As someone familiar with modeling that uses “complicated, unintuitive syntax” (p. 26), I found this book to be a delightful introduction to symbolic programming using STELLA. With the run-time version of STELLA supplied with the text, the process of designing and organizing new models, guided stepwise with examples in each chapter, becomes more enjoyable and produces rapid results.
Although the sheer number of chapters (44, to be precise) may be intimidating to the reader, the chapters are clustered according to themes to provide some cohesion. Furthermore, each chapter describes a different biological system model, complete with a STELLA diagram and associated code. This allows for verification of correct model design before exploring the possibilities for each system. The authors further enhanced the readability of the text by structuring the chapters in a semi-linear fashion; each chapter is meant to be read in order to build through the different aspects of STELLA, but the book can be explored out of order with little impact on the overall understanding.
My primary complaints are that there are no distinct end-of-chapter exercises to test understanding of the newly-developed ideas in the chapter, nor does the version of STELLA provided allow for saving a model for later use. However, the overall easy introduction to biological modeling with STELLA outweighs these points and I would recommend this text to a reader interested in model development using symbolic programming tasks.
Megan Sawyer is an assistant professor of mathematics at Southern New Hampshire University in Manchester, NH.