Syllabus

Week 1

1/19:

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

1/20:

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

1/21:

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

Week 2

1/24:

Lecture 5: Methods for self-referential lists Designing methods for complex class hierarchies Lecture 6: Accumulator methods More complicated methods for self-referential data

1/26:

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

1/27:

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

1/28:

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

Week 3

1/31:

Lecture 9: Abstract classes and inheritance Abstract classes and inheritance

2/02:

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

2/03:

Lecture 11: Defining sameness for complex data, part 1 Sameness of data values

2/04:

Lab 3 Practice white-box and black-box testing

Week 4

2/07:

Lecture 12: Defining sameness for complex data, part 2 More of the same

2/09:

Lecture 13: Abstracting over behavior Overview of world programming; Function objects

2/10:

Lecture 14: Abstractions over more than one argument More function objects

2/11:

Lab 4 Designing sameness methods; functional world games

Week 5

2/14:

Lecture 15: Abstracting over types Generics

2/16:

Lecture 16: Visitors Visitors

2/17:

Exam review, additional practice with generics

2/18:

Lab 5 Equality, functional world games

Week 6

2/21:

No class: Presidents’ Day

2/23:

Lecture 17: Mutation Creating cyclic data, mutation Midterm 1: 6:00--9:00PM Mugar 201

2/24:

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

2/25:

Lab 6 Working with function objects, introduction to generics

Week 7

2/28:

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

3/02:

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

3/03:

Lecture 21: ArrayLists Direct-access data structures: ArrayList; swapping two items, mapping over ArrayLists, for-each loops

3/04:

Lab 7

Week 8

3/07:

Lecture 22: ArrayLists ArrayLists and binary search; for-each loops; working with indices Lecture 23: For-each loops and Counted-for loops For-each loops and counted-for loops

3/09:

Lecture 24: While loops While-loops

3/10:

Design: Handin server data model

3/11:

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

Week 9

3/14:

No class: Spring break

3/16:

No class: Spring break

3/17:

No class: Spring break

3/18:

No lab this week

Week 10

3/21:

Lecture 25: Iterator and Iterable Iterators and Iterables

3/23:

Lecture 26: Hashing and Equality HashMap, equals

3/24:

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

3/25:

Lab 9 Heapsort, stress tests

Week 11

3/28:

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

3/30:

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

3/31:

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

4/01:

Lab 10 Wider trees and advanced iterators

Week 12

4/04:

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

4/06:

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

4/07:

Design: thinking playfully and creatively about algorithms

4/08:

Lab 11

Week 13

4/11:

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

4/13:

Scope in Java: access modifiers and packages

4/14:

Scope in Python

4/15:

Lab 12

4/12:

Midterm 2: 6:00--9:00PM Behrakis 010

Week 14

4/18:

No class: Patriots’ Day

4/20:

Lecture 33 Design choices in object-oriented languages: JavaScript

4/21:

Lecture 34: Implementing Objects Implementing Objects

4/22:

Lab 13 TBD

Week 15

4/25:

Slack

4/27:

Lecture 36 Wrap-up