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

Performance considerations

Parallel algorithms are a cornerstone in exploiting the capabilities of multi-core processors, aiming to enhance computational efficiency and performance. However, the journey from sequential to parallel programming is not straightforward. It requires a deep understanding of the inherent complexities and trade-offs. In this section, we will explore the various facets of parallel algorithms, including their potential for performance improvement, the challenges of parallel execution, optimal data sizing for parallelism, synchronization issues, and the subtleties of balancing workloads across threads. This comprehensive overview will provide a deeper insight into the effective utilization of parallel algorithms, underlining the importance of informed decision-making and profiling in achieving optimal performance in a parallel computing environment.

Parallel algorithms present both opportunities and challenges for performance enhancement. While they offer...