This book is the result of a comprehensive effort by a broader community to lay down fundamental knowledge on recommendation systems in software engineering. The aim is very challenging. I am very glad to be able to note that the process to achieve such an aim was designed with much scientific humbleness with respect to the many intricacies of an area that is evolving so rapidly. The editors mention as many as four review iterations. The authors of the chapters reviewed the other chapters in the book. They met in person at a two-day meeting to present their chapters and discuss them. All this contributed immensely to the quality of the resulting text.

The book is structured into three parts. Part 1 introduces basic techniques that are used for building recommendation systems in software engineering. Part 2 is devoted to methods of evaluating recommendations in software engineering. In Part 3, the authors explore applications, focusing on needs, issues, and solutions of recommendation systems applied to various specific software engineering tasks.

Part 1 includes, in my opinion, two kinds of techniques. The first three chapters describe general techniques used in recommendation systems. I find their inclusion very useful. Only the remaining five chapters are devoted to specific techniques used in software engineering: source code recommending, mining bug data, collecting and processing interaction data, dealing with developer profiles, and recommendation delivery. These chapters form the core of the contents as far as the description of recommender systems in software engineering is concerned.

Part 2 starts with a discussion of dimensions and metrics for evaluating recommendation systems. Special chapters are devoted to benchmarking, simulation, and field studies. In a sense, however, the most attractive part of the book is the third one. Under the umbrella of applications, the respective chapters grouped here hint at directions of current and future development of the field. The respective chapters cover reuse; refactoring; program transformation; requirements discovery; change, evolution, and bugs; and product line configuration. Each chapter is elaborated with a great deal of scientific rigor. The reader learns the actual state of the art, and often also descriptions of relevant exemplary approaches, and there is always a list of dozens of up-to-date references.

The book is a perfect starting point of study for graduate students of software engineering, especially when specializing in recommendation. It is highly recommended also to software professionals seeking to learn what are the possible future directions of their professional field. The book is impressive. Rarely a collection of contributed chapters achieves such a high level of conformity, not only in a formal sense but also in the sense of its contents. Rarely a collection of contributed chapters gives such a representative treatise of a topic. Recommending is a topic that has been among the most important in researching the web during the last decade or so. The book establishes the importance of the concept in the field of software engineering. It is not the first one to do so, but nevertheless it is a very important contribution serving to advance the field. I highly recommend this book to software engineering students, professionals, experts, and other interested readers.