COSC-2010: Data Structures

Fall 2023



  • 11/15/23: Posted the rooms for the final exams. Section 01's exam is on W 12/13 4–6 PM in St. Mary's 126. Section 02's exam is on Sa 12/16 9–11 AM in Healy 104.
  • 11/7/23: Posted p5.
  • 11/2/23: Posted my solution to hw4.
  • 10/21/23: Posted algorithms for red-black trees.
  • 10/18/23: Posted hw4 and p4.
  • 10/11/23: Posted my solution to hw3.
  • 10/4/23: Updated the link to CLRS's Chapter 18.
  • 9/30/23: Posted my solution for hw1.
  • 9/27/23: Posted hw3 and p3.
  • 9/21/23: Posted my solution for hw2.
  • 9/13/23: Posted hw1 and hw2. Changed the due date for hw1 from F 9/15 to F 9/29. Both are still optional.
  • 9/12/23: Posted p2.
  • 8/30/23: Posted OS and IDE information for the CAs.
  • 8/23/23: Posted p1.
  • 8/23/23: Posted p0.
  • 8/22/23: Created student accounts on Autolab. Had accounts created on cs-class-1.
  • 8/21/23: Published the hw0, the concept inventory.
  • 8/21/23: Published the Canvas site.
  • 8/21/23: Turned on the Piazza site.
  • 7/28/23: Set exam and assignment dates.
  • 3/26/23: Created this Web page.
  • Where, When, Who

    Section 01 Class Time: TR 2–3:15 PM
    Section 01 Classroom: St. Mary's 126
    Section 02 Class Time: TR 9:30–10:45 AM
    Section 02 Classroom: CB 201
    Instructor: Mark Maloof
    Office: 325 St. Mary's Hall
    Mailbox: 329A St. Mary's Hall
    Office Hours: In-person (325 STM): TR 11:00 AM–12:00 PM; online: M 10:30–11:30 AM and W 3:00–4:00 PM; or by appointment. Send me an email to get the Zoom link for online office hours.


    This course is designed as a second year course for majors and minors and covers intermediate and advanced data structures and algorithm analysis. Starting with the art and science of analyzing algorithms, the main goal of this course is to learn various techniques for organizing data so that computer programs can create, access, modify, and delete data efficiently. Topics covered include basic data structures (for example, lists, stacks and queues), trees, hashing, heaps, graphs, and self-balancing data structures; worst-case, average-case, and amortized analysis; and basic problem solving techniques. The topics are theoretical in nature but have dramatic impact in practice.

    Prerequisites: Computer Science II (COSC-052) and either Mathematical Methods for Computer Science (COSC-030) or Introduction to Proofs and Problem Solving (MATH-200)

    Required Text:

    Recommended Texts:

    Learning Goals

    By the end of the semester, students will be able to:


    My course policies are designed to supplement the University's Undergraduate Honor System and the CS Department's Honor Policy. Unless stated otherwise when I distribute an assignment, the following is the default for all assignments for this course. I have developed my policies from past teaching experiences and from the CS Department's Honor Code at George Mason University.

    I am obligated to refer all suspected cases of academic dishonesty by undergraduate and master's students to Georgetown's Honor Council. I am obligated to refer all suspected cases of academic dishonesty by doctoral students to the dean of the Graduate School. If you have any questions about these policies or how they apply, please discuss such concerns with me during class, during office hours, by e-mail, or using the class's discussion board.

    In my experience, students at Georgetown do honest work. The very small percentage of students who have submitted someone else's work as their own did so because they did not manage their time wisely.

    Students must always follow proper scholarly practice for all submitted work, whether graded or ungraded and whether a draft or final version of a proposal, paper, program, or problem set. As scholars, we must acknowledge our reliance on the work of others through citation. You can never submit someone else's work as your own without proper attribution. The University assumes that students learned how to properly cite material at their previous institutions. If this is not the case, please let me know.

    Indeed, students may be quite adept at and knowledgeable about citing and quoting material from traditional sources, such as books and articles. Typically, we do not have cite facts, common math formulae, or expressions of our own ideas, observations, interpretations, and analyses. However, students new to computer science may not realize that theorems, proofs, algorithms, programs, and code fragments may require the same treatment as any other form of expression.

    For convenience, you do not need to cite the course materials, which includes the syllabus, sources linked from the syllabus, the course textbooks, the class lectures and discussion, posts on the discussion board, and conversations with me and the courses assistants. You must, however, cite the use of any resource that is not part of the course materials. Note that “the textbook” does not extend to the textbook's Web site, its contents, lecture slides, solution manuals, code repositories, or any other supplemental material related to the textbook. If you are unsure about what requires citation or what constitutes proper scholarly practice, please ask me during class, during office hours, by e-mail, or using the discussion board.

    I design my courses and assignments so students have what they need to complete the assignments individually without consulting outside resources. I determine the size of and credit for assignments based on the assumption that the work for them is the result of individual effort using only the course resources and materials. Students who use outside resources to complete assignments may not be eligible for full credit. Students who do not acknowledge their use of outside resources to complete assignments may be in violation of my course policies and the university's policies on academic integrity.

    The materials that I create and use for my courses (“Course Materials”) are my intellectual property. You may not disseminate or reproduce them in any form for public distribution (e.g., sale, exchange, etc.) without my written permission. Course Materials include all written or electronic documents and materials that I provide, including but not limited to syllabi, current and past assessments and their solutions (e.g., exams, homeworks, projects, problem sets, etc.), and presentations such as lectures, videos, slides, etc. Course Materials may only be used by students enrolled in the course for academic (i.e., course-related) purposes. Furthermore, your solutions to assessments are derivative works of my copyrighted material and are therefore subject to that protection because they necessarily incorporate my protected expression. Consequently, you may not further disseminate or reproduce in any form for distribution (e.g., uploading to websites, sale, exchange, etc.) your solutions to assessments.

    Published course readings (book chapters, articles, reports, etc.) available in Canvas are copyrighted material. I make these works available to students through licensed databases or fair use. They are protected by copyright law, and may not be further disseminated or reproduced in any form for distribution (e.g., uploading to websites, sale, exchange, etc.) without permission of the copyright owner. Note that under § 1202 of Title 17 of the U.S. Code it is illegal to remove or alter copyright management information.

    You can find more information about intellectual property and copyright here: You can find more information about computer acceptable use policy and intellectual property here:

    Copyright issues aside, if you post your solutions to assessments on the Internet, students in current and future classes will be able to find your solutions and submit them as their own work without attribution. Naturally, students who submit another student's work as their own violate my course policies, and in the past, the Honor Council has found these students in violation and sanctioned them. The Honor Council has also found students who post their solutions on the Internet in violation because they facilitated cheating, violated copyright law, the Web site's terms of service, or some combination of these.

    I understand that prospective employers may ask for examples of your work. I recommend that students devise a scheme for providing examples in a manner that does not violate copyright law, does not violate the terms of service of the site on which you have posted material protected by copyright, and does not facilitate cheating. One idea is to share a private folder on Google Drive with a prospective employer.

    The following list details acceptable and unacceptable practices:

    Policies dealing logistics:

    OSs, IDEs, and Tools

    Name NetID Operating Systems IDEs and Tools
    Allegra aih19 macOS Xcode, Visual Studio Code, make, valgrind, FileZilla
    Charlie jm3438 macOS Visual Studio, Visual Studio Code, valgrind, FileZilla, sftp and scp
    Cooper ceg126 Windows, Linux (class-1/cs-class-1 or other) Eclipse, Visual Studio, vi, valgrind, FileZilla, sftp and scp, Windows Subsystem for Linux
    Mackenzie mto35 macOS, Linux (class-1/cs-class-1 or other) Xcode, Eclipse, FileZilla
    Mark maloofm macOS, Linux (class-1/cs-class-1 or other) Linux is my IDE, vi, make, valgrind, gdb, sftp and scp
    Miles yh643 Windows, Linux (class-1/cs-class-1 or other) Visual Studio, Visual Studio Code, valgrind, FileZilla
    Quinn cqo2 macOS, Linux (class-1/cs-class-1 or other) Eclipse, The Terminal app is my IDE, make, valgrind, FileZilla
    Reed rcu8 macOS Visual Studio Code
    Tony yc980 macOS, Linux (class-1/cs-class-1 or other) Xcode, Visual Studio Code, FileZilla
    Shah sv517 macOS, Windows, Linux (class-1/cs-class-1 or other) Visual Studio Code, The Terminal app is my IDE, make, valgrind, FileZilla
    Will whb20 macOS Xcode, Visual Studio Code, FileZilla


    1 Introduction, Maps and Hash Tables
    9.1, 9.2
    2 Maps and Hash Tables
    9.1, 9.2
    3 Maps and Hash Tables
    9.1, 9.2
    4 Trees, Binary Trees, Binary Search Trees, Traversals, Operations
    5   Algorithms and Pseudocode
    6   Algorithm Analysis, Asymptotic Notation
    7   Analysis of Elementary Data Structures
    5, 6
    8 Multi-way trees, (a, b) trees, (2, 4) trees
    9 B-trees, Midterm
    10 Red-black trees
    11 AVL trees
    12 Splay Trees
    13 Heaps and Priority Queues
    14 Graph Algorithms
    14 Graph Algorithms
    16 Sorting: Merge-Sort and Quick-Sort

    Assignments and Grading

    String Grades::getLetterGrade()
      if (grade >= 94)
        return "A";
      else if (grade >= 90)
        return "A-";
      else if (grade >= 87)
        return "B+";
      else if (grade >= 84)
        return "B";
      else if (grade >= 80)
        return "B-";
      else if (grade >= 77)
        return "C+";
      else if (grade >= 74)
        return "C";
      else if (grade >= 70)
        return "C-";
      else if (grade >= 67)
        return "D+";
      else if (grade >= 64)
        return "D";
        return "F";
    } // Grades::getLetterGrade

    I use automatic grading routines to assign an initial grade for the projects. It is important to emphasize that the grade you obtain from Autolab is an initial grade and may not be your final grade. There are many important aspects of a program that are difficult or impossible to assess using automatic grading routines. For example, automatic grading routines can not determine if you have written proper documentation. They can not easily assess if an implementation of an operation is optimally efficient. As a consequence, I start with the initial grade you obtain from Autolab and take further deductions if necessary. I grade the last submission for practical and pedagogical reasons.

    For complete implementations, I use the following distribution as a guide:

    Notice that an implementation consisting entirely method stubs would obtain an initial grade of 60%. Such an implementation is incomplete, and would be subject to further deductions based on the effort required to implement the required operations.

    In addition to the above, the following deductions may be taken if applicable:

    Materials: Readings, Videos, and Links

    Other Interesting Links

    Copyright © 2023 Mark Maloof. All Rights Reserved. This material may not be published, broadcast, rewritten, or redistributed.