🧩 C++ STL & Data Structures – Master Vectors, Maps, Iterators & Algorithms

The Standard Template Library (STL) in C++ offers a rich set of data structures and algorithms, designed for performance, reusability, and type safety. With containers, iterators, adapters, and algorithms, STL simplifies complex data manipulation tasks in modern C++ programming.

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🧲 Introduction – Why Learn STL & Data Structures in C++?

STL gives C++ developers a toolbox of predefined data structures and powerful algorithms, helping you write cleaner, faster, and more maintainable code. Understanding how to use STL containers like vectors, sets, maps, and their adapters is crucial for developing real-world applications efficiently.

🎯 In this guide, you’ll explore:

• Core STL components – containers, iterators, and algorithms
• Usage of STL data structures like vector, stack, map, etc.
• Practical applications and advantages of each structure
• How iterators and algorithms work across containers

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📘 Topics Covered

Subtopic	Description
📘 C++ STL Overview	What STL includes: containers, iterators, algorithms, and functors
📦 C++ Vectors	Dynamic arrays with fast access and resizing
📜 C++ Lists	Doubly linked list with efficient insert/delete
🧱 C++ Stacks	LIFO data structure using container adapters
🛠️ C++ Queues	FIFO structure for sequential processing
📚 C++ Deques	Double-ended queue with fast access from both ends
📁 C++ Sets	Stores unique, sorted elements
🗂️ C++ Maps	Key-value pairs stored in sorted order
🔄 C++ unordered_multiset	Stores duplicates using hash table
🔁 C++ Iterators	Navigates through elements in containers
🔍 C++ Algorithms	Built-in functions for sorting, searching, modifying
🧰 C++ STL Containers & Adapters	Difference between core containers and access-restricted adapters

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📘 C++ STL Overview

The STL is divided into four primary components:

• Containers: Data holders like vector, list, set, map
• Iterators: Abstracts pointer-like access to containers
• Algorithms: Functions like sort(), find(), count()
• Function Objects (Functors): Custom behaviors passed to algorithms

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📦 C++ Vectors

std::vector is a dynamic array that automatically resizes itself.

#include <vector>
#include <iostream>
using namespace std;

int main() {
    vector<int> nums = {1, 2, 3};
    nums.push_back(4);
    cout << nums[2]; // Output: 3
}

✅ Key Benefits:

• Fast random access
• Efficient appending with push_back()
• Contiguous memory layout

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📜 C++ Lists

std::list is a doubly linked list that supports fast insertions/removals.

#include <list>
#include <iostream>
using namespace std;

int main() {
    list<int> lst = {10, 20, 30};
    lst.push_front(5);
    lst.remove(20);
}

✅ When to Use:

• When frequent insertions/deletions are needed
• Random access is not a priority

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🧱 C++ Stacks

std::stack is a LIFO container adapter built on top of deque.

#include <stack>
stack<int> s;
s.push(1); s.push(2); s.pop();

✅ Use Case:

• Parsing expressions
• Undo mechanisms
• Backtracking

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🛠️ C++ Queues

std::queue is a FIFO adapter using deque by default.

#include <queue>
queue<int> q;
q.push(10); q.pop();

✅ Use Case:

• Task scheduling
• Buffers
• Breadth-First Search (BFS)

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📚 C++ Deques

std::deque is a double-ended queue for efficient insertions/removals at both ends.

#include <deque>
deque<int> d;
d.push_front(1);
d.push_back(2);

✅ Hybrid Performance:

• Similar to vector and list
• Useful for queues/stacks where both ends are active

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📁 C++ Sets

std::set stores unique elements in sorted order (internally uses balanced BST).

#include <set>
set<int> s = {3, 1, 4};
s.insert(2);

✅ Automatic sorting and uniqueness guarantee

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🗂️ C++ Maps

std::map stores key-value pairs in sorted order by key.

#include <map>
map<string, int> m;
m["Alice"] = 25;

✅ Associative Access:

• Fast lookup
• Ordered keys
• Unique keys only

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🔄 C++ unordered_multiset

std::unordered_multiset allows duplicates and stores elements using hashing.

#include <unordered_multiset>
unordered_multiset<int> us = {1, 2, 2, 3};

✅ Faster average access time than set, allows duplicates

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🔁 C++ Iterators

Iterators act like smart pointers to access container elements.

vector<int> v = {1, 2, 3};
for (vector<int>::iterator it = v.begin(); it != v.end(); ++it)
    cout << *it << " ";

✅ Types include:

• begin(), end()
• rbegin(), rend()
• const_iterator, reverse_iterator

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🔍 C++ Algorithms

STL provides powerful generic functions.

#include <algorithm>
vector<int> v = {3, 1, 4};
sort(v.begin(), v.end());   // Sort in ascending order
find(v.begin(), v.end(), 3); // Find element

✅ Popular algorithms:

• sort(), find(), reverse(), count(), binary_search()
• Work with any container that supports iterators

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🧰 C++ STL Containers & Adapters

🔹 Containers:

• vector, list, set, map, deque – direct data structures

🔹 Adapters:

• stack, queue, priority_queue – restrict access to mimic specific behaviors

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📌 Summary – Recap & Next Steps

C++ STL gives you a professional-grade toolkit for working with data structures and algorithms. Mastering it enables writing faster, cleaner, and safer code with minimal effort.

🔍 Key Takeaways:

• STL includes containers, iterators, adapters, and algorithms
• Choose containers based on access and insertion needs
• Use iterators to abstract container navigation
• STL algorithms save time and reduce manual coding

⚙️ Real-World Relevance:

• Used in competitive programming, simulations, data analysis, and all performance-critical software

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❓ Frequently Asked Questions (FAQs)

❓ What is the difference between vector and deque in C++?

✅ vector is efficient for random access and end insertions, while deque allows efficient insertions/removals at both ends.

❓ Can I store duplicate elements in a set?

✅ No. Use multiset or unordered_multiset if duplicates are needed.

❓ What is an adapter in STL?

✅ Adapters like stack or queue wrap existing containers and restrict how elements are accessed.

❓ What’s the benefit of using STL algorithms?

✅ They are well-tested, optimized, and reduce the need to write repetitive code for common tasks.

❓ Are STL containers thread-safe?

✅ No. STL containers are not thread-safe by default. Use synchronization mechanisms when used across threads.

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