What Data Structure Is Used to Store a Symbol Table?


Larry Thompson

When it comes to storing a symbol table, there are several data structures that can be used. Each data structure has its own advantages and disadvantages, and the choice depends on the specific requirements of the application. In this article, we will explore some commonly used data structures for storing symbol tables.

Linked List

A linked list is a simple and straightforward data structure that can be used to store a symbol table. In a linked list, each element (node) contains both the symbol and its associated value.

The nodes are connected using pointers, forming a chain-like structure.

One advantage of using a linked list is that it allows for efficient insertion and deletion of symbols. However, accessing a specific symbol in the table requires traversing the entire list, which can be time-consuming for large symbol tables.

Hash Table

A hash table is another popular data structure for storing symbol tables. It uses a hash function to map each symbol to an index in an array.

Each array index contains a linked list of symbols with the same hash value.

The main advantage of using a hash table is its constant time complexity for both insertion and retrieval operations on average. However, collisions can occur when two symbols have the same hash value, requiring additional handling techniques such as chaining or open addressing.

Balanced Search Tree

A balanced search tree, such as an AVL tree or a red-black tree, can also be used to store a symbol table. These trees maintain their balance by performing rotations during insertions and deletions.

The benefit of using a balanced search tree is that it allows for efficient search operations with logarithmic time complexity. Additionally, these trees naturally maintain their order, making them suitable for applications where symbols need to be sorted.


A trie, or prefix tree, is a specialized data structure for storing symbol tables that work with strings. In a trie, each node represents a single character, and the symbols are stored by traversing the tree based on their characters.

Tries excel at searching for symbols with common prefixes and are often used in applications like autocomplete or spell checking. However, they can consume a significant amount of memory, especially for large symbol tables.


In conclusion, there are several data structures that can be used to store a symbol table, each with its own advantages and disadvantages. The choice of data structure depends on factors such as the size of the symbol table, the frequency of insertions and retrievals, and any specific requirements of the application.

Whether it’s a linked list, hash table, balanced search tree, or trie – understanding these different data structures can help you make an informed decision when designing your symbol table implementation.

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