Book Image

Data Structures and Algorithms with the C++ STL

By : John Farrier
5 (2)
Book Image

Data Structures and Algorithms with the C++ STL

5 (2)
By: John Farrier

Overview of this book

While the Standard Template Library (STL) offers a rich set of tools for data structures and algorithms, navigating its intricacies can be daunting for intermediate C++ developers without expert guidance. This book offers a thorough exploration of the STL’s components, covering fundamental data structures, advanced algorithms, and concurrency features. Starting with an in-depth analysis of the std::vector, this book highlights its pivotal role in the STL, progressing toward building your proficiency in utilizing vectors, managing memory, and leveraging iterators. The book then advances to STL’s data structures, including sequence containers, associative containers, and unordered containers, simplifying the concepts of container adaptors and views to enhance your knowledge of modern STL programming. Shifting the focus to STL algorithms, you’ll get to grips with sorting, searching, and transformations and develop the skills to implement and modify algorithms with best practices. Advanced sections cover extending the STL with custom types and algorithms, as well as concurrency features, exception safety, and parallel algorithms. By the end of this book, you’ll have transformed into a proficient STL practitioner ready to tackle real-world challenges and build efficient and scalable C++ applications.
Table of Contents (30 chapters)
Free Chapter
1
Part 1: Mastering std::vector
7
Part 2: Understanding STL Data Structures
13
Part 3: Mastering STL Algorithms
19
Part 4: Creating STL-Compatible Types and Algorithms
23
Part 5: STL Data Structures and Algorithms: Under the Hood

Creating a custom iterator

One of the beauties of C++ is its flexibility, empowering developers to mold the language to suit their needs. This flexibility doesn’t stop with built-in functionality for container iteration. While std::vector comes with its set of built-in iterators, nothing is stopping us from creating our own. But why might we want to?

The appeal of custom iterators

Let’s examine the reasons you’d want to implement a custom iterator:

  • Enhanced abstraction: Consider a vector storing a matrix in a flat format. Wouldn’t it be more intuitive to iterate through rows or columns rather than individual elements? Custom iterators can facilitate this.
  • Data transformation: Perhaps you wish to iterate through the vector but retrieve transformed data, like the squared values of each element. Instead of changing the data before or during retrieval, a custom iterator can abstract this.
  • Filtered views: Imagine skipping over certain elements...