Enrico Pontelli, Karen Villaverde · 2004
a Domain – i.e., a collection of values a set of operations that can be applied on the values in the domain Both these components together characterize a data type. For example, if we consider the data type byte we have that • the domain contains all the integer number between-256 and +255 the set of operations includes the operations: addition, multiplication, subtraction, integer division, and modulo. In addition, we have o operations that are used to compare elements in the domain (e.g., ==,!=,>) and return a Boolean value Observe that in a data type, the only way to access and use values belonging to the domain is to make use of the operations provided by the data type. The user of the data type does not have any other way of modifying these data. Furthermore, the data type does not tell us anything about how the data are internally represented (e.g., we do not see what bit pattern is used to store a byte object) and we do not see what kind of algorithm is employed to implement each operation.
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Jeff Edmonds · Cambridge University Press eBooks · 2024
Understand algorithms and their design with this revised student-friendly textbook. Unlike other algorithms books, this one is approachable, the methods it explains are straightforward, and the insights it provides are numerous and valuable. Without grinding through lots of formal proof, students will benefit from step-by-step methods for developing algorithms, expert guidance on common pitfalls, and an appreciation of the bigger picture. Revised and updated, this second edition includes a new chapter on machine learning algorithms, and concise key concept summaries at the end of each part for quick reference. Also new to this edition are more than 150 new exercises: selected solutions are included to let students check their progress, while a full solutions manual is available online for instructors. No other text explains complex topics such as loop invariants as clearly, helping students to think abstractly and preparing them for creating their own innovative ways to solve problems.
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Gary T. Leavens · Wiley Encyclopedia of Electrical and Electronics Engineering · 1999
Abstract The sections in this article are Abstract Data Types Encapsulate Data Structures Creation and Design of ADTs Related Topics
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TIMOTHY ARNDT · Series on software engineering and knowledge engineering · 2003
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Roman E. Maeder · Elsevier eBooks · 1994
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Ласко Ласков · Scholar Electronic Repository of the New Bulgarian University (New Bulgarian University) · 2020
Formation of notion is a fundamental process in education, and for that reason it is excessively studied in both psychology and pedagogy. The application of the pedagogical techniques has a key role in education in informatics (Asenova, 1990) and has improved significantly the results in introduction of complex notions in our practice. Such complex notion is abstract data type (ADT) which is a key concept in computer programming for developing data structures, data types, and have vast influence on the algorithms applied on them. In order to introduce the notion ADT we adopt a system of tasks that develop the needed knowledge through the important data structures of linked lists, queues and stacks.
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Nell Dale · 1996
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Larry D. Pyeatt · Elsevier eBooks · 2024
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Yorick Hardy, Willi-Hans Steeb · Birkhäuser Basel eBooks · 2001
Programming languages such as C++ and Java have built in data types (so-called basic data types or primitive data types) such as integers that represent information and have operations that can be performed on them (such as multiplication and addition). For example the built in basic data types in C++ are short, int, long, float, double and char.
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Wolfgang Schreiner · Texts & monographs in symbolic computation/Texts and monographs in symbolic computation · 2021
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Larry D. Pyeatt, William Ughetta · Elsevier eBooks · 2019
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Peter J. Ashenden, Gregory D. Peterson, Darrell A. Teegarden · Elsevier eBooks · 2003
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Peter J. Ashenden · Elsevier eBooks · 2002
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Andrzej Tarlecki, Martin Wirsing · Fundamenta Informaticae · 1986
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MIGLIAVACCA M, MURPHY A. L, AND ROMAN G. et al. · Institutional Research Information System (Università degli Studi di Trento) · 2004
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Gian Pietro Picco, Matteo Migliavacca, Amy L. Murphy et al. · Lecture notes in computer science · 2006
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Pascale Champagnoux, Laurence Duchien, Daniel Enselme et al. · HAL (Le Centre pour la Communication Scientifique Directe) · 1999
14th International Workshop on Algebraic Development Techniques (WADT'99), Bonas, France, septembre 1999.
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Poigne, A., Voss, J., Dortmund Univ. (Germany). Lehrstuhl Informatik 2 · OpenGrey (Institut de l'Information Scientifique et Technique) · 1984
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Mila E. Majster · Theoretical Computer Science · 1979
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Nico Verwer · Utrecht University Repository (Utrecht University) · 1988
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