Statistical Software Engineering
Publisher: National Academies Press 1996
Number of pages: 89
This book identifies challenges and opportunities in the development and implementation of software that contain significant statistical content. While emphasizing the relevance of using rigorous statistical and probabilistic techniques in software engineering contexts, it presents opportunities for further research in the statistical sciences and their applications to software engineering.
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by Agner Fog - agner.org
These manuals describe everything you need to know about optimizing code for x86 and x86-64 microprocessors, including optimization advices for C++ and assembly language, details about the microarchitecture and instruction timings of processors.
A guide for software source code quality. The guidelines apply to anyone who creates, modifies, or reads software source code. This document is a set of rules to follow during the implementation phase that will help produce a higher quality result.
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A concise introduction to software design using Python. Intended for people with no programming experience, this book starts with the most basic concepts and gradually adds new material. The goal is to teach you to think like a computer scientist.
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