Following Stevens' guidelines on the coronavirus emergency (COVID-19), all course materials will be offered online, starting Mar 11.

Instructor	Susan (Xueqing) Liu (xueqing.liu AT stevens DOT edu)
Meeting	MWF: 11:00 AM - 11:50 AM, Pierce Hall 120 Zoom meeting for Lectures
Susan's Office Hour	Wed 9-11 Zoom meeting for Office hour
CAs	Bhagyesh Patel Wed 2-3, link can be found on Piazza/Canvas Huihui Liu OH: Tue 2-4pm, link can be found on Piazza/Canvas
Recitation	RE: Fri 1-1:50PM Link can be found in Canvas/Piazza RF: Fri 2-2:50PM Link can be found in Canvas/Piazza

Class Description

This course is an introductory-level course for preparing undergraduate students at Stevens with the fundamental knowledge on data structures. Data structures are ways to organize information in the computer memory, making it more efficient to store, update and retrieve information. Upon finishing the course work, students are expected to achieve a good understanding on data structure, object-oriented programming, algorithm efficiency, etc; they should be capable of implementing basic data structures including lists, stacks, queues, binary trees, as well as fundamental algorithms including sorting, Hashing, and self-balancing trees. We will use the Java programming language throughout the course. The students are expected to be practice a significant amount of coding, in both computer and paper. This course has a prerequisite course CS 115 (Introduction to CS) and a co-requisite course CS 135 (Discrete Structures).

Learning Goals: Upon successful completion of this course, students should be able to:

• (Abstract Data Types): Understand the role of abstract data types in data structures, being able to use UML to represent ADTs;
• (Complexity): Derive Big-O notations for diverse non-recursive algorithms and use it to estimate the computational complexity of algorithms;
• (Collections): Understand the how to use the Collection class, including Lists, Stacks and Queues;
• (Trees): Implement Binary Search Trees, Max/Min Heaps, Priority Queues in Java, and understand the basic concepts of self-balancing trees;
• (Sets and Maps): Understand how to use sets and maps;
• (Sorting): Implement the algorithms of basic sorting algorithms in Java;
• (JUnit): Use JUnit to test projects;

Textbook: Objects, abstraction, data structures and design using Java. Elliot B. Koffman and Paul A.T. Wolfgang.

Schedule

Note: some slides require password, you can find the password from the home page in Canvas

Date	Slides/Readings	Code	Recitation	Assigned reading/HackerRank questions
Week 1 of Feb 1	Overview slides Java Basic slides Inheritance/ADT slides	Person.java Person_2.java Person_3.java Person_4.java	Eclipse installation	Appendix A
Week 2 of Feb 8	Overriding/overloading/Polymorphism slides Quiz 1, JUnit Casting, exceptions, packages slides	Computer.java BankAccount.java SavingsAccount.java	Review Quiz 1	Chapter 3: Inheritance and class definition Chapter 2: Program correctness and efficiency
Week 3 of Feb 15	Presidence day Big-O notations slides Quiz 2		GradeScope Training	Chapter 2.8: Efficiency of algorithms
Week 4 of Feb 22	Big-O notations (cont.) slides Quiz 3 Lists 1 slides	TwoSum.java TwoSumTest.java Person.java StevensStudent.java StevensDatabase.java SearchStevensStudentTest.java	Review of Quiz 3	Chapter 4: Lists Homework 1 due Feb 27
Week 5 of Mar 1	Lists 2 slides Lists 3 slides Stack 1 slides	MyLinkedList.java	No recitations	Chapter 4: Lists Chapter 5: Stack
Week 6 of Mar 8	Quiz 4 Mid-semester, no class on Wed Stack 2 slides	ParenChecker.java	Review of Quiz 4	Chapter 5: Stack
Week 7 of Mar 15	Queue: interface/application slides Recursion slides Review for Midterm	queue_stack.java stack_queue.java	Review for midterm	Chapter 6: Queue Chapter 7: Recursion Homework 2 due Mar 17
Week 8 of Mar 22	Binary tree/BST (guest lecture by Jay Lim)slides Midterm Huffman tree/BST slides		Review of homework 2	Chapter 8: Trees
Week 9 of Mar 29	DFS/BFS 1slides DFS/BFS 2slides Good Friday (no class)	BinaryTree.java BinarySearchTree.java IsoTriangle.java NQueens.java	No recitation	DFS Interview questions Dijkstra's algorithm and Proof of Dijkstra's algorithm correctness Reading: Chapter 8, Chapter 7
Week 10 of April 5	Binary tree/BST slides Quiz 5 Heap slides	AVLTree.java MaxHeap.java	Review of Quiz 5	Homework 3 due April 9 Chapter 8: Trees
Week 11 of April 12	Self-balancing tree slides Selection/Bubble/Insertion sort slides	Sort.java NQueens.java	Review of homework 3	Chapter 11: Self-balancing trees
Week 12 of April 19	Shell sort slides Heap/Quick sort slides Quiz 6	MaxHeap.java Sort.java	Review of Quiz 6	Chapter 10: Sorting
Week 13 of April 26	Sets/Maps slides Hashing 1slides Hashing 2 slides	Anagrams.java HashtableOpen.java HashtableChain.java GroupName.java	Review for the final	Chapter 9: Sets and Maps Homework 4 due April 30
Week 14 of May 3	Quiz 7 Review for endterm Review for final	TupleSort.java BFS.java	Review for Quiz 7
Week 15 of May 10	End term		Review of homework 4	Endterm: Sun - Tue
Final Exam	Final exam (May 16 2 hour or so within 1:00-5:00)			Homework 5 due

Final Grade Calculator

Homework	30%
In-class quizzes	10%
Midterm	20%
Endterm	20%
Final	20%

Policies

Late Policy: submit within 24 hours of deadline - 90%, within 48 hours - 70%, over 48 hours - 0 point, 0 if code not compile

Academic Integrity: Students must follow the instructions from the (Stevens Honor system). This course will have a zero-tolerance policy regarding plagiarism. You should complete all the assignments and quizzes on your own. You can help your classmates with questions such as how to use the programming language, what the library classes or methods do, what the errors mean, and how to interpret the assignment instructions. You are encouraged to come to both the instructor and the CAs' office hours regarding any questions you have, or email your questions to both the instructors or the CAs. However, you may not give or receive help from others (except the CA) with the actual implementation or answers for any of the assignments or tests. Do not show or share your code with others, and do not view or copy source code from others. For the same reason, you are not allowed to copy and paste a code snippet you found online in the assignments. All electronic work submitted for this course will be archived and subjected to automatic plagiarism detection. Whenever in doubt, please seek clarifications from the instructor. Students who violate the academic intergrity principle of Stevens will be immediately reported to the department and the school (which could leave a permanent mark on the transcript).

If you need special accommodations because of a disability, please contact the instructor through emails.