There is also a notable absence of algorithmic thinking. While graph theory appears, there is no discussion of search algorithms, complexity, or data structures—topics that many current discrete math courses include to serve CS majors. Olympia Nicodemi’s Discrete Mathematics is not the best-selling textbook on the market, nor is it the most up-to-date. But for the right student—one who wants to learn not just what mathematicians know but how they think—it is a hidden gem.
Reading Nicodemi is like having a patient, brilliant tutor at your side, constantly asking, “But can you prove that?” and then waiting, without judgment, for you to try. In an era of instant answers and video tutorials, that kind of intellectual patience is rare and precious. Discrete Mathematics by Olympia Nicodemi
First published as part of a series aimed at fostering mathematical maturity, Nicodemi’s book is not a lightweight survey of topics for computer science majors, nor is it a dry collection of proofs. Instead, it is a carefully crafted bridge from computational calculus to the abstract reasoning required for advanced mathematics. This article explores what makes this textbook distinctive, its core strengths, and why it remains a valuable—if underappreciated—resource. The most striking feature of Nicodemi’s approach is its insistence on active learning . Many discrete math texts present a theorem, give a proof, and then ask students to repeat the pattern. Nicodemi inverts this process. She frequently introduces a problem or a pattern, guides the student through examples, and then asks: What do you notice? Can you state a general rule? There is also a notable absence of algorithmic thinking
