Discrete Mathematics & Functional Programming
CS/MATH 220, Whitman College, Fall 2016
MWF 11:00-11:50, Olin 124
Office hours: As posted
and by appointment
About this course
Welcome to CS/MATH 220! The official course
Students will practice formal reasoning over discrete structures through
two parallel modes: mathematical proofs and computer programs.
We will introduce sets and lists, Boolean logic, and proof techniques.
We will explore recursive algorithms and data types alongside mathematical
and structural induction. We consider relations and functions as mathematical
objects built on set theory and develop idioms of higher-order programming.
If time permits, additional topics may include graphs, lattices, or groups,
and their applications to computer science.
I am excited to bring together so many beautiful ideas in this
course. I am experienced at teaching functional programming in Scheme
to beginners. However, before this summer I had not formally studied
discrete mathematics since I was an undergraduate myself, nor had I
used the programming language SML. I look forward to learning together.
By the end of this class, you will be able to:
- Manipulate forms in symbolic logic;
- Write mathematical proofs for propositions about sets, relations, functions, and the correctness of algorithms;
- Write simple programs in the SML programming language;
- Model phenomena in nature or culture using sets, relations, and functions, as well as SML datatypes;
- Devise, implement, and test solutions to algorithmic problems,
using symbolic logic to analyze the problem and synthesize a solution.
Recurring themes include:
- Writing and using formal definitions. We look carefully at
formal, rigorous definitions of mathematical ideas, built from
- Thinking recursively. Recursion
is defining something in terms of itself. This technique is crucial to
some kinds of algorithms and to some kinds of mathematical definitions
- Analysis and synthesis. Many of our proofs and programs comprise
two main steps: Breaking something apart and putting something else
OverviewFor a detailed outline, see the table of contents in your textbook. See also the course schedule.
Set and List.
- We meet the basic mathematical concepts of set, element, set
operations, cardinality, Cartesian product, and powerset. We learn
the basics of the ML programming language including functions and
datatypes. We learn to use ML's main composite type, the list.
- We explore the system of Boolean logic (the "first-order
predicate calculus"). This heading is characterized by three "games" to
exercise your understanding of symbolic logic: 1. verifying logical
equivalences; 2. verifying argument forms; 3. verifying argument forms
with quantification. We also write ML programs that use Boolean
operators and consider how the quantification of a problem
specification affects the algorithm to solve it.
- We learn to write
careful proofs of set-theoretical propositions. This includes one of
the most challenging sections, proofs about powersets. We also consider
the connections between proofs and algorithms.
- We build on our understanding of sets to consider the definition
of mathematical relations and their properties, propositions about
them, and programs that manipulate them. The relation is a useful
concept in itself, but this heading also lets us practice further the
proof and programming techniques we have learned so far.
- Earlier parts of our study will have introduced recursive
definitions, but here we tackle the idea head-on. Specific topics are
recursive types in ML programming and proofs using structural and
- We study functions as mathematical objects built on set theory. These proofs will build on all the
techniques you have learned so far. We also learn programming idioms
that build on the theory of functions as mathematical objects.
Davis (email@example.com). Course goals and overview adapted from Thomas VanDrunen's syllabus for CS/MATH 243, Wheaton College.
Created August 28, 2016
Last revised August 30, 2016, 01:22:45 PM PDT
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