CS 4288: Web Systems (Section 02; Leach)

Fall 2026

A holistic course of modern web systems and technologies, covering front end and back end. Build an Instagram clone in the first half of the semester, and a Google clone in the second.

Syllabus

Course Meetings

• Lecture: MW 2:30 - 3:45PM Central Time
• Office Hours:
  • W after class: 3:45pm-6:00pm CT (with Kevin)

    Note: Kevin will stay after class until 6pm, but only if students are present. Kevin will leave office hours if no students are in the room. Please do not leave and come back before 6pm; Kevin may have left.

  • M 12:00 - 1:00PM, T 1:30 - 2:30PM Central Time (with Nikki)

    Sony 4120

Course Resources

There are several resources you should be aware of this semester:

• Piazza will be the primary form of communication. If you have questions, please start by searching Piazza first. If you are not enrolled in the Piazza, please contact Nikki.
• autograder.isis.vanderbilt.edu — You will submit projects to the autograder website. There are five projects in this course, all of which involve submission to autograder. If you cannot view CS4288 on the autograder, please contact Nikki.
• I do not plan to use Brightspace this semester. All grades will be posted through the course website at a link shared through the Piazza.

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Online Event Calendar

Open calendar in new window

Date	Content	Deadline
Wed Aug 26, 2026	Introduction (slides)
Mon Aug 31, 2026	Web Basics (slides)
Wed Sep 2, 2026	Dynamic Pages (slides)
Fri Sep 4, 2026	Last day to add/drop classes.
Mon Sep 7, 2026	Sessions
Wed Sep 9, 2026	Encryption
Fri Sep 11, 2026		Project 1 Due
Mon Sep 14, 2026	Web Security
Wed Sep 16, 2026	REST APIs
Fri Sep 18, 2026		Project 2 Due
Mon Sep 21, 2026	JavaScript 1
Wed Sep 23, 2026	JavaScript 2
Mon Sep 28, 2026	TBA Exam Review Kevin away at conference
Wed Sep 30, 2026	Exam 1 (in class, proctored by Nikki)	Exam 1
Mon Oct 5, 2026	Asynchronous Programming, React, Closures
Wed Oct 7, 2026	Networking
Fri Oct 9, 2026		Project 3 Due
Mon Oct 12, 2026	Google File System
Wed Oct 14, 2026	Map Reduce
Mon Oct 19, 2026	Systems, Processes, Threads, and Sockets
Wed Oct 21, 2026	Bonus Lecture: Career Development
Thu Oct 22 - Fri Oct 23, 2026	Fall Break
Mon Oct 26, 2026	Information Retrieval 1
Wed Oct 28, 2026	Information Retrieval 2
Fri Oct 30, 2026		Project 4 Due
Mon Nov 2, 2026	Information Retrieval 3 + Exam 2 Review
Wed Nov 4, 2026	Exam 2	Exam 2
Mon Nov 9, 2026	Scaling Static and Dynamic Content
Wed Nov 11, 2026	Scaling Content, Virtualization, Datacenters, Blockchain
Mon Nov 16, 2026	Machine Learning
Wed Nov 18, 2026	Recommender Systems
Mon Nov 23, 2026	Thanksgiving Break — No Class
Wed Nov 25, 2026	Thanksgiving Break — No Class
Mon Nov 30, 2026	Auctions / Ethics
Wed Dec 2, 2026	TOR and the Dark Web
Fri Dec 4, 2026		Project 5 Due
Mon Dec 7, 2026	Enshittification
Wed Dec 9, 2026	Final Exam Review
Mon Dec 14, 2026	Final Exam 2pm - 5pm CT Class Ends — Absolutely all course material must be turned in!	Final Exam

Syllabus

Course Summary: This course is a contemporary exploration of modern web-based information systems. It will integrate concepts from multiple computer science topics used in the design, development, and deployment of web-based applications, services, and knowledge systems. While broad in scope, it will also cover several key concepts in depth, including: web networking protocols, web databases and applications, web services, web search, web-relevant security issues,web infrastructure, and web-relevant data mining. Students will learn how to incorporate these concepts into an engineering process that includes design, analysis, development and testing,using technologies such as HTTP, XML, JavaScript, AJAX, and others.

Students will form teams to implement assignments on Linux-based web servers using open-source components. These assignments will culminate in students implementing their own large-scale web search engine, roughly comparable to Google or Bing. At the end of this course, students will understand the science behind web-based information systems and the engineering principles for building them.

Objectives

This course is about the design and development of information systems in wide area networks. Its primary goal is to take a holistic view of modern web systems and their constituent technologies. By the end of this course, successful students will be able to:

• Understand how n-tiered architectures can be used to implement secure, scalable systems.
• Design and develop database-driven websites and applications
• Understand XML and JSON as messaging and data exchange mechanisms
• Utilize JavaScript to improve database-driven websites
• Analyze server logs to understand system performance and user behavior
• Understand designs for modern search engines and data centers
• Understand Web "semantic systems," such as auctions, recommendation systems, and search ranking.
• Understand critical components of the modern Web infrastructure: DNS, Content Delivery Networks, etc.
• Be confident about picking up a manual and quickly mastering any new web-related language, at any level of the software "stack"

Prerequisites

Students are required to have taken CS 3251.

Textbook

There is no required textbook for this course. Optional sources include:

• JavaScript: the Good Parts, by Douglas Crockford
• Flask Web Development: Developing Web Applications with Python, by Miguel Grinberg

How does this section differ from Prof. Hemingway's?

Both sections cover the same concepts -- full stack development, including front-end, back-end, and databases. The differences are in the assignments. This section has you reproduce an Instagram clone, a MapReduce server, and a basic search engine.

This section will use the autograder because I am a big believer in oracle/comparator testing. It remains an industry standard practice (even with AI involved), and students will benefit from the process of developing test cases (or guiding an AI to produce relevant test cases).

This section uses Python for the backend. In contrast, Prof. Hemingway's section uses JavaScript (nodejs) for backend. Both are popular, however I believe Python is more broadly applicable. We still cover JavaScript through the frontend (e.g., via React), however I want you to become broadly familiar with technologies relevant to computing, and Python is a huge one.

Regardless of which section you take, we follow the same grading distribution (i.e., very generous) for final grades. You will also be equally prepared to take the follow on project course if you like.

Course Communication

Piazza is the primary resource for communicating with course staff. You are allowed to ask general questions, however, you must not post your own entire solutions to projects (doing so is a violation of the Honor Code). Please make private posts if you are unsure whether your question contains too much sensitive code.

If you have a private issue to discuss, email Kevin Leach at kevin.leach@vanderbilt.edu and Cc our TA Nikki. Please put CS 4288 in the subject line of any email-based correspondence about this course.

Course Projects

This course contains 5 programming assignments. The first is individual, and the remainder are in optional groups of 2 to 3. You can form a different group for each project. Course staff will randomly assign a group if you like. Groups are recommended, but not required.

All team members will normally earn the same grade on their joint work. You are expected to resolve conflicts that may arise with your group members. The course staff may ask group members about each member's contributions if conflicts arise.

You must register your groups on the autograder before you submit. If you attempt to submit assignments and form a group later, we may not grade your assignment submission.

The autograder will show you your grade for each assignment. You have 5 submission tokens per day. After you run out of tokens, you cannot submit any more for a grade. This is meant to encourage you to test locally before submitting (e.g., to reflect industrial practice of testing software before shipping it to the customer).

Exams

There are two exams this semester (see the Calendar). These cover all lecture, and project materials.

A midterm exam will be administered during a course lecture slot. The final exam will be comprehensive and take place on our scheduled slot of Saturday, December 6, at 9am (sorry!).

During exams, you are allowed to refer to a single sheet of notes, front and back, on letter paper, 8.5"x11". You can use this sheet however you like, typed or handwritten, etc. You may not use electronic devices during exams.

Quizzes

From time to time, we will administer quizzes to ensure that you are staying on top of the material. There are no extensions or make ups for quizzes, and absolutely no late quizzes accepted.

Late Policy

The late policy is established only for Projects. We will not accept late quizzes. The autograder provides up to 4 late day tokens that you can use throughout the semester. If you want to submit a Project late, each day late you submit will consume 1 late day token. Note that students have their own late day tokens; thus, a group submission will use a late day token from each member. If group members have different numbers of late day tokens, then only those members with a token remaining will be able to receive a grade for the late submission.

To the extent possible, you must let us know in advance if you need to delay taking an exam.

Please contact the course staff via Private Piazza post or via email (to both Kevin and Nikki with CS4288 in the subject line) if you have some other extenuating circumstance (e.g., illness, bereavement). We may make extensions or other arrangements for students with such circumstances.

It is your responsibility to know the project deadlines and how late you are submitting.

Grading

Your grade is computed as follows

Assignment	Percentage of Grade
Programming Projects	5% each (25% for all 5)
Exam 1	15%
Exam 2	15%
Final Exam	20%
Quizzes	20%
Participation	5%

To pass the course, you must receive a passing average Project score and a passing average Exam score. By default, the threshold for "passing" is 70%. We may lower the threshold depending on exam and assignment outcomes (i.e., we will only ever make it easier to earn a better grade).

Participation

The Participation component of the grade is primarily used to reward students for in-class participation and participation in the Piazza. We may take attendance each class from time to time, provide extra credit to students who attend class, and give credit to students who contribute meaningfully to the Piazza forum.

Student Accommodations and Disabilities

Please let the course staff know in advance if you require accommodations for exams. We require you to submit accommodation requests at least 2 weeks before each exam.

We do not provide accommodations for quizzes.

Research Data

As a research university, we may collect data about your completion of assignments in anonymized or de-identified form for aggregate analysis. If you would not like to participate in any research, please let the instructor know via email at kevin.leach@vanderbilt.edu.

Honor Code Policy

This course is adapted from another course at the University of Michigan, which has successfully been taught since 2017 to thousands of students. It is possible that you come across online materials that relate to this course. Although the material changes every semester, we do retain every single submission ever made by any student who ever took this course. We will use automatic plagiarism detection software (take CS3276 for more information about why software plagiarism detection is feasible). Please do not use online repositories of similar project code -- odds are, we almost certainly know about it and will discover your use of it.

Generative AI Policy

Generative AI and Large Language Models are disruptive technologies that provide increasingly fascinating capabilities. While I am not opposed to attempts to use LLMs for completing the Projects, you are absolutely required to disclose how you use them. Failing to disclose your use of generative AI is a violation of the honor code and will result in a referral to the honor council.

• We cannot spend course staff time debugging code that you cannot explain. If you approach us in office hours with AI slop, we will not help you.
• You must document how you used generative AI in each Project submission. At a minimum, you must submit a readme.txt that describes how you used generative AI for that project. Your readme must describe whether and how generative AI was used for the following:
  • Conceptual understanding. Did you use an LLM to help you understand a concept described in the lectures or assignment spec?
  • High-level design. Did you use an LLM to help you plan out architecture for your submission? Like directories, which files go where, and what functions to implement?
  • Implementation. Did you use an LLM to help you implement functionality described in the spec?
  • Test cases. Did you use an LLM to write test cases?
  • Testing. Did you use an LLM to evaluate implementation against test cases?
  • End-to-end use. Did you just paste the spec into the LLM?
• In addition, we may award bonus points to students who submit their entire chat transcripts with their assignments.
• This course was designed in an era before LLMs existed. While I am convinced that this is a great curriculum, you may not get as much out of this course if you use an LLM -- we simply haven't had enough time as CS educators to adapt courses to the presence of LLMs and the impact they have on student education and retainment, especially in upper-level electives. For conscientious students, this may be an important point to consider.