CS 260 Data Structures - Syllabus

Term and Credits

Winter 2023-2024
3 Credits

Room and Time

Section 001 - MW 9:00AM-10:20AM Prof. Boady [3675 Market Street 1054-1055]
Section 002 - TR 10:30AM-11:50AM Prof. Boady [3675 Market Street 1054-1055]


Mark Boady
Electronic Mail Address: mwb33@drexel.edu
Office: 3675 Market Street Room 1063 (near snack machine)
Extention: 215-895-2347
Office Hours: Wednesday 1:00PM-3:00PM

Teaching Assistant(s)

Anomitro Paul
Electronic Mail Address: ap3742@drexel.edu
Office: CLC 3675 Market Room 1066
Office Hours: Monday 6:00PM-8:00PM and Wednesday 6:00AM-8:00PM

Mihir Rao
Electronic Mail Address: mr3554@drexel.edu
Office: CLC 3675 Market Room 1066
Office Hours: Monday 2:00PM-4:00PM and Wednesday 2:00AM-4:00PM

Satwik Shresth
Electronic Mail Address: ss5278@drexel.edu
Office: CLC 3675 Market Room 1066
Office Hours: Tuesday 6pm-8pm and Wednesday 6pm-8pm

Daniel Epstein
Electronic Mail Address: de442@drexel.edu
Office: CLC 3675 Market Room 1066
Office Hours: Tuesday 6pm-8pm

Natalia Weglicka
Electronic Mail Address: nw528@drexel.edu
Office: CLC 3675 Market Room 1066
Office Hours: Monday 2pm-4pm and Wednesday 2pm-4pm

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, 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
Book Website with Additional Resources

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:

CCI's Commitment to Diversity, Equity, and Inclusion (DEI)

The College of Computing & Informatics commits to creating a positive and safe learning environment for everyone - instructors, professional staff, and students - both inside and outside of the classroom. We embrace the diversity of thoughts, perspectives, and experiences that each community member brings, and we honor everyone's identity (including, but not limited to, race, ethnicity, age, gender, socioeconomic status, sexuality, religion, veteran status, and disability). We encourage each community member to share information regarding pronouns, religious and cultural holidays, accommodations, and any other information that will assist instructors in fostering a supportive and inclusive community environment. For more information about CCI's commitment to DEI, visit Diversity, Equity & Inclusion Council | Drexel CCI.

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 (January 8, 2024) Lecture 1: Searching
Lecture 2: Analysis of Algorithms
Reflection 01 Due Friday 1/12 at 11:59PM
2 (January 15, 2024) Lecture 3: Bubble and Insertion Sorts
[1/15/24: Martin Luther King, Jr. Day watch video lecture]
Lecture 4: Merge Sort and Quick Sort
Homework 1 Due Wednesday 1/17 at 11:59PM
Reflection 02 Due Friday 1/19 at 11:59PM
3 (January 22, 2024) Lecture 5: Stacks
Lecture 6: Queues
Homework 2 Due Wednesday 1/24 at 11:59PM
Reflection 03 Due Friday 1/26 at 11:59PM
4 (January 29, 2024) Lecture 7: Open Hash Table
Lecture 8: Closed Hash Table
Homework 3 Due Wednesday 1/31 at 11:59PM
Reflection 04 Due Friday 2/2 at 11:59PM
5 (February 5, 2024) Lecture 9: Binary Search Trees
Lecture 10: AVL Trees
Homework 4 Due Wednesday 2/7 at 11:59PM
Reflection 05 Due Friday 2/9 at 11:59PM
6 (February 12, 2024) Lecture 11: Heaps
Lecture 12: Midterm Exam
Reflection 06 Due Friday 2/16 at 11:59PM
7 (February 19, 2024) Lecture 13: Huffman Encoding
Lecture 14: Intro to Graphs (Breadth First Search)
Homework 5 Due Wednesday 2/21 at 11:59PM
Reflection 07 Due Friday 2/23 at 11:59PM
8 (February 26, 2024) Lecture 15: Depth First Search
Lecture 16: Dijkstra's Algorithm and Bellman-Ford
Homework 6 Due Wednesday 2/28 at 11:59PM
Reflection 08 Due Friday 3/1 at 11:59PM
9 (March 4, 2024) Lecture 17: Prim's Algorithm
Lecture 18: Kruskal's Algorithm
Homework 7 Due Wednesday 3/6 at 11:59PM
Reflection 09 Due Friday 3/8 at 11:59PM
10 (March 11, 2024) Lecture 19: The Master Theorem
Lecture 20: Something Cool
Homework 8 Due Wednesday 3/13 at 11:59PM
Reflection 10 Due Friday 3/15 at 11:59PM
11 (March 18, 2028) Final Assessment - March 21, 2024 3:30-5:30PM in Bossone Research Entr. Center AUD
Extra Credit - Due March 20, 2024 at 11:59PM
Optional Homework: Due March 20, 2024 at 11:59PM