the exclusive OR of EndNode and NULL node: EndNode. And, the ptrdiff of the EndNode is StartNode.

The insertion and deletion of a specific node depends on traversal. We need only one simple routine to traverse back and forth. If we provide the StartNode as an argument and because the previous node is NULL, our direction of traversal implicitly is defined to be left to right. On the other hand, if we provide the EndNode as an argument, the implicitly defined direction of traversal is right to left. The present implementation does not support traversal from the middle of the list, but it should be an easy enhancement. The NextNode is defined as follows:

typedef listNode * plistNode; plistNode NextNode( plistNode pNode, plistNode pPrevNode){ return ((plistNode) ((int) pNode->ptrdiff ^ ( int)pPrevNode) ); }

Given an element, we keep the pointer difference of the element by exclusive ORing of the next node and previous node. Therefore, if we perform another exclusive OR with the previous node, we get the pointer to the next node.

Given a new node and the element of an existing node, we would like to insert the new node after the first node in the direction of traversal that has the given element (Listing 1). Inserting a node in an existing doubly linked list requires pointer fixing of three nodes: the current node, the next node of the current node and the new node. When we provide the element of the last node as an argument, this insertion degenerates into insertion at the end of the list. We build the list this way to obtain our timing statistics. If the InsertAfter() routine does not find the given element, it would not insert the new element.

**Listing 1. Function to Insert a New Node
**

void insertAfter(plistNode pNew, T theElm) { plistNode pPrev, pCurrent, pNext; pPrev = NULL; pCurrent = pStart; while (pCurrent) { pNext = NextNode(pCurrent, pPrev); if (pCurrent->elm == theElm) { /* traversal is done */ if (pNext) { /* fix the existing next node */ pNext->ptrdiff = (plistNode) ((int) pNext->ptrdiff ^ (int) pCurrent ^ (int) pNew); /* fix the current node */ pCurrent->ptrdiff = (plistNode) ((int) pNew ^ (int) pNext ^ (int) pCurrent->ptrdiff); /* fix the new node */ pNew->ptrdiff = (plistNode) ((int) pCurrent ^ (int) pNext); break; } pPrev = pCurrent; pCurrent = pNext; } }

First, we traverse the list up to the node containing the given element by using the NextNode() routine. If we find it, we then place the node after this found node. Because the next node has pointer difference, we dissolve it by exclusive ORing with the found node. Next, we do exclusive ORing with the new node, as the new node would be its previous node. Fixing the current node by following the same logic, we first dissolve the pointer difference by exclusive ORing with the next current node. We then do another exclusive ORing with the new node, which provides us with the correct pointer difference. Finally, since the new node would sit between the found current node and the next node, we get the pointer difference of it by exclusively ORing them.

Tools and Technologies for Scale and Reliability

by Linux Journal Editor Bill Childers

Sponsored by IBM

Scheduling Crontabs With an Enterprise Scheduler

11am CDT, April 29th

Moderated by *Linux Journal* Contributor Mike Diehl

Sponsored by Skybot

## Trending Topics

## Webinar: 8 Signs You’re Beyond Cron

*Scheduling Crontabs With an Enterprise Scheduler*

11am CDT, April 29th

Join *Linux Journal* and Pat Cameron, Director of Automation Technology at HelpSystems, as they discuss the eight primary advantages of moving beyond cron job scheduling. In this webinar, you’ll learn about integrating cron with an enterprise scheduler.

Android Candy: Intercoms | Apr 23, 2015 |

"No Reboot" Kernel Patching - And Why You Should Care | Apr 22, 2015 |

Return of the Mac | Apr 20, 2015 |

DevOps: Better Than the Sum of Its Parts | Apr 20, 2015 |

Play for Me, Jarvis | Apr 16, 2015 |

Drupageddon: SQL Injection, Database Abstraction and Hundreds of Thousands of Web Sites | Apr 15, 2015 |

- Tips for Optimizing Linux Memory Usage
- "No Reboot" Kernel Patching - And Why You Should Care
- DevOps: Better Than the Sum of Its Parts
- Return of the Mac
- Android Candy: Intercoms
- JavaScript All the Way Down
- Drupageddon: SQL Injection, Database Abstraction and Hundreds of Thousands of Web Sites
- Designing Foils with XFLR5
- Non-Linux FOSS: .NET?
- Play for Me, Jarvis

## Comments

## Worst. Linked List. Ever.

Worst. Linked List. Ever.

## This is an interesting

This is an interesting article. A criteria of a linked list is that any node by be unlinked from the list in O(1). Exclusive-or method requires history to move ahead similar to how parity is calculated. Thus, we must call this a memory efficient queue instead. The memory efficient queue is a nice technique to use in embedded systems.