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This text provides a very simple, initial introduction to the complete scientific computing pipeline: models, discretization, algorithms, programming, verification, and visualization. The pedagogical strategy is to use one case study – an ordinary differential equation describing exponential decay processes – to illustrate fundamental concepts in mathematics and computer science. The book is easy to read and only requires a command of onevariable calculus and some very basic knowledge about computer programming. Contrary to similar texts on numerical methods and programming, this text has a much stronger focus on implementation and teaches testing and software engineering in particular.
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This open access book offers an initial introduction to programming for scientific and computational applications using the Python programming language. The presentation style is compact and examplebased, making it suitable for students and researchers with little or no prior experience in programming. The book uses relevant examples from mathematics and the natural sciences to present programming as a practical toolbox that can quickly enable readers to write their own programs for data processing and mathematical modeling. These tools include file reading, plotting, simple text analysis, and using NumPy for numerical computations, which are fundamental building blocks of all programs in data science and computational science. At the same time, readers are introduced to the fundamental concepts of programming, including variables, functions, loops, classes, and objectoriented programming. Accordingly, the book provides a sound basis for further computer science and programming studies.
Computational Science and Engineering  Professional Computing  Programming Techniques  Software Engineering/Programming and Operating Systems  Mathematics of Computing  Programming Language  Software Engineering  programming  Python  computational science  data science  object oriented programming  open access  Maths for scientists  Applied computing  Computer programming / software engineering  Operating systems  Mathematical theory of computation  Maths for computer scientists
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This open access book constitutes the proceedings of the 23rd International Conference on Foundations of Software Science and Computational Structures, FOSSACS 2020, which took place in Dublin, Ireland, in April 2020, and was held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2020. The 31 regular papers presented in this volume were carefully reviewed and selected from 98 submissions. The papers cover topics such as categorical models and logics; language theory, automata, and games; modal, spatial, and temporal logics; type theory and proof theory; concurrency theory and process calculi; rewriting theory; semantics of programming languages; program analysis, correctness, transformation, and verification; logics of programming; software specification and refinement; models of concurrent, reactive, stochastic, distributed, hybrid, and mobile systems; emerging models of computation; logical aspects of computational complexity; models of software security; and logical foundations of data bases.
Mathematical Logic and Foundations  Discrete Mathematics in Computer Science  Programming Languages, Compilers, Interpreters  Programming Techniques  Logic in AI  Computer Systems Organization and Communication Networks  categorical models and logics  language theory, automata, and games  modal, spatial, and temporal logics  type theory and proof theory  concurrency theory and process calculi  rewriting theory  semantics of programming languages  program analysis, correctness, transformation, and verification  logics of programming  software specification and refinement  emerging models of computation  logical aspects of computational complexity  models of software security  logical foundations of data bases  mathematics  artificial intellegence  formal logic  linguistics  Mathematical foundations  Mathematical logic  Discrete mathematics  Maths for computer scientists  Programming & scripting languages: general  Compilers & interpreters  Computer programming / software engineering  Artificial intelligence  Computer networking & communications
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