Problems Solving In Data Structures And Algorithms Using C
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Problem Solving in Data Structures and Algorithms Using C#
Author: Hemant Jain
language: en
Publisher: Createspace Independent Publishing Platform
Release Date: 2016-11-14
"Problem Solving in Data Structures & Algorithms" is a series of books about the usage of Data Structures and Algorithms in computer programming. The book is easy to follow and is written for interview preparation point of view. In various books, the examples are solved in various languages like Go, C, C++, Java, C#, Python, VB, JavaScript and PHP. GitHub Repositories https: //github.com/Hemant-Jain-Author Book's Composition This book is designed for interviews so in Chapter 0, various preparation plans are proposed. Then in chapters 1, a brief introduction of the programming language and concept of recursion is explained. A number of problems based on recursion and array are explained. Then in the coming chapter, we will be looking into complexity analysis. Then we will be looking into Sorting & Searching techniques. Then will look into the various data structures and their algorithms. We will be looking into a Linked List, Stack, Queue, Trees, Heap, Hash Table and Graphs. Then we will be looking into algorithm analysis, we will be looking into Brute Force algorithms, Greedy algorithms, Divide & Conquer algorithms, Dynamic Programming, and Backtracking. In the end, we will be looking into System Design, which will give a systematic approach for solving the design problems in an Interview. Table of Contents Chapter 0: How to use this book. Chapter 1: Introduction - Programming Overview Chapter 2: Algorithms Analysis Chapter 3: Approach to solve algorithm design problems Chapter 4: Abstract Data Type Chapter 5: Searching Chapter 6: Sorting Chapter 7: Linked List Chapter 8: Stack Chapter 9: Queue Chapter 10: Tree Chapter 11: Priority Queue Chapter 12: Hash-Table Chapter 13: Graphs Chapter 14: String Algorithms Chapter 15: Algorithm Design Techniques Chapter 16: Brute Force Algorithm Chapter 17: Greedy Algorithm Chapter 18: Divide & Conquer Chapter 19: Dynamic Programming Chapter 20: Backtracking Chapter 21: Complexity Theory Chapter 22: Interview Strategy Chapter 23: System Design
Problem Solving in Data Structures and Algorithms Using Java
Author: Hemant Jain
language: en
Publisher: Createspace Independent Publishing Platform
Release Date: 2016-10-21
This book is about the usage of Data Structures and Algorithms in computer programming. Designing an efficient algorithm to solve a computer science problem is a skill of Computer programmer. This is the skill which tech companies like Google, Amazon, Microsoft, Adobe and many others are looking for in an interview. This book assumes that you are a JAVA language developer. You are not an expert in JAVA language, but you are well familiar with concepts of references, functions, lists and recursion. In the start of this book, we will be revising the JAVA language fundamentals. We will be looking into some of the problems in arrays and recursion too. Then in the coming chapter, we will be looking into complexity analysis. Then will look into the various data structures and their algorithms. We will be looking into a Linked List, Stack, Queue, Trees, Heap, Hash Table and Graphs. We will be looking into Sorting & Searching techniques. Then we will be looking into algorithm analysis, we will be looking into Brute Force algorithms, Greedy algorithms, Divide & Conquer algorithms, Dynamic Programming, Reduction, and Backtracking. In the end, we will be looking into System Design, which will give a systematic approach for solving the design problems in an Interview.
Problems Solving in Data Structures and Algorithms Using C++
DESCRIPTION The book “Problem Solving in Data Structures and Algorithms Using C++" is designed to equip readers with a solid foundation in data structures and algorithms, essential for both academic study and technical interviews. It provides a solid foundation in the field, covering essential topics such as algorithm analysis, problem-solving techniques, abstract data types, sorting, searching, linked lists, stacks, queues, trees, heaps, hash tables, graphs, string algorithms, algorithm design techniques, and complexity theory. The book presents a clear and concise explanation of each topic, supported by illustrative examples and exercises. It progresses logically, starting with fundamental concepts and gradually building upon them to explore more advanced topics. The book emphasizes problem-solving skills, offering numerous practice problems and solutions to help readers prepare for coding interviews and competitive programming challenges. Each problem is accompanied by a structured approach and step-by-step solution, enhancing the reader's ability to tackle complex algorithmic problems efficiently. By the end of the book, readers will have a strong understanding of algorithms and data structures, enabling them to design efficient and scalable solutions for a wide range of programming problems. KEY FEATURES ● Learn essential data structures like arrays, linked lists, trees, and graphs through practical coding examples for real-world application. ● Understand complex topics with step-by-step explanations and detailed diagrams, suitable for all experience levels. ● Solve interview and competitive programming problems with C++ solutions for hands-on practice. WHAT YOU WILL LEARN ● Master algorithmic techniques for sorting, searching, and recursion. ● Solve complex problems using dynamic programming and greedy algorithms. ● Optimize code performance with efficient algorithmic solutions. ● Prepare effectively for coding interviews with real-world problem sets. ● Develop strong debugging and analytical problem-solving skills. WHO THIS BOOK IS FOR This book is for computer science students, software developers, and anyone preparing for coding interviews. The book's clear explanations and practical examples make it accessible to both beginners and experienced programmers. TABLE OF CONTENTS 1. Algorithm Analysis 2. Approach for Solving Problems 3. Abstract Data Type 4. Sorting 5. Searching 6. Linked List 7. Stack 8. Queue 9. Tree 10. Priority Queue / Heaps 11. Hash Table 12. Graphs 13. String Algorithms 14. Algorithm Design Techniques 15. Brute Force Algorithm 16. Greedy Algorithm 17. Divide and Conquer 18. Dynamic Programming 19. Backtracking 20. Complexity Theory Appendix A