Here is an ideal textbook on software visualization, written especially for students and teachers in computer science. It provides a broad and systematic overview of the area including many pointers to tools available today. Topics covered include static program visualization, algorithm animation, visual debugging, as well as the visualization of the evolution of software. The author's presentation emphasizes common principles and provides different examples mostly taken from seminal work. In addition, each chapter is followed by a list of exercises including both pen-and-paper exercises as well as programming tasks.

Here is an ideal textbook on software visualization, written especially for students and teachers in computer science. It provides a broad and systematic overview of the area including many pointers to tools available today. Topics covered include static program visualization, algorithm animation, visual debugging, as well as the visualization of the evolution of software. The author's presentation emphasizes common principles and provides different examples mostly taken from seminal work. In addition, each chapter is followed by a list of exercises including both pen-and-paper exercises as well as programming tasks.

Content Description #Includes bibliographical references and index.

Software Visualization: From Theory to Practice was initially selected as a special volume for "The Annals of Software Engineering (ANSE) Journal", which has been discontinued. This special edited volume, is the first to discuss software visualization in the perspective of software engineering. It is a collection of 14 chapters on software visualization, covering the topics from theory to practical systems. The chapters are divided into four Parts: Visual Formalisms, Human Factors, Architectural Visualization, and Visualization in Practice. They cover a comprehensive range of software visualization topics, including *Visual programming theory and techniques for rapid software prototyping and graph visualization, including distributed programming; *Visual formalisms such as Flowchart, Event Graph, and Process Communication Graph; *Graph-oriented distributed programming; *Program visualization for software understanding, testing/debugging and maintenance; *Object-oriented re-design based on legacy procedural software; *Cognitive models for designing software exploration tools; *Human comprehensibility of visual modeling diagrams in UML; *UML extended with pattern compositions for software reuse; *Visualization of software architecture and Web architecture for better understanding; *Visual programming and program visualization for music synthesizers; *Drawing diagrams nicely using clustering techniques for software engineering.

Software Visualization: From Theory to Practice was initially selected as a special volume for "The Annals of Software Engineering (ANSE) Journal", which has been discontinued. This special edited volume, is the first to discuss software visualization in the perspective of software engineering. It is a collection of 14 chapters on software visualization, covering the topics from theory to practical systems. The chapters are divided into four Parts: Visual Formalisms, Human Factors, Architectural Visualization, and Visualization in Practice. They cover a comprehensive range of software visualization topics, including *Visual programming theory and techniques for rapid software prototyping and graph visualization, including distributed programming; *Visual formalisms such as Flowchart, Event Graph, and Process Communication Graph; *Graph-oriented distributed programming; *Program visualization for software understanding, testing/debugging and maintenance; *Object-oriented re-design based on legacy procedural software; *Cognitive models for designing software exploration tools; *Human comprehensibility of visual modeling diagrams in UML; *UML extended with pattern compositions for software reuse; *Visualization of software architecture and Web architecture for better understanding; *Visual programming and program visualization for music synthesizers; *Drawing diagrams nicely using clustering techniques for software engineering.

Effective visualization is the best way to communicate information from the increasingly large and complex datasets in the natural and social sciences. But with the increasing power of visualization software today, scientists, engineers, and business analysts often have to navigate a bewildering array of visualization choices and options. This practical book takes you through many commonly encountered visualization problems, and it provides guidelines on how to turn large datasets into clear and compelling figures. What visualization type is best for the story you want to tell? How do you make informative figures that are visually pleasing? Author Claus O. Wilke teaches you the elements most critical to successful data visualization. Explore the basic concepts of color as a tool to highlight, distinguish, or represent a value Understand the importance of redundant coding to ensure you provide key information in multiple ways Use the book’s visualizations directory, a graphical guide to commonly used types of data visualizations Get extensive examples of good and bad figures Learn how to use figures in a document or report and how employ them effectively to tell a compelling story

An accessible primer on how to create effective graphics from data This book provides students and researchers a hands-on introduction to the principles and practice of data visualization. It explains what makes some graphs succeed while others fail, how to make high-quality figures from data using powerful and reproducible methods, and how to think about data visualization in an honest and effective way. Data Visualization builds the reader’s expertise in ggplot2, a versatile visualization library for the R programming language. Through a series of worked examples, this accessible primer then demonstrates how to create plots piece by piece, beginning with summaries of single variables and moving on to more complex graphics. Topics include plotting continuous and categorical variables; layering information on graphics; producing effective “small multiple” plots; grouping, summarizing, and transforming data for plotting; creating maps; working with the output of statistical models; and refining plots to make them more comprehensible. Effective graphics are essential to communicating ideas and a great way to better understand data. This book provides the practical skills students and practitioners need to visualize quantitative data and get the most out of their research findings. Provides hands-on instruction using R and ggplot2 Shows how the “tidyverse” of data analysis tools makes working with R easier and more consistent Includes a library of data sets, code, and functions