Table of Contents
The Standard Template Library (STL) is a flexible and powerful C++ library consisting of generic data structures and algorithms. It provides reusable software components to simplify programming and enable faster development of complex, high-performance applications.
What is STL?
Put simply, STL is a collection of C++ template classes broadly grouped into the following three categories:
- Containers: Storage classes including vectors, lists, dequeues, sets, multisets and maps.
- Algorithms: Functions that act on containers like searching, sorting, merging, transforming elements.
- Iterators: Objects that point to container elements, used to step through them.
The key benefit of this collection is code reuse and interoperability. STL algorithms can work across multiple containers through iterators. Developers can mix-and-match components as per application needs instead of writing low-level data structures from scratch.
Evolution of STL
STL traces its roots to the pioneering work of computer scientist Alexander Stepanov in the 1970s on generic programming. In the 1990s, he collaborated with Meng Lee to develop early versions of STL coded in C++.
The first commercial implementation of STL was in Hewlett-Packard‘s implementation of C++, followed by Silicon Graphics. In 1994, STL was incorporated into the draft C++ standard, becoming an integral part of standard C++.
Over the years, STL has grown in popularity among C++ users due to its flexibility. Additional containers like deque, string and bitset were added by the C++ standards committee. The TR1 (Technical Report 1) in 2005 added shared pointers, hash tables, regular expressions and more to the library.
C++11 in 2011 introduced multi-threading support through atomic operations and mutexes. Abseil library by Google is an open-sourced extension of STL with more tools. The library continues to evolve with newer C++ standards.
STL Containers
STL supports several template container classes for managing collections of objects. Let‘s look at some popular sequential containers:
Vector
The vector acts like a dynamic array that can grow and shrink automatically. Insertions/deletions at end are fast while middle insertions are costlier.
vector<int> nums {1, 3, 5}; //Create vector
nums.push_back(2); //Insert at end
nums.size(); //Get current size
nums.at(2) = 4; //Access & modify element Deque
The deque (double-ended queue) allows fast inserts/deletes at both the start and the end. But middle inserts are slower.
deque<string> words {"hello", "world"};
words.push_front("goodbye"); //Insert at start
words.push_back("STL"); //Insert at end List
The list is implemented as a doubly linked list. Insertions and deletions are fast even in the middle – but search is slower.
list<int> nums {2, 8};
nums.sort(); //Sort linked list
nums.reverse(); //Reverse linked listThere are also useful associative containers like maps, sets, multisets that store key-value pairs in specific sorted orders to allow faster lookups.
STL Algorithms
STL algorithms provide reusable functions that work on container elements through iterators. For example:
vector<int> points {10, -3, 25, 16};
sort(points.begin(), points.end()); //Sort vector
find(points.begin(), points.end(), 16); //Find 16Here are some useful STL algorithms:
| Algorithm | Purpose |
|---|---|
sort |
Sort elements |
find |
Find value |
count |
Count occurrences |
reverse |
Reverse elements |
random_shuffle |
Randomly shuffle |
transform |
Apply function to elements |
And many more algorithms for tasks like searching, comparisons, permutations, partitions etc.
STL Iterators
Iterators act as bridges between containers and algorithms by allowing algorithms to access and manipulate container elements without knowing their underlying representation.
Some common iterator categories are:
- Input iterators: Read-only forward iteration
- Output iterators: Write-only iteration
- Forward iterators: Read/write multi-pass iteration
- Bidirectional: Both forward and backward iteration
- Random-access: Direct access like pointers
For example:
vector<int> points {4, 8, 3, 5};
vector<int>::iterator it; //Iterator
for(it = points.begin(); it != points.end(); ++it) {
*it *= 2; //Dereference & modify
}Iterators relieve algorithms from handling containers directly. New containers just need to provide iterators matching algorithm expectations. This makes components interoperable.
Advantages of Using STL
STL offers several benefits:
Reusability: Components can be reused across projects, reducing rewrite.
Interoperability: Mix-and-match algorithms and containers through iterators.
Efficiency: Optimized underlying implementations of templated classes.
Abstraction: Simple interfaces hide complex code underneath.
Flexibility: Components work across old and new compilers.
Concurrency: Thread-safe components allow parallelism.
This table compares efficiency of some STL containers:
| Operation/DS | Vector | Deque | List |
|---|---|---|---|
| Insert Back | Fast | Fast | Slow |
| Insert Middle | Slow | Slow | Fast |
| Search | Fast | Slow | Very Slow |
As visible, there are performance trade-offs so choose wisely!
Real-World Usage
STL is widely used across many domains due to its flexibility:
Graphics: STL data structures like kd-trees used in rendering pipelines.
Gaming: Vectors for positions, maps for character stats etc.
Database Systems: B+ tree containers for indexes, hashes for cache.
Compilers: Parsing uses STL strings, maps used for symbol tables.
Operating Systems: Kernel uses red-black trees, schedulers use heaps.
Finance Applications: Containers for order books, algorithms for analytics.
Physics Simulation: Spatial partitioning trees, random number generators.
STL enables faster development, better code organization and efficiency across complex systems.
Comparison With Other Libraries
Boost: Large peer-reviewed collection of C++ libraries for specific domains. STL offers low-level generic data structures only.
Qt: Used mainly for developing user interfaces and applications. STL focuses on core algorithm/container classes.
Abseil: Developed by Google for their internal C++ codebase. Extends STL with useful new utilities.
So while libraries like Boost build over STL, STL provides the underlying foundation.
Recent Additions
Over the years, STL has continued to evolve:
- C++11 expanded support for concurrency through atomic operations and mutexes.
- C++17 added parallel versions of algorithms like
for_eachandsort. - C++20 introduces span for handling array slices and task flow for task graphs.
- Libraries like Google Abseil extend STL with more features.
So STL continues to incorporate new utilities around emerging C++ coding styles and hardware support.
Conclusion
The Standard Template Library is an essential framework for reusable components in C++. It enables generic programming and faster development through its rich set of containers, algorithms and iterators.
STL hides complex implementations behind simple interfaces while providing flexibility and efficiency. Understanding STL helps unlock the true power of C++ for developing high-performance applications.