Syllabus🔗

Note: the schedule towards the end of the semester is tentative and will change as needed.

Week 1🔗

1/08:

Lecture 1: Data Definitions in Java Designing Data: Simple classes, classes with containment Lecture 2: Data Definitions: Unions Designing unions of classes; self-reference

1/10:

Lecture 3: Methods for simple classes Methods for simple classes and classes with containment Lecture 4: Methods for unions Methods for unions of classes and classes with self-reference

1/11:

Lecture 4: Methods for unions Methods for unions of classes and classes with self-reference Lecture 5: Methods for self-referential lists Designing methods for complex class hierarchies

1/12:

Lab 1 Data definitions in Java; Eclipse IDE; Handins homework server; simple methods

Week 2🔗

1/15:

No class: MLK Day

1/17:

Lecture 6: Accumulator methods More complicated methods for self-referential data

1/18:

Lecture 7: Accumulator methods, continued (continued) Methods with accumulators

1/19:

Lab 2 Designing methods in Java: classes, containment, unions, self-reference

Week 3🔗

1/22:

Lecture 8: Practice Design Recap: designing methods and wish lists for a larger problem

1/24:

Lecture 9: Abstract classes and inheritance Abstract classes and inheritance

1/25:

Lecture 10: Customizing constructors for correctness and convenience Customizing constructors for correctness and convenience

1/26:

Lab 3 Practice white-box and black-box testing

Week 4🔗

1/29:

Lecture 11: Defining sameness for complex data, part 1 Sameness of data values Lecture 12: Defining sameness for complex data, part 2 More of the same

1/31:

Lecture 13: Abstracting over behavior Overview of world programming; Function objects Lecture 14: Abstractions over more than one argument More function objects

2/01:

Lecture 15: Abstracting over types Generics

2/02:

Lab 4 Designing sameness methods; functional world games

Week 5🔗

2/05:

Lecture 16: Visitors Visitors

2/07:

Homework review, practice with generics

2/08:

Exam review, additional practice with generics

2/09:

Lab 5 Equality, functional world games

Week 6🔗

2/12:

Lecture 17: Mutation Creating cyclic data, mutation

2/14:

Lecture 18: Mutation inside structures Testing mutation methods, indirect cycles

2/15:

Lecture 19: Mutation, aliasing and testing Aliasing and equality, revisited

2/16:

Lab 6 Working with function objects, introduction to generics

Week 7🔗

2/19:

No class: Presidents’ Day

2/21:

Lecture 20: Mutable data structures Removing items from lists, mutable lists Lecture 21: ArrayLists Direct-access data structures: ArrayList; swapping two items, mapping over ArrayLists, for-each loops

2/22:

Lecture 22: ArrayLists ArrayLists and binary search; for-each loops; working with indices

2/23:

Lab 7

2/20:

Midterm 1: 5:30--8:30PM Hurtig 129

Week 8🔗

2/26:

Lecture 23: For-each loops and Counted-for loops For-each loops and counted-for loops

2/28:

Lecture 24: While loops While-loops

2/29:

Lecture 25: Iterator and Iterable Iterators and Iterables

3/01:

Lab 8 Loyd's 15 puzzle: working with ArrayLists, loops and imperative worlds

Week 9🔗

3/04:

No class: Spring break

3/06:

No class: Spring break

3/07:

No class: Spring break

3/08:

No lab this week

Week 10🔗

3/11:

Lecture 26: Hashing and Equality HashMap, equals

3/13:

Lecture 27: Introduction to Big-O Analysis Big Oh: searching and sorting; insertion sort and selection sort

3/14:

Lecture 28: Quicksort and Mergesort Big Oh: searching and sorting; quicksort and merge sort

3/15:

Lab 9 Tries

Week 11🔗

3/18:

Lecture 28: Quicksort and Mergesort Big Oh: searching and sorting; quicksort and merge sort

3/20:

Lecture 29: Priority Queues and Heapsort Big Oh: searching and sorting; HeapSort -- Priority Queue

3/21:

Lecture 35: Dynamic Programming Dynamic programming: Solving recursive problems faster

3/22:

Lab 10 Heapsort, stress tests

Week 12🔗

3/25:

Lecture 35: Dynamic Programming Dynamic programming: Solving recursive problems faster Lecture 30: Breadth-first search and Depth-first search on graphs Graph algorithms: breadth-first search, depth-first search

3/27:

Lecture 30: Breadth-first search and Depth-first search on graphs Graph algorithms: breadth-first search, depth-first search

3/28:

Lecture 31: Dijkstra’s Algorithm for single-source shortest paths Graph algorithms: Dijkstra's algorithm, and comparison with BFS/DFS

3/29:

Lab 11 Wider trees and advanced iterators

Week 13🔗

4/01:

Lecture 32: Minimum Spanning Trees Minimum spanning trees: Prim's and Kruskal's algorithms

4/03:

Lecture 32: Minimum Spanning Trees Minimum spanning trees: Prim's and Kruskal's algorithms Design: Handin server data model

4/04:

Design: thinking playfully and creatively about algorithms

4/05:

Lab 12 Python

Week 14🔗

4/08:

Scope in Java: access modifiers and packages

4/10:

Java: Streams

4/11:

Lecture 34: Implementing Objects Implementing Objects

4/12:

Lab 13 Streams

4/09:

Midterm 2: 6:00--9:00PM Hurtig 129

Week 15🔗

4/15:

No class: Patriots’ Day

4/17:

Lecture 36 Wrap-up