How Skip List Is Implemented in Data Structure?


Angela Bailey

How Skip List Is Implemented in Data Structure?

A skip list is a data structure that allows efficient search, insertion, and deletion operations. It is similar to a linked list but includes additional layers of linked lists, known as “levels,” which allow for faster searching.

Overview of Skip Lists

Skip lists were invented by William Pugh in 1989 as an alternative to balanced search trees. They provide logarithmic time complexity for search, insertion, and deletion operations on average.

A skip list consists of multiple levels, where the bottom level is a regular sorted linked list. Each higher level acts as an “express lane” to skip over elements in the lower levels.

Implementation Details

To implement a skip list, you can use the following HTML elements:

  • <p>: Used to enclose paragraphs of text.
  • <h2>: Used for section headings.
  • <h3>: Used for subheadings within sections.
  • <ul>: Used to create unordered lists.
  • <li>: Used to create list items within unordered lists.

The Node Structure

In a skip list, each element is represented by a node. The node contains two main components: the value and an array of pointers called “next” that point to the next nodes at each level. The height of the next array determines the level of the node.

struct Node {
    T value;
    Node** next;

Levels and Promotion

Each level in a skip list represents a different probability of skipping elements. The bottom level contains all the elements, while each subsequent level contains fewer elements.

When inserting a new element, it is randomly assigned a level. If the new element’s level is greater than the current highest level of the skip list, the skip list is extended by adding a new top-level and updating the pointers accordingly.


To search for an element in a skip list, we start from the top-level and traverse through each level until we find an element that is greater than or equal to our Target value. We then move down to the next level and repeat until we reach the bottom level.

If an element with the Target value is found, we return it. Otherwise, we conclude that the element does not exist in the skip list.


The insertion process involves searching for the correct position to insert the new element and then updating the pointers at each level accordingly. To maintain balance, we randomly assign a level to the new element based on a probability distribution.


To delete an element from a skip list, we first search for its position. Once found, we update the pointers of previous nodes to bypass it at each level. Finally, we free up memory occupied by the deleted node.

Benefits of Skip Lists

  • Simplicity: Skip lists are relatively easy to implement compared to other balanced search tree structures like AVL trees or red-black trees.
  • Ease of modification: Insertion and deletion operations are straightforward in skip lists as they do not require balancing steps.
  • Efficiency: Skip lists provide logarithmic time complexity for search, insertion, and deletion on average, making them suitable for large datasets.


Skip lists are a powerful data structure that combines simplicity with efficiency. By incorporating multiple levels of linked lists, skip lists allow for fast search, insertion, and deletion operations. They are particularly useful when maintaining balance is not a primary concern.

Whether you’re implementing a skip list in your own project or simply expanding your knowledge of data structures, understanding how skip lists work and their implementation details can greatly benefit your programming skills.

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