Book Image

C++ Data Structures and Algorithm Design Principles

By : John Carey, Anil Achary, Shreyans Doshi, Payas Rajan
Book Image

C++ Data Structures and Algorithm Design Principles

By: John Carey, Anil Achary, Shreyans Doshi, Payas Rajan

Overview of this book

C++ is a mature multi-paradigm programming language that enables you to write high-level code with a high degree of control over the hardware. Today, significant parts of software infrastructure, including databases, browsers, multimedia frameworks, and GUI toolkits, are written in C++. This book starts by introducing C++ data structures and how to store data using linked lists, arrays, stacks, and queues. In later chapters, the book explains the basic algorithm design paradigms, such as the greedy approach and the divide-and-conquer approach, which are used to solve a large variety of computational problems. Finally, you will learn the advanced technique of dynamic programming to develop optimized implementations of several algorithms discussed in the book. By the end of this book, you will have learned how to implement standard data structures and algorithms in efficient and scalable C++ 14 code.
Table of Contents (11 chapters)


In the previous chapter, we studied some commonly used data structures. Data structures are organizations of data in different forms, and a data structure enables and controls the cost of access to the data stored inside it. However, what makes software useful is not just the ability to store and retrieve data in various formats, but the ability to make transformations on data in order to solve computational problems. For a given problem, the precise definition and order of transformations on data is determined by a sequence of instructions called an algorithm.

An algorithm takes in a set of inputs that define an instance of a problem, applies a series of transformations, and outputs a set of results. If these results are the correct solutions to the computational problem at hand, our algorithm is said to be correct. The goodness of an algorithm is determined by its efficiency, or how few instructions the algorithm needs to perform to produce correct results:

Figure 4.1: Scaling of steps taken by an algorithm with respect to the size of the input