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Grokking Data Structures
Don’t be perplexed by data structures! This fun, friendly, and fully illustrated guide makes it easy to learn useful data structures you'll put to work every day. Grokking Data Structures makes it a breeze to learn the most useful day-to-day data structures. You'll follow a steady learning path from absolute basics to advanced concepts, all illustrated with fun examples, engaging industry stories, and hundreds of graphics and cartoons. In Grokking Data Structures you'll learn how to: Understand the most important and widely used data structuresIdentify use cases where data structures make the biggest differencePick the best data structure solution for a coding challengeUnderstand the tradeoffs of data structures and avoid catastrophesImplement basic data collections like arrays, linked lists, stacks, and priority queuesUse trees and binary search trees (BSTs) to organize dataUse graphs to model relationships and learn about complex dataEfficiently search by key using hash tables and hashing functionsReason about time and memory requirements of operations on data structures Grokking Data Structures carefully guides you from the most basic data structures like arrays or linked lists all the way to powerful structures like graphs. It’s perfect for beginners, and you won't need anything more than high school math to get started. Each data structure you encounter comes with its own complete Python implementation so you can start experimenting with what you learn right away. About the technology Data structures are vital for shaping and handling your data organization. They're also an important part of most IT job interviews! Whether you're new to data structures or just dusting off what you learned in school, this book will get you up to speed fast with no advanced math, abstract theory, or complicated proofs.
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Grokking Artificial Intelligence Algorithms
AI is primed to revolutionize the way we build applications, offering exciting new ways to solve problems, uncover insights, innovate new products, and provide better user experiences. Successful AI is based on a set of core algorithms that form a base of knowledge shared by all data scientists. Grokking Artificial Intelligence Algorithms is a fully-illustrated and interactive tutorial guide to the different approaches and algorithms that underpin AI. Written in simple language and with lots of visual references and hands-on examples, readers learn the concepts, terminology, and theory they need to effectively incorporate AI algorithms into their applications. Grokking Artificial Intelligence Algorithms uses simple language, jargon-busting explanations, and hand-drawn diagrams to open up complex algorithms. Don’t worry if you aren’t a calculus wunderkind; you’ll need only the algebra you picked up in math class. • Use cases for different AI algorithms • How to encode problems and solutions using data structures • Intelligent search for game playing • Ant colony algorithms for path finding • Evolutionary algorithms for optimization problems For software developers with high school-level algebra and calculus skills.
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Data Structures
This text is intended for the one-term course in data structures with the following prerequisites: mastery of a high-level programming language, preferably Pascal, and finite or discrete mathematics. Each basic concept is introduced first through numerous examples and followed by advanced material allowing maximum flexibility in structuring the course. Through the use of data structures, the author has included coverage of the following related topics: recursion, pattern recognition, and dynamic programming. Extensive examples, over 300 exercises, 400 figures and tables, and 80 working algorithms contribute to student learning.
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Advanced Data Structures
Advanced data structures is a core course in Computer Science which most graduate program in Computer Science, Computer Science and Engineering, and other allied engineering disciplines, offer during the first year or first semester of the curriculum. The objective of this course is to enable students to have the much-needed foundation for advanced technical skill, leading to better problem-solving in their respective disciplines. Although the course is running in almost all the technical universities for decades, major changes in the syllabus have been observed due to the recent paradigm shift of computation which is more focused on huge data and internet-based technologies. Majority of the institute has been redefined their course content of advanced data structure to fit the current need and course material heavily relies on research papers because of nonavailability of the redefined text book advanced data structure. To the best of our knowledge well-known textbook on advanced data structure provides only partial coverage of the syllabus. The book offers comprehensive coverage of the most essential topics, including: Part I details advancements on basic data structures, viz., cuckoo hashing, skip list, tango tree and Fibonacci heaps and index files. Part II details data structures of different evolving data domains like special data structures, temporal data structures, external memory data structures, distributed and streaming data structures. Part III elucidates the applications of these data structures on different areas of computer science viz, network, www, DBMS, cryptography, graphics to name a few. The concepts and techniques behind each data structure and their applications have been explained. Every chapter includes a variety of Illustrative Problems pertaining to the data structure(s) detailed, a summary of the technical content of the chapter and a list of Review Questions, to reinforce the comprehension of the concepts. The book could be used both as an introductory or an advanced-level textbook for the advanced undergraduate, graduate and research programmes which offer advanced data structures as a core or an elective course. While the book is primarily meant to serve as a course material for use in the classroom, it could be used as a starting point for the beginner researcher of a specific domain.
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Data structures based on non-linear relations and data processing methods
The systematic description starts with basic theory and applications of different kinds of data structures, including storage structures and models. It also explores on data processing methods such as sorting, index and search technologies. Due to its numerous exercises the book is a helpful reference for graduate students, lecturers.
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Guide to Data Structures
This accessible and engaging textbook/guide provides a concise introduction to data structures and associated algorithms. Emphasis is placed on the fundamentals of data structures, enabling the reader to quickly learn the key concepts, and providing a strong foundation for later studies of more complex topics. The coverage includes discussions on stacks, queues, lists, (using both arrays and links), sorting, and elementary binary trees, heaps, and hashing. This content is also a natural continuation from the material provided in the separate Springer title Guide to Java by the same authors.Topics and features: reviews the preliminary concepts, and introduces stacks and queues using arrays, along with a discussion of array-based lists; examines linked lists, the implementation of stacks and queues using references, binary trees, a range of varied sorting techniques, heaps, and hashing; presents both primitive and generic data types in each chapter, and makes use of contour diagrams to illustrate object-oriented concepts; includes chapter summaries, and asks the reader questions to help them interact with the material; contains numerous examples and illustrations, and one or more complete program in every chapter; provides exercises at the end of each chapter, as well as solutions to selected exercises, and a glossary of important terms.This clearly-written work is an ideal classroom text for a second semester course in programming using the Java programming language, in preparation for a subsequent advanced course in data structures and algorithms. The book is also eminently suitable as a self-study guide in either academe or industry.
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Data structures based on linear relations
Data structures is a key course for computer science and related majors. This book presents a variety of practical or engineering cases and derives abstract concepts from concrete problems. Besides basic concepts and analysis methods, it introduces basic data types such as sequential list, tree as well as graph. This book can be used as an undergraduate textbook, as a training textbook or a self-study textbook for engineers.
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Basic Concepts in Data Structures
Data structures are the fundamental building blocks of any computer program, used for storing, representing and manipulating data in a computer. This text presents the basic concepts of data structures as part of the art of writing computer programs. The author concentrates on the fundamentals of what should be done to solve a problem efficiently rather than technical implementation details. The text includes pseudocode and covers all the most common data structures, such as queues, stacks, trees, heaps, and hash tables, along with the basics of searching, sorting, and coding. This book can supplement any undergraduate algorithms or discrete math course and will also be accessible to students and researchers in other quantitative disciplines. No prerequisites beyond introductory programming and basic mathematics are required, and the accessible, conceptual presentation will appeal to undergraduates in many quantitative fields. Carefully designed problem sets with selected solutions will allow students to test their understanding.
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Learn Data Structures and Algorithms with Golang
Explore Golang's data structures and algorithms to design, implement, and analyze code in the professional settingKey FeaturesLearn the basics of data structures and algorithms and implement them efficientlyUse data structures such as arrays, stacks, trees, lists and graphs in real-world scenariosCompare the complexity of different algorithms and data structures for improved code performanceBook DescriptionGolang is one of the fastest growing programming languages in the software industry. Its speed, simplicity, and reliability make it the perfect choice for building robust applications. This brings the need to have a solid foundation in data structures and algorithms with Go so as to build scalable applications. Complete with hands-on tutorials, this book will guide you in using the best data structures and algorithms for problem solving.The book begins with an introduction to Go data structures and algorithms. You'll learn how to store data using linked lists, arrays, stacks, and queues. Moving ahead, you'll discover how to implement sorting and searching algorithms, followed by binary search trees. This book will also help you improve the performance of your applications by stringing data types and implementing hash structures in algorithm design. Finally, you'll be able to apply traditional data structures to solve real-world problems.By the end of the book, you'll have become adept at implementing classic data structures and algorithms in Go, propelling you to become a confident Go programmer.What you will learnImprove application performance using the most suitable data structure and algorithmExplore the wide range of classic algorithms such as recursion and hashing algorithmsWork with algorithms such as garbage collection for efficient memory management Analyze the cost and benefit trade-off to identify algorithms and data structures for problem solvingExplore techniques for writing pseudocode algorithm and ace whiteboard coding in interviewsDiscover the pitfalls in selecting data structures and algorithms by predicting their speed and efficiencyWho this book is forThis book is for developers who want to understand how to select the best data structures and algorithms that will help solve coding problems. Basic Go programming experience will be an added advantage.
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Textbook of Data Structures and Algorithms, Volume 1
Data structures and algorithms is a fundamental course in Computer Science, which enables learners across any discipline to develop the much-needed foundation of efficient programming, leading to better problem solving in their respective disciplines. A Textbook of Data Structures and Algorithms is a textbook that can be used as course material in classrooms, or as self-learning material. The book targets novice learners aspiring to acquire advanced knowledge of the topic. Therefore, the content of the book has been pragmatically structured across three volumes and kept comprehensive enough to help them in their progression from novice to expert. With this in mind, the book details concepts, techniques and applications pertaining to data structures and algorithms, independent of any programming language. It includes 181 illustrative problems and 276 review questions to reinforce a theoretical understanding and presents a suggestive list of 108 programming assignments to aid in the implementation of the methods covered.
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Data Structure Programming
This textbook provides an introduction to data structures and the Standard Template Library (STL), which has been recently accepted by the C++ Standards Committee. It provides a carefully integrated discussion of general data structures together with their implementation and use in the STL, thus teaching readers the important features of abstraction whilst using the STL to develop applications.
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Hands-On Data Structures and Algorithms with Python
Learn to implement complex data structures and algorithms using PythonKey FeaturesUnderstand the analysis and design of fundamental Python data structuresExplore advanced Python concepts such as Big O notation and dynamic programmingLearn functional and reactive implementations of traditional data structuresBook DescriptionData structures allow you to store and organize data efficiently. They are critical to any problem, provide a complete solution, and act like reusable code. Hands-On Data Structures and Algorithms with Python teaches you the essential Python data structures and the most common algorithms for building easy and maintainable applications.This book helps you to understand the power of linked lists, double linked lists, and circular linked lists. You will learn to create complex data structures, such as graphs, stacks, and queues. As you make your way through the chapters, you will explore the application of binary searches and binary search trees, along with learning common techniques and structures used in tasks such as preprocessing, modeling, and transforming data. In the concluding chapters, you will get to grips with organizing your code in a manageable, consistent, and extendable way. You will also study how to bubble sort, selection sort, insertion sort, and merge sort algorithms in detail.By the end of the book, you will have learned how to build components that are easy to understand, debug, and use in different applications. You will get insights into Python implementation of all the important and relevant algorithms.What you will learnUnderstand object representation, attribute binding, and data encapsulationGain a solid understanding of Python data structures using algorithmsStudy algorithms using examples with pictorial representationLearn complex algorithms through easy explanation, implementing PythonBuild sophisticated and efficient data applications in PythonUnderstand common programming algorithms used in Python data scienceWrite efficient and robust code in Python 3.7Who this book is forThis book is for developers who want to learn data structures and algorithms in Python to write complex and flexible programs. Basic Python programming knowledge is expected.
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Textbook of Data Structures and Algorithms, Volume 3
Data structures and algorithms is a fundamental course in Computer Science, which enables learners across any discipline to develop the much-needed foundation of efficient programming, leading to better problem solving in their respective disciplines. A Textbook of Data Structures and Algorithms is a textbook that can be used as course material in classrooms, or as self-learning material. The book targets novice learners aspiring to acquire advanced knowledge of the topic. Therefore, the content of the book has been pragmatically structured across three volumes and kept comprehensive enough to help them in their progression from novice to expert. With this in mind, the book details concepts, techniques and applications pertaining to data structures and algorithms, independent of any programming language. It includes 181 illustrative problems and 276 review questions to reinforce a theoretical understanding and presents a suggestive list of 108 programming assignments to aid in the implementation of the methods covered.
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Textbook of Data Structures and Algorithms, Volume 2
Data structures and algorithms is a fundamental course in Computer Science, which enables learners across any discipline to develop the much-needed foundation of efficient programming, leading to better problem solving in their respective disciplines. A Textbook of Data Structures and Algorithms is a textbook that can be used as course material in classrooms, or as self-learning material. The book targets novice learners aspiring to acquire advanced knowledge of the topic. Therefore, the content of the book has been pragmatically structured across three volumes and kept comprehensive enough to help them in their progression from novice to expert. With this in mind, the book details concepts, techniques and applications pertaining to data structures and algorithms, independent of any programming language. It includes 181 illustrative problems and 276 review questions to reinforce a theoretical understanding and presents a suggestive list of 108 programming assignments to aid in the implementation of the methods covered.
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Hands-On Data Structures and Algorithms with Kotlin
Understand and solve complex computational problems and write efficient code with KotlinKey FeaturesLearn about important data structures such as lists, arrays, queues, and stacksDesign custom algorithms for real-life implementationsIdentify suitable tools for different scenarios and deliver immediate resultsBook DescriptionData 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.What you will learnUnderstand the basic principles of algorithms and data structuresExplore general-purpose data structures with arrays and linked listsGet to grips with the basics of stacks, queues, and double-ended queuesUnderstand functional programming and related data structuresUse performant searching and efficient sortingUncover how Kotlin's collection framework functionsBecome adept at implementing different types of mapsWho this book is forIf you're a Kotlin developer who wants to learn the intricacies of implementing data structures and algorithms for scalable application development, this book is for you.
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C++ Data Structures and Algorithm Design Principles
Get started with C++ programming by learning how to build applications using its data structures and algorithmsKey FeaturesExplore data structures such as arrays, stacks, and graphs with real-world examplesStudy the trade-offs between algorithms and data structures and discover what works and what doesn'tDiscover how techniques such as bloom filters and multi-way heaps boost real-world applicationsBook DescriptionC++ 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.What you will learnBuild applications using hash tables, dictionaries, and setsExplore how modern hardware affects the actual run-time performance of programsApply common algorithms such as heapsort and merge sort for string data typesUse C++ template metaprogramming to write code librariesImplement a URL shortening service using a bloom filterUse appropriate modern C++ idioms such as std:: array instead of C-style arraysWho this book is forThis book is for developers or students who want to revisit basic data structures and algorithm design techniques. Although no mathematical background is required, basic knowledge of complexity classes and Big O notation along with a qualification in an algorithms course will help you get the most out of this book. Familiarity with C++ 14 standard is assumed.
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Data Structures for Engineers and Scientists Using Python
The text covers the fundamentals of Python programming and the implementation of data structures using Python programming with the help of worked-out examples. It provides a learning tool for engineers as well as for researchers and scientists of advanced level. The text further discusses important concepts such as polynomial manipulation, sparse matrices, implementation of stack using the queue model and topological sorting.This book:Discusses the implementation of various data structures such as an array, stack, queue, tree and graph along with sorting and searching algorithms. Includes programming tips to highlight important concepts and help readers avoid common programming errors. Presents each concept of data structure with a different approach and implements the same using Python programming. Offers rich chapter-end pedagogy including objective-type questions (with answers), review questions and programming exercises to facilitate review. Covers fundamentals of Python up to object-oriented concepts including regular expression. It is primarily written for senior undergraduate, graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering and information technology.
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Basic Concepts in Data Structures
Data structures are the fundamental building blocks of any computer program, used for storing, representing and manipulating data in a computer. This text presents the basic concepts of data structures as part of the art of writing computer programs. The author concentrates on the fundamentals of what should be done to solve a problem efficiently rather than technical implementation details. The text includes pseudocode and covers all the most common data structures, such as queues, stacks, trees, heaps, and hash tables, along with the basics of searching, sorting, and coding. This book can supplement any undergraduate algorithms or discrete math course and will also be accessible to students and researchers in other quantitative disciplines. No prerequisites beyond introductory programming and basic mathematics are required, and the accessible, conceptual presentation will appeal to undergraduates in many quantitative fields. Carefully designed problem sets with selected solutions will allow students to test their understanding.
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Data Structures using C
The data structure is a set of specially organized data elements and functions, which are defined to store, retrieve, remove and search for individual data elements. Data Structures using C: A Practical Approach for Beginners covers all issues related to the amount of storage needed, the amount of time required to process the data, data representation of the primary memory and operations carried out with such data. Data Structures using C: A Practical Approach for Beginners book will help students learn data structure and algorithms in a focused way. Resolves linear and nonlinear data structures in C language using the algorithm, diagrammatically and its time and space complexity analysis Covers interview questions and MCQs on all topics of campus readiness Identifies possible solutions to each problem Includes real-life and computational applications of linear and nonlinear data structuresThis book is primarily aimed at undergraduates and graduates of computer science and information technology. Students of all engineering disciplines will also find this book useful.
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Hands-On Data Structures and Algorithms with Python
Understand how implementing different data structures and algorithms intelligently can make your Python code and applications more maintainable and efficientKey FeaturesExplore functional and reactive implementations of traditional and advanced data structuresApply a diverse range of algorithms in your Python codeImplement the skills you have learned to maximize the performance of your applicationsBook DescriptionChoosing the right data structure is pivotal to optimizing the performance and scalability of applications. This new edition of Hands-On Data Structures and Algorithms with Python will expand your understanding of key structures, including stacks, queues, and lists, and also show you how to apply priority queues and heaps in applications. You'll learn how to analyze and compare Python algorithms, and understand which algorithms should be used for a problem based on running time and computational complexity. You will also become confident organizing your code in a manageable, consistent, and scalable way, which will boost your productivity as a Python developer.By the end of this Python book, you'll be able to manipulate the most important data structures and algorithms to more efficiently store, organize, and access data in your applications.What you will learnUnderstand common data structures and algorithms using examples, diagrams, and exercisesExplore how more complex structures, such as priority queues and heaps, can benefit your codeImplement searching, sorting, and selection algorithms on number and string sequencesBecome confident with key string-matching algorithmsUnderstand algorithmic paradigms and apply dynamic programming techniquesUse asymptotic notation to analyze algorithm performance with regard to time and space complexitiesWrite powerful, robust code using the latest features of PythonWho this book is forThis book is for developers and programmers who are interested in learning about data structures and algorithms in Python to write complex, flexible programs. Basic Python programming knowledge is expected.
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Advanced Data Structures
This text closely examines ideas, analysis, and implementation details of data structures as a specialised topic in applied algorithms. It looks at efficient ways to realise query and update operations on sets of numbers, intervals, or strings by various data structures, including: search trees; structures for sets of intervals or piece-wise constant functions; orthogonal range search structures; heaps; union-find structures; dynamization and persistence of structures; structures for strings; and hash tables. Instead of relegating data structures to trivial material used to illustrate object-oriented programming methodology, this is the first volume to show data structures as a crucial algorithmic topic. Numerous code examples in C and more than 500 references make Advanced Data Structures an indispensable text.
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Data Structures in Depth Using C++
Understand and implement data structures and bridge the gap between theory and application. This book covers a wide range of data structures, from basic arrays and linked lists to advanced trees and graphs, providing readers with in-depth insights into their implementation and optimization in C++.You’ll explore crucial topics to optimize performance and enhance their careers in software development. In today's environment of growing complexity and problem scale, a profound grasp of C++ data structures, including efficient data handling and storage, is more relevant than ever. This book introduces fundamental principles of data structures and design, progressing to essential concepts for high-performance application.Finally, you’ll explore the application of data structures in real-world scenarios, including case studies and use in machine learning and big data. This practical, step-by-step approach, featuring numerous code examples, performance analysis and best practices, is written with a wide range of C++ programmers in mind. So, if you’re looking to solve complex data structure problems using C++, this book is your complete guide.What You Will LearnWrite robust and efficient C++ code.Apply data structures in real-world scenarios.Transition from basic to advanced data structuresUnderstand best practices and performance analysis.Design a flexible and efficient data structure library.Who This Book is For Software developers and engineers seeking to deepen their knowledge of data structures and enhanced coding efficiency, and ideal for those with a foundational understanding of C++ syntax. Secondary audiences include entry-level programmers seeking deeper dive into data structures, enhancing their skills, and preparing them for more advanced programming tasks. Finally, computer science students or programmers aiming to transition to C++ may find value in this book.
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C++ Data Structures: A Laboratory Course
C++ Data Structures: A Laboratory Course exemplifies the active learning experience. With a dynamic learn-by-doing focus, this laboratory manual encourages students to explore data structures by implementing them, a process through which students discover how data structures work and how they can be applied. Providing a framework that offers feedback and support, this text challenges students to exercise their creativity in both programming and analysis. Topics covered include: Text ADT, BlogEntry ADT, Stack ADT, Heap ADT, Weighted Graph ADT, and much more!
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Quick Data Structures
If you want to upgrade your programming skills, the most important thing you need is a solid understanding of fundamental data structures. The proper choice of data structures distinguishes excellent programmers from merely competent ones.As an experienced programmer, you use data structures—at least arrays—all the time. However, you may not be familiar with hash tables, trees and binary trees, priority queues, directed and undirected graphs, and other data structures at your disposal.A good choice of data structures will simplify your job, not complicate it. Your code will be not only faster but also easier to understand and debug. There is no downside to using the right data structures for the job.This book Provides an understanding of the fundamental building blocks of data structures Describes the construction and use of all common data structures Explains the simple math required for selecting efficient data structures Equips you with everything you need to choose data structures or devise appropriate new ones
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Data Structures, Algorithms, and Invariants
Data Structures, Algorithms, and Invariants: A Practical Guide provides students with the knowledge and understanding they need to make sensible decisions regarding the choice of an abstract data type (ADT) for particular use cases. The book is a practical guide that helps readers with the process of building a software application utilizing a variety of list-based, tree-based, and graph-based ADTs.The opening chapters discuss solving problems, the concept of computational complexity, different types of ADTs, and why they are needed in software development. Additional chapters address unordered, positional, and ordered ADTs, the process of sorting, ways of determining order, and graphs. Each chapter features an introduction, learning objectives, key terms, takeaways, QR codes that link out to additional content such as videos, and chapter review questions to support the reading and learning experience. Additionally, students gain access to a companion source code repository that provides implementations of many of the ADTs.Data Structures, Algorithms, and Invariants is an ideal textbook for data structure and algorithms courses in information science, data science, and programming.
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Grokking Simplicity
Distributed across servers, difficult to test, and resistant to modification—modern software is complex. Grokking Simplicity is a friendly, practical guide that will change the way you approach software design and development. It introduces a unique approach to functional programming that explains why certain features of software are prone to complexity, and teaches you the functional techniques you can use to simplify these systems so that they’re easier to test and debug. Available in PDF (ePub, kindle, and liveBook formats coming soon). about the technologyEven experienced developers struggle with software systems that sprawl across distributed servers and APIs, are filled with redundant code, and are difficult to reliably test and modify. Adopting ways of thinking derived from functional programming can help you design and refactor your codebase in ways that reduce complexity, rather than encouraging it. Grokking Simplicity lays out how to use functional programming in a professional environment to write a codebase that’s easier to test and reuse, has fewer bugs, and is better at handling the asynchronous nature of distributed systems. about the bookIn Grokking Simplicity, you’ll learn techniques and, more importantly, a mindset that will help you tackle common problems that arise when software gets complex. Veteran functional programmer Eric Normand guides you to a crystal-clear understanding of why certain features of modern software are so prone to complexity and introduces you to the functional techniques you can use to simplify these systems so that they’re easier to read, test, and debug. Through hands-on examples, exercises, and numerous self-assessments, you’ll learn to organize your code for maximum reusability and internalize methods to keep unwanted complexity out of your codebase. Regardless of the language you’re using, the ways of thinking in this book will help recognize problematic code and tame even the most complex software. what's inside Apply functional programming principles to reduce codebase complexityWork with data transformation pipelines for code that’s easier to test and reuseTools for modeling time to simplify asynchrony60 exercises and 100 questions to test your knowledge about the readerFor experienced programmers. Examples are in JavaScript. about the author Eric Normand has been a functional programmer since 2001 and has been teaching functional programming online and in person since 2007. Visit LispCast.com to see more of his credentials.
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Purely Functional Data Structures
Most books on data structures assume an imperative language like C or C++. However, data structures for these languages do not always translate well to functional languages such as Standard ML, Haskell, or Scheme. This book describes data structures from the point of view of functional languages, with examples, and presents design techniques so that programmers can develop their own functional data structures. It includes both classical data structures, such as red-black trees and binomial queues, and a host of new data structures developed exclusively for functional languages. All source code is given in Standard ML and Haskell, and most of the programs can easily be adapted to other functional languages. This handy reference for professional programmers working with functional languages can also be used as a tutorial or for self-study.
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