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

Specific container concerns

Different STL container types present unique challenges and considerations in a multi-threaded environment. The thread safety of operations on these containers is not inherently guaranteed, making their use in concurrent scenarios a matter of careful planning. For instance, containers such as std::vector or std::map might behave unpredictably when simultaneously accessed or modified from multiple threads, leading to data corruption or race conditions. In contrast, containers such as std::atomic are designed for safe concurrent operations on individual elements, but they don’t safeguard the container’s structure as a whole. Therefore, understanding the specific threading implications of each STL container type is essential. Developers must implement appropriate locking mechanisms or use thread-safe variants where necessary to ensure data integrity and correct program behavior in a multi-threaded environment.

Behaviors of std::vector in multi...