CS 260 Data Structures - Syllabus

Term and Credits

Spring 2022
3 Credits

Room and Time

Section 001 - TR 9:30AM-10:50AM Prof. Boady [3675 Market Street 1052]
Section 002 - TR 11:00AM-12:30AM Prof. Boady [3675 Market Street 1052]


Mark Boady
Electronic Mail Address: mwb33@drexel.edu
Office: 3675 Market Street Room 1058 (near snack machine)
Extention: 215-895-2347
Office Hours: Monday and Wednesday 10-11AM

Teaching Assistant(s)

Mathilda Nguyen
Electronic Mail Address: gtn35@drexel.edu
Office: Online Only. Zoom link will be posted to Discord
Office Hours: Wednesday 6-8PM

Course Description

Data structures form the basics for the programmer's toolbox. You will become familiar with the basic common data structures, and learn to modify them or create your own. Further, the notion of data abstraction is important from several aspects. You will start down the road of separating interface from implementation, to viewing a problem simply in terms of functional requirements and dependencies (or lack of). On the flip side, we will explore various issues involved in implementing a given interface.

Course Objective and Goals

  1. Understand what an algorithm is.
  2. Master the ability to analyze the complexity of programs and algorithms. Understand recurrence relations and sums and basic asymptotic analysis.
  3. Understand algorithms and abstract data types. In particular, understand sets, stacks, queues, priority queues, dictionaries, binary search trees, hash tables, arrays, linked lists, trees, graphs, and heaps.
  4. Understand what basic operations each data structure supports and why one might choose one over another.
  5. Understand data abstraction and recursion, both in the context of procedures and of data types.


  1. Arrays
  2. Trees
  3. Graphs
  4. Dictionaries/ Hash Tables
  5. Algorithm Analysis

Audience and Purpose within Plan of Study

This is required course for CS BS students and CS Minor Students. It is generally taken sophomore year.


What Students Should Know Prior to this Course

  1. Students should be able to program in a high level language (C++, Java, Python, etc)
  2. Familiarity with basic data structures such as vectors and arrays.
  3. Familiarity with object oriented design principles.

What Students will be able to do upon Successfully Completing this Course: Statement of Expected Learning

  1. Students will be able to analyze data structures.
  2. Students will understand a set of fundamental algorithms and how to apply them.
  3. Students will understand basic data structures and how to apply them to different situations.


The Algorithm Design Manual (3rd ed.)
Author: Steven Skiena
Published: October 6, 2020
ISBN-10: 3030542556
ISBN-13: 978-3030542559
Buy from Amazon

Grading and Policies

Final grades will be determined by your total points weighted according to this distribution. Grades may be curved but are generally computed via the formula below. It may be modified at the instructor's sole discretion, but letter grades will generally not be lower than those shown here.

Course Material

Late Policy

Academic Honesty Policy

The CCI Academic Honesty policy is in effect for this course. Please see the policy at http://drexel.edu/cci/resources/current-students/undergraduate/policies/cs-academic-integrity/.

Academic Honesty Violations will be reported to the University. Punishment will be determined by the severity of the incident. Punishments include, but are not limited to,





Extra Credit


University Policies
In addition to the course policies listed on this syllabus, course assignments or course website, the following University policies are in effect:

Appropriate Use of Course Materials

It is important to recognize that some or all of the course materials provided to you are the intellectual property of Drexel University, the course instructor, or others. Use of this intellectual property is governed by Drexel University policies, including the IT-1 policy found at: https://drexel.edu/it/about/policies/policies/01-Acceptable-Use/
Briefly, this policy states that all course materials including recordings provided by the given prior written approval by the University. Doing so may be considered a breach of this policy and will be investigated and addressed as possible academic dishonesty, among other potential violations. Improper use of such materials may also constitute a violation of the University's Code of Conduct found at: https://drexel.edu/cpo/policies/cpo-1/ and will be investigated as such.

Recording of Class Activities:

In general, students and others should not record course interactions and course activities in lecture, lab, studio or recitation.
Students who have an approved accommodation from the Office of Disability Resources to record online lectures and discussions for note taking purposes should inform their course instructor(s) of their approved accommodation in advance. The recording of lectures and discussions may only be carried out by the students enrolled in the class who have an approved accommodation from Disability Resources with their instructors’ prior knowledge and consent. Students with approved accommodations may be asked to turn off their recorder if confidential or personal information is presented.
If a student has any comments, concerns, or questions about provided class materials and/ or recording, talk to your course instructor first. If this does not resolve the issue, you can also reach out to the Department Head, and use the process described for a grade appeal to move your concern forward. The process described for grade appeals can be found at: https://drexel.edu/provost/policies/grade-appeals/

Tentative Course Schedule

Please see the appropriate assignment webpages for a detailed description of course deliverables.

Week Topic Assignments
1 (March 28, 2022) Lecture 1: Searching
Lecture 2: Analysis of Algorithms
Blog 01 Due Friday 4/1 at 11:59PM
2 (April 4, 2022) Lecture 3: Bubble and Insertion Sorts
Lecture 4: Merge Sort and Quick Sort
Homework 1 Due Wednesday 4/6 at 11:59PM
Blog 2 - Due Friday 4/8 at 11:59PM
Blog Comments 1 - Due Friday 4/8 at 11:59PM
3 (April 11, 2022) Lecture 5: Stacks
Lecture 6: Queues
Homework 2 Due Wednesday 4/13 at 11:59PM
Blog 3 - Due Friday 4/15 at 11:59PM
Blog Comments 2 - Due Friday 4/15 at 11:59PM
4 (April 18, 2022) Lecture 7: Hash Tables
Lecture 8: General Linked Lists
Homework 3 Due Wednesday 4/20 at 11:59PM
Blog 4 - Due Friday 4/22 at 11:59PM
Blog Comments 3 - Due Friday 4/22 at 11:59PM
5 (April 25, 2022) Lecture 9: Binary Search Trees
Lecture 10: AVL Trees
Homework 4 Due Wednesday 4/27 at 11:59PM
Blog 5 - Due Friday 4/29 at 11:59PM
Blog Comments 4 - Due Friday 4/29 at 11:59PM
6 (May 2, 2022) Lecture 11: Heaps
Lecture 12: No Class - Free Period to take Assessment
Midterm Assessment - Due Thursday May 5 at 11:59PM
7 (May 9, 2022) Lecture 13: Huffman Encoding
Lecture 14: Intro to Graphs (Depth-First Search)
Homework 5 Due Wednesday 5/11 at 11:59PM
Blog 6 - Due Friday 5/13 at 11:59PM
Blog Comments 5 - Due Friday 5/13 at 11:59PM
8 (May 16, 2022) Lecture 15: Dijkstra's Algorithm
Lecture 16: Breadth First Search and Bellman Ford
Homework 6 Due Wednesday 5/18 at 11:59PM
Blog 7 - Due Friday 5/20 at 11:59PM
Blog Comments 6 - Due Friday 5/20 at 11:59PM
9 (May 23, 2022) Lecture 17: Prim's Algorithm
Lecture 18: Kruskal's Algorithm
Homework 7 Due Wednesday 5/25 at 11:59PM
Blog 8 - Due Friday 5/27 at 11:59PM
Blog Comments 7 - Due Friday 5/27 at 11:59PM
10 (May 30, 2022) Lecture 19: The Master Theorem
Lecture 20: Special Topic (Quantum Algorithms)
Homework 8 Due Wednesday 6/1 at 11:59PM
Blog 9 - Due Friday 6/3 at 11:59PM
Blog Comments 8 - Due Friday 6/3 at 11:59PM
11 (June 6, 2022) Final Assessment - Due Wednesday June 8, 2022 at 11:59PM