Book Image

The Complete Coding Interview Guide in Java

By : Anghel Leonard
Book Image

The Complete Coding Interview Guide in Java

By: Anghel Leonard

Overview of this book

Java is one of the most sought-after programming languages in the job market, but cracking the coding interview in this challenging economy might not be easy. This comprehensive guide will help you to tackle various challenges faced in a coding job interview and avoid common interview mistakes, and will ultimately guide you toward landing your job as a Java developer. This book contains two crucial elements of coding interviews - a brief section that will take you through non-technical interview questions, while the more comprehensive part covers over 200 coding interview problems along with their hands-on solutions. This book will help you to develop skills in data structures and algorithms, which technical interviewers look for in a candidate, by solving various problems based on these topics covering a wide range of concepts such as arrays, strings, maps, linked lists, sorting, and searching. You'll find out how to approach a coding interview problem in a structured way that produces faster results. Toward the final chapters, you'll learn to solve tricky questions about concurrency, functional programming, and system scalability. By the end of this book, you'll have learned how to solve Java coding problems commonly used in interviews, and will have developed the confidence to secure your Java-centric dream job.
Table of Contents (25 chapters)
1
Section 1: The Non-Technical Part of an Interview
7
Section 2: Concepts
12
Section 3: Algorithms and Data Structures
19
Section 4: Bonus – Concurrency and Functional Programming

The best case, worst case, and expected case

If we simplify things, then we can think of the efficiency of our algorithms in terms of best case, worst case, and expected case. The best case is when the input of our algorithms meets some extraordinary conditions that allow it to perform the best. The worst case is at the other extreme, where the input is in an unfavorable shape that makes our algorithm reveal its worst performances. Commonly, however, these amazing or terrible situations won't happen. So, we introduce the expected performance.

Most of the time, we care about the worst and expected cases, which, in the case of most algorithms, are usually the same. The best case is an idealistic performance, and so it remains idealistic. Mainly, for almost any algorithm, we can find a special input that will lead to the O(1) best-case performance.

For more details about Big O, I strongly recommended you read the Big O cheat sheet (https://www.bigocheatsheet.com/).

Now,...