Where to Use a Particular STL Container?

The Standard Template Library (STL) in C++ has a variety of containers designed to store collections of data. Each container has unique characteristics and is optimized for different operations. One common question that arises is which STL container to use in a specific scenario.

In this article, we will learn about various STL containers, understand their unique features, and discuss the scenarios in which each container is most suitable.

When to Use Which STL Container?

The following flowchart illustrates which STL container should we use in a particular scenario in C++.

The STL provides several types of containers, including sequence containers, associative containers, and container adapters.

Sequence Containers in C++ STL

1. std::vector

Use std::vector when you need a dynamic array that provides fast random access and efficient insertion and deletion at the end.

For Example: Managing a list of elements where the order matters, such as a list of students in a classroom.

2. std::deque

Use std::deque when you need a dynamic array that allows efficient insertion and deletion at both the front and the back.

For Example: Implementing a double-ended queue where elements are frequently added and removed from both ends.

3. std::list

Use std::list when you need a doubly-linked list that allows efficient insertion and deletion at any position.

For Example: Managing a playlist where songs can be added or removed from any position.

Associative Containers in C++ STL

4. std::set

Use std::set when you need a sorted collection of unique elements with fast lookup, insertion, and deletion.

For Example: Storing a collection of unique words in a dictionary application.

5. std::multiset

Use std::multiset when you need a sorted collection that allows duplicate elements.

For Example: Counting occurrences of words in a text document.

6. std::map

Use std::map when you need a sorted collection of key-value pairs with unique keys and fast lookup by key.

For Example: Storing student IDs and their corresponding grades.

7. std::multimap

Use std::multimap when you need a sorted collection of key-value pairs with duplicate keys allowed.

For Example: Storing students' grades, where each student can have multiple grades.

8. std::unordered_set

Use std::unordered_set when you need a collection of unique elements with fast average-time complexity for lookup, insertion, and deletion (without sorting).

For Example: Managing a collection of unique identifiers where order does not matter.

9. std::unordered_multiset

Use std::unordered_multiset when you need a collection that allows duplicate elements with fast average-time complexity for lookup, insertion, and deletion (without sorting).

For Example: Counting occurrences of elements where order does not matter.

10. std::unordered_map

Use std::unordered_map when you need a collection of key-value pairs with unique keys and fast average-time complexity for lookup, insertion, and deletion (without sorting).

For Example: Caching results with unique keys for quick retrieval.

11. std::unordered_multimap

Use std::unordered_multimap when you need a collection of key-value pairs with duplicate keys allowed and fast average-time complexity for lookup, insertion, and deletion (without sorting).

For Example: Implementing a phone book where a person can have multiple phone numbers.

Container Adapter in C++ STL

12. std::stack

Use std::stack when you need a last-in, first-out (LIFO) data structure.

For Example: Implementing function call stacks in a program.

13. std::queue

Use std::queue when you need a first-in, first-out (FIFO) data structure.

For Example: Managing tasks in a printer queue.

14. std::priority_queue

Use std::priority_queue when you need a priority-based queue where elements are ordered by priority.

For Example: Scheduling tasks based on their priority levels.

Conclusion

Choosing the right STL container depends on the specific requirements of our application, such as the need for fast access, insertion, deletion, or sorting. By understanding the unique features and optimal scenarios for each container, you can make informed decisions that lead to more efficient and maintainable code.