Synopsis
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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About the Author
Robin Hillyard is an associate teaching professor in the College of Engineering at Northeastern University. He has been a software innovator, developer, manager, and architect over a long career, having written his first program in 1968. Dr. Hillyard holds an undergraduate degree in engineering science from University College, Oxford, with a specialization in control engineering, and a Ph.D. in computer science from the University of Cambridge. His research focuses on sorting algorithms, genetic algorithms, anonymization, cryptography, and blockchain.
"About this title" may belong to another edition of this title.
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Paperback. Condition: New. 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. Seller Inventory # LU-9781793588845
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Paperback. Condition: new. Paperback. 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. Discover practical strategies for selecting and applying abstract data typeslist, tree, and graph structuresto tackle software challenges. The guide explores computational complexity, sorting, and order analysis, enhanced by interactive examples, review questions, and hands-on code to bridge theory with practice. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9781793588845
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