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

Searching algorithms

The main searching algorithm that occurs in interviews as a standalone problem or part of another problem is the Binary Search algorithm. The best case time complexity is O(1), while the average and worst case is O(log n). The worst case auxiliary space complexity of Binary Search is O(1) for the iterative implementation and O(log n) for the recursive implementation due to the call stack.

The Binary Search algorithm relies on the divide and conquer strategy. Mainly, this algorithm debuts by dividing the given array into two sub-arrays. Furthermore, it discards one of these sub-arrays and operates on the other one iteratively or recursively. In other words, at each step, this algorithm halves the search space (which is initially the whole given array).

So, these algorithms describe the steps for looking for element x in an array, a. Consider a sorted array, a, that contains 16 elements, as shown in the following image:

Figure 14.8 &...