Mathematical Foundations of Advanced Informatics [electronic resource] : Volume 1: Inductive Approaches / by Bernhard Steffen, Oliver Rüthing, Michael Huth.
Tipo de material: TextoEditor: Cham : Springer International Publishing : Imprint: Springer, 2018Edición: 1st ed. 2018Descripción: XXVII, 228 p. 29 illus., 7 illus. in color. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783319683973Tema(s): Computer science-Mathematics | Computers | Computer mathematics | Software engineering | Mathematics of Computing | Theory of Computation | Mathematical Applications in Computer Science | Software Engineering/Programming and Operating SystemsFormatos físicos adicionales: Printed edition:: Sin título; Printed edition:: Sin título; Printed edition:: Sin títuloClasificación CDD: 004.0151 Clasificación LoC:QA76.9.M35Recursos en línea: Libro electrónicoTipo de ítem | Biblioteca actual | Colección | Signatura | Copia número | Estado | Fecha de vencimiento | Código de barras |
---|---|---|---|---|---|---|---|
Libro Electrónico | Biblioteca Electrónica | Colección de Libros Electrónicos | 1 | No para préstamo |
Acceso multiusuario
Introduction -- Propositions and Sets -- Relations and Functions -- Inductive Definitions -- Inductive Proofs -- Inductive Approach: Potential, Limitations, and Pragmatics.
The books in this trilogy capture the foundational core of advanced informatics. The authors make the foundations accessible, enabling students to become effective problem solvers. This first volume establishes the inductive approach as a fundamental principle for system and domain analysis. After a brief introduction to the elementary mathematical structures, such as sets, propositional logic, relations, and functions, the authors focus on the separation between syntax (representation) and semantics (meaning), and on the advantages of the consistent and persistent use of inductive definitions. They identify compositionality as a feature that not only acts as a foundation for algebraic proofs but also as a key for more general scalability of modeling and analysis. A core principle throughout is invariance, which the authors consider a key for the mastery of change, whether in the form of extensions, transformations, or abstractions. This textbook is suitable for undergraduate and graduate courses in computer science and for self-study. Most chapters contain exercises and the content has been class-tested over many years in various universities.
UABC ; Temporal ; 01/01/2021-12/31/2023.