Exploring the Benefits of Different Data Structures

Data structures are the first thing you are taught when learning any programming language. This is because data structures are an essential part of any computer program. They form the foundation of any software application and can have a huge impact on the performance of the application. This blog will discuss the importance of understanding the data structure and how it can affect an application's performance.

What is a Data Structure?

Data structures are used for organising data in a computer. It is used to,

• Process data
• Retrieve data 
• Store data

Data structures are used in all programming languages. Hence it is essential to understand the different kinds of data structures and how they work. 

Basic Types of Data Structures

Data structures come in all shapes and sizes,

• Arrays
• Linked lists
• Trees
• Hash tables
• Stacks

Arrays 

Arrays are one of the most basic data structures available. Arrays are usually indexed, meaning each item can be accessed by its position in the array ranging from 0 to (n-1), where n is the array's size.

Arrays are a data structure that stores data in a fixed-size list. They are great for storing data when you know the data size.

Arrays are also great for searching, as they can be quickly searched using binary search algorithms.

Pros

• They store a collection of related items in a single structure.
• Arrays are useful when storing data that needs to be accessed quickly, such as in a game or search engine.

Cons

• It could require more space to store many records.

Linked Lists

Linked Lists are a linear data structure which is organised in a sequence. Each element in the list is connected to the next one, forming a chain. 

Linked Lists are dynamic, meaning they can grow and shrink as needed. They are a great choice for storing data when you need to add or remove elements quickly, as the process is relatively simple. They also require less memory than other data structures, making them a great choice when memory is limited. Operations of a linked list include,

• Traversal
• Insertion
• Deletion
• Search 

Pros

• They are used to implement algorithms that require quick access to data, such as,
• Searching algorithms 
• Sorting algorithms
• Linked lists are dynamic and can be expanded and contracted at runtime by allocating and releasing memory.

Cons

• Memory addresses cannot access a linked list's elements directly. 
• Linked lists are not capable of random access due to their dynamic memory allocation.

Trees 

Trees are a type of data structure that stores data hierarchically. They are great for storing data when searching for data quickly. They are used in many applications, such as,

• Databases
• Search engines
• Operating systems

Trees are composed of nodes, which store the required individual data. Each node can have one or more child nodes, which are connected to it. The node that has no children is referred to as a leaf node. 

Paths are the edges that connect nodes. Subtree represents the descendants of a node. The root node is the first node in the tree. All other nodes are connected to the root node.

Pros 

• It is used in different data structures and algorithms, including 
• Decision trees
• The Huffman coding
• When new data is added or withdrawn, tree data structures can automatically self-organise, enhancing efficiency and lowering complexity.

 Cons 

• For data without hierarchical linkages, trees are not the best option.
• When trees are not balanced properly, they perform poorly and are less efficient.

Hash tables

Hash tables are a type of data structure that stores data in an associative array. Hash tables comprise key and value pairs, where each key is associated with a specific value.

Hash tables use a hashing algorithm to store and retrieve data. This hashing algorithm takes a key and generates a unique hash value. This hash value is then used to store the associated value in the hash table. 

Hash tables are often used in applications requiring fast data access, such as,

• Databases
• Caching systems
• Search engines

Pros 

• The majority of hash table implementations have self-adjusting sizes.
• On average, hash offers constant speed for,
• Searching
• Inserting
• Deleting

Cons

• Hash collisions can never be avoided for a large collection of potential keys.
• Since hash tables do not preserve the order of the components, it is challenging to get the elements in a certain order.

Stack 

A stack is a linear data structure that permits insertion and deletion operations from the top end of the stack data structure. It used the LIFO (Last-In-First-Out ) concept, where memory operations are used in a specific way. 

Stacks can be used for 

• Function calls
• Parenthesis matching
• Reversing any set of data

When introduced to the stack, a new element takes the top spot. The LIFO characteristic refers to the removal operation's priority for removing the element entered most recently into the stack. The operation of a stack is similar to a stack of books kept one over another. To remove a book from the stack, the books above it must be taken off (starting from the one at the top). 

Pros 

• Local variables are put in a stack when a function is called, and the stack is automatically removed once the function has returned.
• Stack is more dependable and safe since it is less likely to become corrupted.

Cons 

• Stack overflow can occur more frequently if too many objects are created on the stack.
• The stack will exit the memory region, which could result in an unexpected termination.

Conclusion

By understanding the different types of data structures available and how they can be used, developers can create robust applications tailored to their users' specific needs. Harnessing the power of data structures allows developers to create optimised applications for performance, usability, and scalability. 

To learn more about data structures, enrol in Skill-Lync’s Data Structures course. Talk to our experts to know more about the course!