In the field of technology there are a numerous amount of keys and entries that you will need to learn in order to complete a variety of tasks. With AVL trees they are directly related to search tasks, giving users the ability to find the information they need. Commonly related to a red-black tree, both operations require O(log n) time for simple operations. Below is a compiled list of all of the advantages and disadvantages of using an AVL tree in computer science applications.
List of Pros of AVL Trees
1. Faster Search Operations
The most prevalent benefit of AVL trees is the fact that they offer faster search operations than their counterparts such as red-black trees. This means that users are able to complete their tasks much quicker than if they were to rely on other search operations. Typically this is imperative for coding to ensure that projects are completed in a timely manner. It is also essential for when users need to complete searches faster and in a more reliable nature.
2. Balancing Capabilities
One of the main concerns that computer science professionals have is to ensure that their trees are balanced and with AVL trees, there is a higher likelihood of them being balanced. An unbalanced tree means that it will take longer for operations to be performed, resulting in time intensive lookup applications. The longer it takes for a tree to be balanced, the longer the search will take. Typically referred to as a self balancing binary search tree, the three major operations you can complete with an AVL tree include search, insert, and delete.
List of Cons of AVL Trees
1. Slow Inserts and Deletes
The largest disadvantage to using an AVL tree is the fact that in the event that it is slightly unbalanced it can severely impact the amount of time that it takes to perform inserts and deletes. Computer science professionals find that since AVL trees don’t allow anything outside of -1 to 1, it can drastically slow these 2 functions down.
2. Fast Updating Systems
In the event that you’re working on a system that has the tendency to update quickly then it is advisable to avoid AVL trees. This is because they work much better with systems that are rarely updated, giving the system time to acquire all of the information that it needs to perform at its best. If you are working with controlled data, an AVL tree is your best option.