Scientific Software Engineering in a Nutshell

TL;DR

This paper emphasizes the importance of selecting appropriate tools and techniques for scientific software development, covering program organization, debugging, data reduction, visualization, and useful libraries.

Contribution

It provides a comprehensive overview of essential tools and strategies for effective scientific software engineering, highlighting best practices and key libraries.

Findings

Effective tool selection improves scientific program quality.

Using proper debugging and data reduction techniques enhances analysis.

Libraries like boost, GSL, LEDA, and Numerical Recipes are valuable resources.

Abstract

Writing complex computer programs to study scientific problems requires careful planning and an in-depth knowledge of programming languages and tools. In this chapter the importance of using the right tool for the right problem is emphasized. Common tools to organize computer programs, as well as to debug and improve them are discussed, followed by simple data reduction strategies and visualization tools. Furthermore, some useful scientific libraries such as boost, GSL, LEDA and numerical recipes are outlined.