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Why does this book take a practical approach to discrete mathematics?

Why does this book take a practical approach to discrete mathematics? (Brisk · Chapter 1) — "Preface Discrete math is a popular book topic — start Googling aro…

Ideas in this flowchart

  • Discrete mathematics for computer science should emphasize practical understanding and use.
  • Most discrete mathematics textbooks are thick, dense, and packed with equations and proofs.
  • These textbooks generally present principled approaches aimed at mathematicians and researchers.
  • Mathematicians are needed to derive complex expressions and prove theorems from scratch.
  • Computer science practitioners may be better served by a different approach.
  • Discrete mathematics is therefore part of the mandatory curriculum in most computer science undergraduate programs.
  • The emphasis for future programmers and engineers should differ from the emphasis for mathematicians and computing-theory researchers.
  • Practical computer scientists mostly need to use discrete mathematics tools rather than derive them.
  • They need familiarity and practice with fundamental concepts and the thought processes those concepts involve.
  • Constructing a graph-theory proof is rarely necessary for the average software developer.
  • Reasoning about probability, logic, and the properties of collections is frequently useful.
  • Most computer science students benefit from appreciating the richness and rigor of discrete mathematics.
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Why does this book take a practical approach to discrete mathematics?

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Brisk

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"Preface Discrete math is a popular book topic — start Googling around and you’ll find a zillion different textbooks about it. Take a closer look, and you’ll discover that most of these are pretty thick, dense volumes packed with lots of equations and proofs. They’re prin- cipled approaches, written by mathematicians and (seemingly) to mathematicians. I speak with complete frankness when I say I’m comforted to know that the human race is well covered in this area. We need smart people who can derive complex expressions and prove theorems from scratch, and I’m glad we have them. Your average computer science practitioner, however, might be bet- ter served by a different approach. There are elements to the dis- crete math mindset that a budding software developer needs ex- perience with. This is why discrete math is (properly, I believe) part of the mandatory curriculum for most computer science un- dergraduate programs. But for future programmers and engineers, the emphasis should be different than it is for mathematicians and researchers in computing theory. A practical computer scientist mostly needs to be able to use these tools, not to derive them. She needs familiarity, and practice, with the fundamental concepts and the thought processes they involve. The number of times the average software developer will need to construct a proof in graph theory is probably near zero. But the times she’ll find it useful to reason about probability, logic, or the properties of collections are frequent. I believe the majority of computer science students benefit most from simply gaining an appreciation for the richness and rigor of"

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