The University of Chicago
Department of Computer Science

MPCS 56600 Course Syllabus

Introduction to Blockchain
Online Offering Only - No Hyde Park Campus Class

Summer 2024

Instructor:        Mark Shacklette
Office:               Online Zoom Only
Office Hours:    Tuesdays 3:00 PM - 3:45 PM and by Appt.

email:    mark@cs.uchicago.edu (read hourly or so)
              mshack@post.harvard.edu (read hourly or so)

Teaching staff: 

SUBJECT	COURSE	TITLE	TIME	BUILDING
324	56600	Introduction to Blockchain:  Concepts, Technologies, Implementations	Tuesday, 4:10pm - 6:00 PM (CST)	Zoom Online*

*Course is conducted entirely remotely via zoom.

Texts: Required

Bitcoin and Cryptocurrency Technologies: A Comprehensive Introduction, Narayanan, et. al. Princeton, 2016.  ISBN: 978-0691171692

Mastering Bitcoin:  Programming the Open Blockchain, 2nd ed., Antonopoulos, O'Reilly, 2017.  ISBN:  978-1491954386

Programming Bitcoin, Song, O'Reilly, 2019.  ISBN:  978-1492031499

Texts: Highly Recommended

Docker Cookbook, Miell & Sayers, Manning, 2016, ISBN: 9781491919712

Docker in Practice, Sebastien Goasguen, O'Reilly, 2016, ISBN: 9781617292729

Recommended Reading

II. PREREQUISITE:

All students in this course are required to have passed core programming.  No exceptions.

Additionally, the following courses are suggested prerequisites for taking this course.  Those with this or equivalent background will find this course easier going:

Mathematics for Computer Science: Discrete Mathematics (MPCS 50103 or equivalent)
Algorithms (MPCS 55001 or equivalent)
Networks (MPCS 54001 or equivalent)

Solid comfort with one (or more) of the following programming languages:  Java (Javascript), C/C++, Python, Ruby, C#, Go, Objective-C/Swift.   If you have a preferred familiarity with any Functional/Lisp/Haskell dialect (i.e., CLOS, Scheme, Haskell, etc.), we should talk.

For those university students not enrolled in the MPCS:

For those students wishing to audit this course:

III. COURSE DESCRIPTION

V. ACADEMIC INTEGRITY

Students are expected to have read and understood the University's policy on Academic Integrity. This policy is detailed in the Student Manual of University Policies and Regulations, available online at https://masters.cs.uchicago.edu/page/program-policies.

GENERATIVE AI TOOLS:  Problem solving is truly the core skill that needs to be developed. This can only be achieved through determination and perseverance; there are no shortcuts. Finishing assignments on time and getting the correct answer are meaningless if you do not fully understand what you are submitting. In computer science, there are many ways to accomplish the same task, and solutions will vary by levels of exposure, experience, and expertise. By not allowing a natural progression of skills you risk undermining your long-term success in this field.  THEREFORE:  In this course, we will be developing skills and knowledge that are important to discover and practice on your own.  Because use of AI tools inhibits development of these skills and knowledge, students are not allowed to use any AI tools, such as (but not limited to) ChatGPT or DallE 2, in this course. Students are expected to present work that is their own without assistance from others, including automated tools. If you are unclear if something is an AI tool,  check with Professor Shacklette or a TA.  Using AI tools for any purposes in this course will violate the University�s academic integrity policy and will incur subsequent, and likely severe, penalties.

VI. METHOD OF INSTRUCTION

Methods include lecture and homework (labs) assignments.  
 

VII. OTHER COURSE INFORMATION

Attendance:

No formal attendance taken.  There may be information presented in class that is not in the texts. You will find the lectures helpful in doing the laboratory exercises.

Make-up Work:

Students are expected to read the assigned texts before class in order to be able to full participate in the discussions and course activities.
 

VIII. METHOD OF EVALUATING STUDENT PROGRESS

Assigned work evaluated as follows:

Grading scale:
 
95-100:     A
90-94:       A-
87.6-89:    B+
83-87.5:    B
80-82.9:    B-
76-79:       C+

Lab Deliverables will be graded on a 10-point basis.  Deliverable due dates are noted on the lab pages.  All labs and homework are due by 4:00 pm on the due date (with the exception of Lab 9). We will be using Github for submissions:

Work Submission:

We will be using a repository for each submission. We have provided invitation URLs on Ed Discussion that you will use to request your lab repository. Use the GitHub classroom invitation link for "LabN" [for N=1,2,3,4] to create your assignment repository. See the Ed post for more info about submission using GitHub classroom. Upload your LabN files and any supporting materials to the repo. Please include a README text file that contains any instructions or additional details for the TAs to assist with grading.

When you open the invitation URL in a browser tab, you will have to complete the following steps:

Github may ask you to grant permission for GitHub Classroom to have access to your GitHub account. If you are asked this question, you should say yes and grant access to Github Classroom.

You must click “Accept this assignment” or your repository will not actually be created. Do not skip this step!

If you run into any issues, please ask for help on Ed Discussion.

All assignments are due as specified on this syllabus and lab and other deliverables.  Any and all lateness will suffer penalties.  The penalty for late labs will be 2.0 points off for each 24-hour period the lab is late, through five days late (5*2.0=10.0).  After five days delay, the lab will no longer be accepted for grading and will receive a 0.

NB: The instructor reserves the right to alter the course contents, dates, times or percentage of credit based on time allowed and class progress through the course material. The instructor also reserves the right to curve grades if he deems it in the best interest of the majority of students.

IX. COURSE SCHEDULE

The following abbreviations reference the following works (see esp. Required Reading under Schedule below):

Abbreviation	Referenced Text
BCT	Bitcoin and Cryptocurrency Technologies.  Narayanan et. al.
MB	Mastering Bitcoin, Antonopoulos
PB	Programming Bitcoin, Song

Articles* (Abbreviations Key for Required texts (see esp. Required Reading under Schedule below):

*Articles starred may be found on the cluster under my pub directory (~mark/pub/56600/pdfs).  All numbers refer to chapters in texts, not pages, unless otherwise noted (as "pp. xxx").

EVERYONE:  Our discussion platform has moved from Piazza to Ed Discussion via Canvas.  Please access Ed here.  An Ed Discussion Quickstart guide is located here.