Book Image

Hands-On Design Patterns with C++ (Second Edition) - Second Edition

By : Fedor G. Pikus
5 (1)
Book Image

Hands-On Design Patterns with C++ (Second Edition) - Second Edition

5 (1)
By: Fedor G. Pikus

Overview of this book

C++ is a general-purpose programming language designed for efficiency, performance, and flexibility. Design patterns are commonly accepted solutions to well-recognized design problems. In essence, they are a library of reusable components, only for software architecture, and not for a concrete implementation. This book helps you focus on the design patterns that naturally adapt to your needs, and on the patterns that uniquely benefit from the features of C++. Armed with the knowledge of these patterns, you’ll spend less time searching for solutions to common problems and tackle challenges with the solutions developed from experience. You’ll also explore that design patterns are a concise and efficient way to communicate, as patterns are a familiar and recognizable solution to a specific problem and can convey a considerable amount of information with a single line of code. By the end of this book, you’ll have a deep understanding of how to use design patterns to write maintainable, robust, and reusable software.
Table of Contents (26 chapters)
1
Part 1: Getting Started with C++ Features and Concepts
5
Part 2: Common C++ Idioms
10
Part 3: C++ Design Patterns
18
Part 4: Advanced C++ Design Patterns

The overhead of small memory allocations

The local buffer optimization is just that - an optimization. It is a performance-oriented pattern, and we must, therefore, keep in mind the first rule of performance - never guess anything about performance. Performance, and the effect of any optimization, must be measured.

The cost of memory allocations

Since we are exploring the overhead of memory allocations and the ways to reduce it, the first question we must answer is how expensive a memory allocation is. After all, nobody wants to optimize something so fast that it needs no optimization. We can use Google Benchmark (or any other microbenchmark, if you prefer) to answer this question. The simplest benchmark to measure the cost of memory allocation might look like this:

void BM_malloc(benchmark::State& state) {
  for (auto _ : state) {
    void* p = malloc(64);
    benchmark::DoNotOptimize(p);
  }
  state...