C++ program complexity optimization: for different data structures

In C++ programming, optimizing program complexity requires selecting appropriate data structures. Different data structures have different performance characteristics: array: search O(1), insertion/deletion O(n) linked list: search O(n), insertion/deletion O(1) stack: push/pop O(1) ) Queue: enqueuing/dequeuing O(1) Collection: insert/search O(log n) Mapping: search/insert O(log n) Choosing the most appropriate structure according to specific needs can significantly improve program operation efficiency.

C++ program complexity optimization: for different data structures

In C++ programming, choose the appropriate data structure for the optimization program Complexity matters. Different data structures have different performance characteristics. Choosing the most appropriate structure according to the actual situation can significantly improve program operation efficiency.

Array

An array is a collection of elements of the same type in a contiguous block of memory. The complexity of an array is usually as follows:

• Find: O(1)
• Insert: O(n)
• Delete: O(n)

Practical case: If you need to perform frequent searches on large data sets, you can use arrays, because the complexity of the search operation is O(1).

Linked list

A linked list is a dynamic data structure in which data elements are stored in a linear manner. The complexity of a linked list is usually as follows:

• Lookup: O(n)
• Insertion: O(1)
• Delete: O(1)

Practical case: If you need to frequently insert and delete large data sets, you can use linked lists, because the complexity of these operations is O(1).

Stack

The stack is a last-in-first-out (LIFO) data structure. The complexity of the stack is usually as follows:

• Pushing the stack: O(1)
• Popping the stack: O(1)

Practical case : If you need to implement a function call recording or undo/redo function, you can use the stack, because the LIFO nature is very suitable for these scenarios.

Queue

The queue is a first-in-first-out (FIFO) data structure. The complexity of the queue is usually as follows:

• Entry: O(1)
• Departure: O(1)

Actual case : If you need to implement a message queue or task queue, you can choose to use a queue because the FIFO nature can process tasks in an orderly manner among multiple threads or processes.

Collection

A collection is a collection that does not contain duplicate elements. The complexity of the set is usually as follows:

• Insertion: O(log n)
• Search: O(log n)

Practical case :If you need to store unique values ​​in a collection and need to find and insert them quickly, you can use a collection.

Mapping

Mapping stores key-value pairs together. The complexity of mapping is usually as follows:

• Find: O(log n)
• Insert: O(log n)

Practical case : If you need to associate data to keys, and you need to access the data quickly, you can use mapping.

By understanding the complexity and characteristics of different data structures, you can choose the most appropriate data structure according to the actual situation, thereby optimizing the complexity of the program and improving operating efficiency.

The above is the detailed content of C++ program complexity optimization: for different data structures. For more information, please follow other related articles on the PHP Chinese website!