Schedule

An introduction to algorithms

We begin the class by exploring the definition of computer science and by trying to write some basic algorithms.

Getting started with Racket

We consider Racket, the programming language we will use throughout the course.

Algorithmic and image decomposition

We consider a key technique in algorithmic thinking, how one “decomposes” a more complex problem or algorithm into simpler ones.

Reading and writing procedures

We consider ways to write your own procedures and why you might do so. We also explore how one interprets the algorithms others write. And we develop some mental models for what happens when we run Scheme/Racket programs.

Expressions and types

We explore many of the basic types of values in Racket, the capabilities Racket provides for working with those types, and how one builds more complex expressions. We also continue building our mental model.

Booleans, predicates, and conditionals

We consider how one writes procedures that make decisions.

Pause for breath

We take some time to review concepts and catch up.

Pair programming

We explore the whys and hows of working with others. We also catch up on any confusing issues from the first week of class as we prepare for the first set of learning assessment.

First set of learning assessments

We check in to make sure that we’re beginning to master the first set of concepts.

Lists

We return to Scheme’s list data structure and some ways to use lists to work with collections of data.

Lists, revisited

We continue our exploration of lists in Racket, including “the big three” list procedures: map, reduce, and filter.

Regular Expressions

We begin to explore regular expressions, tools used to identify patterns in strings.

Local bindings

We consider why and how to name values within procedures.

Documenting your code

We consider documentation for your programs: Why to write documention, when to write documentation, how to write documentation. We also explore various styles of documentation that we use in this course.

Testing with Rackunit

We consider testing: When, why, and how you might test the procedures and programs that you write.

Introduction to recursion

We begin our exploration of recursion, the most general form of repetition available in Scheme. You can use recursion to both build and iterate over different kinds of values.

Class Cancelled

Recursive skeletons, Lists and Numbers

We explore some basic patterns of list recursIon.

Second set of learning assessments

We check in to make sure that we’re beginning to master the second set of concepts. We revisit concepts missing from the first learning assessment inventory.

Tail Recursion

We consider a particular kind of recursion that tends to lead to more efficient code.

Higher-order recursive Design

We explore patterns of recursion in the design of programs, particularly with regards to higher-order procedures.

Randomness

We consider Scheme’s random procedure and how one might use that procedure in generating language.

Pairs and Vectors

We explore pairs, the basic building blocks of lists, and consider other, non-list structures one might build from pairs.
We also explore vectors, an alternative to lists for storing data. We consider how data are stored in memory.

Dictionaries and hash tables

We consider structures that allow us to store information for quick retrieval.

Third set of learning assessments

We check in to make sure that we’re beginning to master the third set of concepts. We revisit any missing concepts from earlier assessments.

Trees

We consider a common hierarchial mechanism for structuring data and its relationship to Scheme/Racket and XML/HTML.

Tree recursion

We consider how to write recursive programs that process trees and other tree-like structures.

Complexity analysis and binary search

We explore techniques for analyzing the number of calls made in evaluating procedures, particularly recursive procedures. We consider why such analysis is useful. We then delve into a common problem: That of finding values in a collection.

Sorting

We explore the problem of sorting. When you sort a list, vector, or other collection, you put the elements in order. The order of the elements usually corresponds to the type of the elements. We might sort strings alphabetically, grades numerically, colors by brightness, and so on and so forth. We also reflect on one common sorting algorithm.

Case study: Insertion Sort

We continue our exploration of sorting by considering the applicability of the divide-and-conquer approach to the problem of sorting. We look at one particular divide-and-conquer algorithm, insertion sort. We explore the relationship between the number of steps the algorithm typically takes and the number of values in the list we are sorting.

Fourth set of learning assessments

We check in on the last set of topics and revisit any necessary topics from earlier in the term.

Case study: Mergesort

We continue our exploration of sorting by considering the applicability of the divide-and-conquer approach to the problem of sorting. We look at one particular divide-and-conquer algorithm, merge sort. We explore the relationship between the number of steps the algorithm typically takes and the number of values in the list we are sorting.

Wrap-up

Open Office Hours

This class is an optional class in which you can come ask questions..

Reading day

No class!

Last set of learning assessments (optional)

We have one more opportunity to check our learning.