Introduction to Data Structures and Algorithms

What is Data?

• Data is a collection of any information.
• Example: Name (like Ankus), Age (like 23).

Data Structure

• A method to organize data in a specific format.
• Different data elements are logically and mathematically interrelated.

Linked List

• Data Part: Part to store data.
• Link Part: Stores the address of the next node.
• Example: Storing a name like Ankit in a linked list.

Purpose of Data Structure

• To enhance the functionality of a program.
• To reduce storage requirements.

Classification

• Linear and Non-linear: Data is stored in sequence or randomly.
• Homogeneous and Non-homogeneous: Storing data of the same or different types.
• Static and Dynamic: Fixed size or adjusting memory as needed.

Operations

• Searching: Finding a specific element.
• Sorting: Arranging data in an order.
• Traversing: Processing all elements.
• Inserting, Updating, Deleting: Making changes to data.
• Merging: Combining two lists.

Algorithm

• Definition: Step-by-step instructions used to solve a problem.
• Example: Algorithm to add two numbers:
  • Step 1: Start
  • Step 2: Take two numbers as input
  • Step 3: Find their sum
  • Step 4: Print the result
  • Step 5: End

Characteristics of Algorithm

• Input: An algorithm should have clear input.
• Output: There should be a clear output.
• Clarity: Each instruction should be clear.

Conclusion

• Data structures and algorithms are important for enhancing the functionality and memory utilization of a program.
• An algorithm is a step-by-step process that simplifies programming.