Book Image

Hands-On Data Structures and Algorithms with Kotlin

By : Chandra Sekhar Nayak, Rivu Chakraborty
Book Image

Hands-On Data Structures and Algorithms with Kotlin

By: Chandra Sekhar Nayak, Rivu Chakraborty

Overview of this book

Data structures and algorithms are more than just theoretical concepts. They help you become familiar with computational methods for solving problems and writing logical code. Equipped with this knowledge, you can write efficient programs that run faster and use less memory. Hands-On Data Structures and Algorithms with Kotlin book starts with the basics of algorithms and data structures, helping you get to grips with the fundamentals and measure complexity. You'll then move on to exploring the basics of functional programming while getting used to thinking recursively. Packed with plenty of examples along the way, this book will help you grasp each concept easily. In addition to this, you'll get a clear understanding of how the data structures in Kotlin's collection framework work internally. By the end of this book, you will be able to apply the theory of data structures and algorithms to work out real-world problems.
Table of Contents (16 chapters)
Free Chapter
1
Section 1: Getting Started with Data Structures
4
Section 2: Efficient Grouping of Data with Various Data Structures
8
Section 3: Algorithms and Efficiency
11
Section 4: Modern and Advanced Data Structures
15
Assessments

Introducing hashing

To understand hashing, let's consider a small example where you want to store details of students in a Map, where key is the student ID and value is the student object. As student IDs can be alphanumeric, the number of possible keys is infinite. Now, in order to fetch a student's details from their ID, we first need to search the IDs and then fetch the details. It takes O(n) to do the required task.

To make it faster, we can slightly change the approach by storing the entries. Instead of storing each entry individually, we can store them based on the first character of the ID. If a student has an ID that starts with a, then we store their details in the 0th index, b in the first index, c in the second index, and so on. By following this approach, we can make our Map operate 26 times faster than the earlier approach.

If we look closely, we should be...