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Using C, this book develops the concepts and theory of data structures and algorithm analysis in a gradual, step-by-step manner, proceeding from concrete examples to abstract principles. Standish covers a wide range of both traditional and contemporary software engineering topics. The text also includes an introduction to object-oriented programming using C++. By introducing recurring themes such as levels of abstraction, recursion, efficiency, representation and trade-offs, the author unifies the material throughout. Mathematical foundations can be incorporated at a variety of depths, allowing the appropriate amount of math for each user.
This practical text contains fairly "traditional" coverage of data structures with a clear and complete use of algorithm analysis, and some emphasis on file processing techniques as relevant to modern programmers. It fully integrates OO programming with these topics, as part of the detailed presentation of OO programming itself.Chapter topics include lists, stacks, and queues; binary and general trees; graphs; file processing and external sorting; searching; indexing; and limits to computation.For programmers who need a good reference on data structures.
About the Book: Principles of DATA STRUCTURES using C and C++ covers all the fundamental topics to give a better understanding about the subject. The study of data structures is essential to every one who comes across with computer science. This book is written in accordance with the revised syllabus for B. Tech./B.E. (both Computer Science and Electronics branches) and MCA. students of Kerala University, MG University, Calicut University, CUSAT Cochin (deemed) University. NIT Calicut (deemed) University, Anna University, UP Technical University, Amritha Viswa (deemed) Vidyapeeth, Karunya (dee.
Algorithms are at the heart of every nontrivial computer application, and algorithmics is a modern and active area of computer science. Every computer scientist and every professional programmer should know about the basic algorithmic toolbox: structures that allow efficient organization and retrieval of data, frequently used algorithms, and basic techniques for modeling, understanding and solving algorithmic problems. This book is a concise introduction addressed to students and professionals familiar with programming and basic mathematical language. Individual chapters cover arrays and linked lists, hash tables and associative arrays, sorting and selection, priority queues, sorted sequences, graph representation, graph traversal, shortest paths, minimum spanning trees, and optimization. The algorithms are presented in a modern way, with explicitly formulated invariants, and comment on recent trends such as algorithm engineering, memory hierarchies, algorithm libraries and certifying algorithms. The authors use pictures, words and high-level pseudocode to explain the algorithms, and then they present more detail on efficient implementations using real programming languages like C++ and Java. The authors have extensive experience teaching these subjects to undergraduates and graduates, and they offer a clear presentation, with examples, pictures, informal explanations, exercises, and some linkage to the real world. Most chapters have the same basic structure: a motivation for the problem, comments on the most important applications, and then simple solutions presented as informally as possible and as formally as necessary. For the more advanced issues, this approach leads to a more mathematical treatment, including some theorems and proofs. Finally, each chapter concludes with a section on further findings, providing views on the state of research, generalizations and advanced solutions.
Most books on data structures are based on Pascal. With increased use of C, however, advanced programming techniques including dynamic data structures are found to be more practical and efficient in this language. By using the C language throughout, the author is able to discuss and demonstrate random file access in sorting programs and in programs that manipulate B-trees. The book focusses on useful applications such as storing and retrieving large amounts of data efficiently, and the critical-path method in project planning.
Lux Pascal is a modern programming language designed for high-performance parallel computing, especially in the field of scientific computing and data processing. It is an extension of Pascal language and provides a rich set of features, such as support for arrays, matrices, complex numbers, and built-in functions for mathematical operations. Lux Pascal aims to enable developers to write efficient, scalable, and maintainable code, while also providing a simple and intuitive syntax. One of the key strengths of Lux Pascal is its use of data parallelism, which allows multiple data items to be processed simultaneously. This is achieved through the use of parallel loops, which can distribute data across multiple cores or processors. Additionally, Lux Pascal provides a set of built-in functions for task parallelism, which allows developers to create multiple threads and execute them concurrently. With these features, Lux Pascal is well-suited for numerical computations, data analytics, and simulations, as well as other performance-critical applications.