Software Engineering At Google Lessons Learned From Programming Over Time Pdf Github


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Introduction to Aerosol Modelling


Introduction to Aerosol Modelling

Author: David L. Topping

language: en

Publisher: John Wiley & Sons

Release Date: 2022-08-15


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INTRODUCTION TO AEROSOL MODELLING Introduction to Aerosol Modelling: From Theory to Code An aerosol particle is defined as a solid or liquid particle suspended in a carrier gas. Whilst we often treat scientific challenges in a siloed way, aerosol particles are of interest across many disciplines. For example, atmospheric aerosol particles are key determinants of air quality and climate change. Knowledge of aerosol physics and generation mechanisms is key to efficient fuel delivery and drug delivery to the lungs. Likewise, various manufacturing processes require optimal generation, delivery and removal of aerosol particles in a range of conditions. There is a natural tendency for the aerosol scientist to therefore work at the interface of the traditional academic subjects of physics, chemistry, biology, mathematics and computing. The impacts that aerosol particles have are linked to their evolving chemical and physical characteristics. Likewise, the chemical and physical characteristic of aerosol particles reflect their sources and subsequent processes they have been subject to. Computational models are not only essential for constructing evidence-based understanding of important aerosol processes, but also to predict change and impact. Whilst existing textbooks provide an overview of theoretical frameworks on which aerosol models are based, there is a significant gap in reference material that provide training in translating theory into code. The purpose of this book is to provide readers with exactly that. In following the content provided in this book, you will be able to reproduce models of key processes that can either be used in isolation or brought together to construct a demonstrator 0D box-model of a coupled gaseous-particulate system. You may be reading this book as an undergraduate, postgraduate, seasoned researcher in the private/public sector or as someone who wishes to better understand the pathways to aerosol model development. Wherever you position yourself, it is hoped that the tools you will learn through this book will provide you with the basis to develop your own platforms and to ensure the next generation of aerosol modellers are equipped with foundational skills to address future challenges in aerosol science.

Software Engineering Perspectives in Systems


Software Engineering Perspectives in Systems

Author: Radek Silhavy

language: en

Publisher: Springer Nature

Release Date: 2022-07-16


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The study of software engineering and its applications to system engineering is critical in computer science research. Modern research methodologies, as well as the use of machine and statistical learning in software engineering research, are covered in this book. This book contains the refereed proceedings of the Software Engineering Perspectives in Systems part of the 11th Computer Science On-line Conference 2022 (CSOC 2022), which was held in April 2022 online.

Bits and Bugs


Bits and Bugs

Author: Thomas Huckle

language: en

Publisher: SIAM

Release Date: 2019-03-08


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In scientific computing (also known as computational science), advanced computing capabilities are used to solve complex problems. This self-contained book describes and analyzes reported software failures related to the major topics within scientific computing: mathematical modeling of phenomena; numerical analysis (number representation, rounding, conditioning); mathematical aspects and complexity of algorithms, systems, or software; concurrent computing (parallelization, scheduling, synchronization); and numerical data (such as input of data and design of control logic). Readers will find lists of related, interesting bugs, MATLAB examples, and ?excursions? that provide necessary background, as well as an in-depth analysis of various aspects of the selected bugs. Illustrative examples of numerical principles such as machine numbers, rounding errors, condition numbers, and complexity are also included.