Nowadays, ubiquitous computing applications--for example, neural networks, fuzzy logic, decision-making, medical informatics, and real-estate management--make a title like this one sound somehow general. In fact, the content is a little bit of this and a little bit of that, and primarily contains notes from the author’s lectures on computational physics. There are seven chapters: “Simulation,” “Graphics,” “Visualization,” “Efficiency,” “Recursion,” “Projects,” and “Modeling.” Each chapter is divided into three parts that present some general topics, including random walks, the approximation of π, text seen as word clouds, games like the turtle puzzle, recursive calculations, as well as distribution and dynamics models. High school teachers could use it as a book that adopts physics laws in problem modeling.

There are many graphs and pseudocode listings in C++, Python, Fortran, Java, and other programming languages. However, most of them are shells that simply give an idea of how a model works. The chapters are divided into very short sections called “labs.” Teachers could use these to teach students the basics only, or they could add methodology to show students how to address a specific problem. Readers will find many numerical analysis examples that make the book friendlier to tactile learners who absorb knowledge by exploring the physical world around them.

The material cannot be considered state of the art, especially when compared to the popular Applied Soft Computing journal or the serial World Conference on Soft Computing (WSC) texts (published by Springer) from the World Federation on Soft Computing (WFSC). However, high school students studying engineering, future graphic designers, and students interested in applying some of the models to fields other than physics will benefit from reading this book. Other titles are better if you’re looking for reflections on teaching applied computer science [1,2].