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Mathematics in Computing

Gerard O'Regan
Publisher: 
Springer
Publication Date: 
2020
Number of Pages: 
458
Format: 
Paperback
Edition: 
2nd
Series: 
Undergraduate Topics in Computer Science
Price: 
54.99
ISBN: 
978-3-030-34208-1
Category: 
Textbook
[Reviewed by
Tricia Muldoon Brown
, on
08/1/2020
]
See our review of the first edition of this book.
 
As a regular instructor of mathematics classes for computer science students, I was interested in O’Regan’s textbook Mathematics in Computing.  I wanted to see if I could get a deeper and broader understanding of how many of the mathematical topics that I teach are utilized in computing.  From that perspective, this text was successful along the breadth component, although not the depth.
 
Most chapters are set up with a short introduction, several sections of mathematical topics, and a brief conclusion including several review questions.  The interior mathematical sections usually contain important vocabulary, practical examples, and historical context.  The chapters are very readable and should be accessible to general interest readers.  Thankfully, the key terms are defined within the text rather than set aside as in more traditional textbooks.  The extra effort to introduce relevant mathematicians and other kinds of scientists associated with the development of the theories as well as some societal background also aids in making the book enjoyable to read.  
 
The 28 chapters cover an extensive list of topics, beginning with the foundations of computing, moving on to mathematical disciplines such as number theory and graph theory, as well as including other topics of software engineering and programming.  What you will not find, however, is any deep explanation or proofs to accompany the theory.  You can think about this book as a well-done Cliffs Notes version of the history and development of mathematics in computing.
 
In addition to being a source for mathematicians who want to understand how their field connects with computing, this is would be a very good reference for computer science students who want to learn more mathematics.  As topics come up in various classes the reader would be able to look up the appropriate entries, almost as a dictionary of mathematics topics to accompany computer science concepts.  Because the entries are brief, the reader can quickly absorb the necessary lexicon and develop a working grasp of the math behind the computer science topic.  Because of this, I would not use this textbook as the main text to accompany an undergraduate or graduate course.   I think it is much more suited as a reference book that could be used in addition to the main text for various classes.
Tricia Muldoon Brown (tmbrown@georgiasouthern.edu) is a Professor of Mathematics at Georgia Southern University with interests in combinatorics, recreational mathematics, and sports.

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