CIS 5050: Software Systems (Fall 2025)
Overview

Image of a router
This course provides an introduction to fundamental concepts of distributed systems, and the design principles for building large-scale computational systems.

We will study some of the key building blocks – such as synchronization primitives, group communication protocols, and replication techniques – that form the foundation of modern distributed systems, such as cloud-computing platforms or the Internet. We will also look at some real-world examples of distributed systems, such as GFS, MapReduce, Spark, and Dynamo, and we will gain some hands-on experience with building and running distributed systems.

CIS 5050 is one of the core courses in the MSE program, as well as an option for the WPE-I requirement for PhD students.

Logistics

Instructor:
Linh Thi Xuan Phan
Office hours: TBA (Levine 576)

When and where:
Mondays/Wednesday 10:15-11:45am, Towne 100

Teaching assistants and office hours: TBD

Course policies

Course textbook:
Distributed Systems: Principles and Paradigms, 4th edition (by M. van Steen and A. Tanenbaum). You can get a digital version of this book for free; hardcopies of the previous version of the book are available, e.g., from Amazon. Additional material will be drawn from selected research publications.

Prerequisites:
The course requires undergraduate-level operating systems and networking knowledge, such as CIS 4480 (formerly CIS 3800) and NETS 2120 (or CIS 5530) or the equivalence. You must also be proficient in C or C++ programming.

Workload:
The course will involve three substantial programming assignments, a group project, and two midterms. Both the programming assignments and the project involve a considerable amount of programming in C/C++, and the project requires the ability to work with your classmates in teams.

Grading:
Your letter grade will be based on the individual programming assignments (35%), the group project (30%), the midterm exams (30%), and participation (5%).

Attendance and other policies:
Class attendance is mandatory and will count towards your participation score. More details on attendance and key course policies can be found here.


Resources

We will be using Ed Discussion for all course-related discussions.

Homework assignments and project are available for download from the assignments page. You can submit your solutions online via GradeScope.

Special sessions

The goal of the special sessions is to provide you with tools and resources that might be useful for the assignments and project. See the special sessions page for more details.

Tentative schedule

  Topic Details Reading Remarks
  Introduction Course overview
Policies
Chapter 1  
  Processes and threads Basic concepts
The UNIX model
Implementation in the kernel
Chapter 3.1 (Sections 1+2)  
  System calls
System calls
The file API
Kernel entry/exit
   
  Concurrency control
Synchronization primitives
Race conditions, critical sections
Deadlock and starvation
   
  Synchronization Semaphores
Classical synchronization problems
Monitors and condition variables
[Hoare monitors]
[Mesa monitors]
 
  Communication Sockets
Socket programming
Handling multiple connections
Chapters 4.1+4.3  
  Remote Procedure Calls
Programming model
Stub code; marshalling; binding
Handling failures
Chapters 4.2+8.3  
  Naming Kinds of names; name spaces
The Domain Name System;
Akamai; DNSSEC
Chapter 6  
  Clock synchronization
Logical clocks
NTP and Berkeley algorithms
Lamport and vector clocks
Chapters 5.1+5.2  
  Replication Primary/backup protocols
Quorum protocols
Sequential and causal consistency
Client-centric models
Chapter 7  
  First midterm exam
  Group communication
Reliable multicast
IP multicast
FIFO, causal and total ordering
Chapter 8.4  
  Bigtable and Project Bigtable case study
Project overview
[Bigtable]  
  Fault tolerance
2PC and 3PC
Logging and recovery
Chandy-Lamport algorithm
Chapters 8.5+8.6;  
  State-machine replication
Failure models
The Consensus problem
Paxos
Chapters 8.1+8.2; [Paxos]  
  Non-crash Fault Tolerance
The Byzantine Generals problem
Impossibility results
Solutions
[BFT]  
  Distributed file systems NFS
Coda
Disconnected operation
Chapter 2.3.3; [Coda]  
  Google File System
Google cluster architecture
Reading and writing in GFS
Consistency and fault tolerance
[Cluster] [GFS]  
  MapReduce
MapReduce programming model
System architecture
[MapReduce]  
  Spark Differences to MapReduce
RDDs
Case study: PageRank
[RDD] [Spark]  
  DHTs and Dynamo Distributed hash tables
The CAP dilemma
Amazon Dynamo
[Dynamo]  
  Special topics
Evolution of DynamoDB
Predictability, Scalability, Availability, and Consistency
   
  Second midterm exam
  Reading days
  Project demos and reports
Web site contact: Linh Thi Xuan Phan