Last Updated: 2018-09-28 Fri 14:38

CSCI 2041: Advanced Programming Principles

University of Minnesota

4 credits, Fall 2018

Table of Contents

1 Basic Information

1.1 Catalog Description

Principles/techniques for creating correct, robust, modular programs. Computing with symbolic data, recursion/induction, functional programming, impact of evaluation strategies, parallelism. Organizing data/computations around types. Search-based programming, concurrency, modularity.

1.2 Prerequisites

Grade of C or better in CSCI 1913 or 1933 or instructor consent.

It is presumed that students will have the equivalent of 1 year of college-level programming in some high-level language such as Python or Java prior to taking this course. The C programming language will be introduced but not at an introductory level so prior programming experience is a must.

1.3 Course Goals

Students that complete CSCI 2041 will posses the following characteristics.

  • Basic proficiency in a high-level programming language that facilitates functional programming, typically an ML variant like OCaml or a Lisp variant like Clojure. Ability to edit, compile, run, and debug functional programs.
  • An understanding of the advantages and disadvantages of types in programming languages: organization of program data into types, common bugs eliminated by strong type systems, limitations of type systems.
  • An understanding of the importance of polymorphism in programming language types particularly with respect to data structures that organize arbitrary kinds. Knowledge of how languages provide flexibility through polymorphism in type systems.
  • The ability to employ functions as first-class values in common higher-order computation patterns such as mapping, reducing, and filtering.
  • An understanding of the advantages and disadvantages of side-effect free "pure" functions in computation versus computations based on explicit mutation and state change.
  • A strong knowledge of how recursive functions perform and solve problems on data structures and search problems. Knowledge of tail recursion optimizations and its relation to iteration.
  • Familiarity with program organization mechanisms such as modules, namespaces, private internals, classes, and nesting.

1.4 Instructor

Name Chris Kauffman
Sections 001
Email kauffman@umn.edu
Office Keller 6-198
Phone 612-626-7510

1.5 Teaching Assistants

Name Email Role
Anas Saeed saeed044@umn.edu GTA
Karthik Buddha buddh009@umn.edu GTA
Yifan Hu huxxx988@umn.edu GTA
Benjamin Rohlfing rohlf060@umn.edu UTA
Charles Harper harpe334@umn.edu UTA
Ian Kariniemi karin010@umn.edu UTA
Jacob Elafandi elafa009@umn.edu UTA
Joseph Blanchard blanc317@umn.edu UTA
Julie Yuan yuanx254@umn.edu UTA
Marek Pierepiekarz piere008@umn.edu UTA
Nathan White whit2267@umn.edu UTA
Nicholas Stalter stalt007@umn.edu UTA
Noah Omdal omdal007@umn.edu UTA
Samantha Seifert seife178@umn.edu UTA
Tasha Bornemann borne038@umn.edu UTA
Vincent Knauss knaus039@umn.edu UTA
Yuyang Xiao xiao0153@umn.edu UTA
Manu Padma padma017@umn.edu UTA
Chase Bowen bowen198@umn.edu UTA
Jessie Speert speer034@umn.edu UTA
Yongle Zhang zhan5262@umn.edu UTA
Sam Matenaer maten009@umn.edu UTA
Rui Zuo zuoxx067@umn.edu Resigned

1.6 Lectures and Lab

Meeting Day/Time Location
Lecture (001) M,W,F 09:05 AM - 09:55 AM Bruininks 230
Laboratory (002) M 05:45 PM - 06:35 PM Keller 1-250
Laboratory (003) M 06:50 PM - 07:40 PM Keller 1-250
Laboratory (004) T 08:00 AM - 08:50 AM Keller 1-250
Laboratory (005) T 09:05 AM - 09:55 AM Keller 1-250
Laboratory (006) T 10:10 AM - 11:00 AM Keller 1-250
Laboratory (007) M 07:55 PM - 08:45 PM Keller 1-250
Lecture (010) M,W,F 01:25 PM - 02:15 PM Fraser 102
Laboratory (011) T 11:15 AM - 12:05 PM Keller 1-250
Laboratory (012) T 12:20 PM - 01:10 PM Keller 1-250
Laboratory (013) T 01:25 PM - 02:15 PM Keller 1-250
Laboratory (014) T 02:30 PM - 03:20 PM Keller 1-250
Laboratory (015) T 03:35 PM - 04:25 PM Keller 1-250
Laboratory (016) T 04:40 PM - 05:30 PM Keller 1-260

1.7 Reading Materials

There is no required textbook for the course. Readings will be posted and available online and will be largely drawn from free / online sources.

Below are some optional reading materials that will be suggested

OCaml System Manual, Release 4.07 (Optional)
The official manual for OCaml, it gives a brief but complete outline of the language, tools, and standard library. It is freely available here: http://caml.inria.fr/pub/docs/manual-ocaml/
Practical OCaml by Joshua B Smith (Optional)
A solid introduction to OCaml for folks who already know some programming. Available via the library
Real World OCaml by Yaron Minsky, Anil Madhavapeddy, Jason Hickey (Optional)
A somewhat more complex introduction intro to OCaml. Some of the tools and conventions used will be different from those in class but this text provides an alternative perspective and presenetation of some concepts. Available free online here: https://v1.realworldocaml.org/

1.8 Computing Resources

It is assumed you will have access to a computer with the ability to edit, compile, and run OCaml programs. Some university labs provide this ability; the first week of the course will cover how to set up your personal environment as well. If you have difficulty accessing a suitable environment, contact the course staff.

You will need to create a CSE Labs account for use on assignments and during Discussion. Accounts can be created here: https://wwws.cs.umn.edu/account-management/

1.9 Communication

  • Canvas is used for project submission and to post grades. The course Canvas is available here: https://canvas.umn.edu/courses/73791
  • Gradescope will be used for exam grading and disputes. Students will receive an invite to view their exam grades.
  • Piazza is the central site for our announcements and discussion board. The announcements and discussion board are part of the required reading for the course.
    • Sign up for our piazza site here: http://piazza.com/umn/fall2018/csci2041
    • All instructors and TAs can view all material on Piazza
    • Do not e-mail course staff about programming problems; use the discussion board.
    • Use public posts on Piazza to discuss programming project requirements, labs, and other material related to the course.
    • When prompted by a TA, use private posts on Piazza to share portions of your code pertaining to your questions. Don't share your project code in public posts.
    • Refer to the Piazza main page for etiquette on what should be posted publicly versus privately.
    • Email course staff only for logistical issues such as meeting outside of office hours, missing lab/lecture, grading disputes, medical situations, etc.
  • Office Hours will be posted on the course Canvas and Piazza sites. Office hours for all staff are open to all students in any section of the course governed by this syllabus.

2 Coursework

2.1 Lectures

During lectures we will discuss concepts and instructors will provide demos relevant to other course work. In addition to attending the regular meeting times, you are strongly encouraged to visit the professor and teaching assistant(s) during office hours to further your understanding of the material: we are here to help you learn.

2.2 Textbook / Readings

Assigned readings relevant to each lecture are listed in the schedule. You will increase your understanding of lectures by reading associated textbook sections ahead of time, though this is not assumed. We may provide additional reading material which will be posted on the course web page.

2.3 Lab Sections

Lab sections meet once per week and attendance is optional but encouraged. In each meeting, the lab leader will guide students through exercises to reinforce course concepts. These exercises are required and worth a small portion of the overall grade for the course. Students are encouraged to freely collaborate on lab exercises which are usually due a few days after the lab meets.

2.4 Assignments / Projects

Students will receive a number of homework assignments during the semester. These will be a combination of programming, analysis, debugging, and problem solving. Unless otherwise stated, assignments will require individual work with no collaboration allowed. Pay careful attention to the guidelines for each assignment. Assignments are usually large and require a significant amount of work to complete.

2.5 Exams

There will be a series of midterm exams during the semester. Exams take place during the regularly scheduled lecture period and are worth a significant portion of the overall course grade. There will also be a comprehensive final exam at the end of the semester. Refer to the schedule for dates of the exams.

3 Grading Policies

3.1 Graded Components

Final grades will be determined by scores obtained on the components below according to their associated weight.

Component Weight Policy
Collaborative Lab Exercises (14) 10% Drop two lowest scores
Individual Assignments (5-7) 20% No drops
Midterm Exams (3 x 15%) 45% No drops
Final Exam 25% Comprehensive

3.2 Final Grade Determination

Final grades will be assigned without rounding according to the following criteria.

Percent Grade Percent Grade Percent Grade Percent Grade
>= 93 A 87-89 B+ 77-79 C+ 65-69 D+
90-92 A- 83-86 B 73-76 C 60-64 D
    80-82 B- 70-72 C- <60 F

If circumstances require it, the grading scale may be adjusted, generally in the students' favor.

3.3 Lab Exercises Grading

No late submissions for Lab Exercises will be accepted. Missing the deadline results in 0 credit. The two lowest scores on Lab Exercises will be dropped in final grade calculations

Attendance at the first lab meeting is mandatory. Attendance at the remaining labs is encouraged but optional.

In order to receive full credit for completing Lab Exercises, students must fulfill two requirements.

  • Check-off 30%: Demonstrate to a TA that a student understands answers to questions. This must be done in person in groups of one or two. Check-offs can happen during the lab period of during a TA office hour.
  • Submit 70%: Submit required files according to the lab instruction. This can be done at any time and from anywhere with a network connection. Submitting does not require attending lab. All students must submit files even if they were checked off in a group during lab.

Students may collaborate with other students in our section(s) of the course to complete exercises and are encouraged to do so. Submitting identical code for exercises is acceptable so long as you adhere to the PRIME DIRECTIVE.

3.4 Assignment Grading

Rules for collaboration on assignments are indicated in the assignment specification and usually involve NO collaboration with other students. Utilize the discussion board and office hours of course staff if you have questions about the projects.

Assignment grading will include the following elements for grading.

  1. Manual Inspection: Assignments will include a checklist of features of completely correct answers. These usually comprise things that cannot be easily checked automatically such as showing the process to reach an answer, inclusion of key elements of an answer, or style aspects of computer code. These features will be checked by graders and assigned credit based on level of compliance.
  2. Automatic Testing: Some assignments may have automatic tests provided which check for correctly functioning programs or answers. In most cases, these automatic checks will be publicly available for use while working on the assignment.

3.5 Late Assignment Submission

Late submission of assignments is governed by the following.

  • On-time assignments receive no penalties
  • Assignment more than 48 hours late are not graded and receive 0 credit
  • Assignments submitted 1-24 hours late are capped at 75%
  • Assignments submitted 25-48 hours late are capped at 50%
  • Students can Day-Late Tokens to "buy back" the late caps
  • Students can use up to 3 Day-Late tokens during the semester
  • On submitting late, up to two tokens are automatically charged to the student which will "buy back" a higher max score.
  • Token charges happen automatically and require no communication:
    • Submitting 1 day late will automatically charge 1 token
    • Submitting 2 days late will automatically charge 2 tokens unless only 1 token remains
  • Each unused token is worth 0.25% bonus credit overall in the course so submitting on time confers benefit at the end of the course
  • To avoid penalties and losing tokens, submit on time.
  • The table below gives examples of when an assignment is submitted, whether penalties apply, how tokens are charged, and their effects on assignment scores
    Pre- #Used #Used Post-      
    Token Tokens Tokens Token Raw Penalized  
Ex# Submitted Max Before After Max Score Score Comments
1 On-time 100% 0 0 100% 93 93 On-time means:
2 On-time 100% 0 0 100% 68 68 1. No tokens lost
3 On-time 100% 0 0 100% 46 46 2. No penalties
4 1-24 hours late 75% 0 1 100% 93 93 1 token used, max 100%
5 1-24 hours late 75% 3 3 75% 93 75 No tokens remain, max 75%
6 1-24 hours late 75% 2 3 100% 68 68 1 token used, max 100%, no benefit
7 1-24 hours late 75% 3 3 75% 68 68 No tokens remain, max 75%
8 25-48 hours late 50% 0 2 100% 93 93 2 tokens used, max 100%
9 25-48 hours late 50% 2 3 75% 93 75 1 token used, max 75%
10 25-48 hours late 50% 3 3 50% 93 50 No tokens, max 50%
11 25-48 hours late 50% 1 3 100% 68 68 2 tokens used, max 100%
12 25-48 hours late 50% 2 3 75% 68 68 1 token used, max 75%
13 25-48 hours late 50% 3 3 50% 68 50 No tokens, max 50%
14 >48 hours late 0% 0 0 0% 93 0 Not accepted or graded
15 >48 hours late 0% 1 1 0% 68 0 Not accepted or graded
16 >48 hours late 0% 3 3 0% 46 0 Not accepted or graded

3.6 Exam Policies and Grading

  • Your U-CARD is required for all exams. You may be asked to show ID on handing your exam in to verify your identity.
  • Missing an exam results in a zero score and make-up exams will be considered only in situations involving death, injury, or disease. Proof of such circumstances will be required for a make-up to be considered.
  • Open Resource Exams: Unless otherwise specified, exams will be open resource: notes, textbook, editor, compiler, and any code the student finds useful is allowed to be used. No communication is allowed during the exam (no email/texting/chat), no Internet searches are allowed, and no unauthorized web sites may be visited. If in doubt, ask about specifics before or during the exam.

3.7 Grading Disputes

Disputes should be raised respectfully either in person or via e-mail. If it is not possible to reach a resolution, the professor may be contacted by the grader to resolve the dispute. Assignment grading feedback will always include the grader who should be contacted first.

  • Assignments: Contact your grader
  • Lab work: Contact your grader
  • Exams: Exam feedback will be distributed on Gradescope. Use the "Request Regrade" mechanism there to raise an issue with the staff member that graded your work. This policy was edited from its original version.

If contact has not been initiated 1 week after a grade is posted, the chance to contest the grade is forfeited.

3.8 Bonus Credit

Bonus credit will be awarded based on participation in class discussions in lecture. Students may elect to sit in the first few rows of the room ("hot seats") and answer questions. Reasonable effort on answering questions in class will garner class participation credit. Participation points may also earned for involvement in the class discussion board such as giving suggestions to students with questions (but not revealing answers wholesale). The highest point winner at the end of the semester will receive a 3% bonus to their overall score in the course. All other students will receive a bonus proportional to the highest point winner. For example, someone tied with the highest point scorer will also receive a 3% bonus while someone with half the participation points will receive a 1.5% bonus.

A small amount of bonus credit also available for unused Day Late Tokens at the end of each semester.

4 Academic Integrity

PRIME DIRECTIVE: Be able to explain your own work including homework answers, program code, and exam solutions. The work you submit should be the product of your own effort and reflect your personal understanding.

Nearly all cheating in programming can be averted by adhering to the PRIME DIRECTIVE. Students may be asked at any time to explain code or exam solutions they submit. Inability to do so will be construed as evidence of misconduct. More specific guidelines are given below.

4.1 Thou Shalt Not

Unless otherwise specified, all assignments and exams in this course are individual efforts involving no unfair collaboration. For the purposes of this course, the following actions constitute scholastic misconduct (cheating) and will be reported.

  • Directly copying someone else's solution to a problem, including student solutions from a previous semester
  • Directly copying an answer from some outside source such as the Internet or friend for a problem.
  • Making use of an Instructor Solution manual to complete problems.
  • Submitting someone else's work as your own.
  • Paying someone for a solutions to assignments.
  • Posting solutions to any web site including public posts to our course web site.
  • Collaborating or copying the work of others during an exam.
  • Taking another student's code with or without their consent.
  • Aiding or abetting any of the above.
  • Witnessing any of the above and failing to report it to an instructor immediately.

Refer to the following links for additional information.

4.2 Penalties

Any instance of misconduct that is detected will be referred to the honor board and will likely result in failing the course. Be advised that the teaching team will be employing electronic means to detect plagiarism. This is extremely easy with computer code so keep your nose clean.

4.3 Fair Collaboration

The purpose of this course is to learn about programming and learning from one another is a great help. To that end, the following actions will NOT be considered cheating in this course.

  • Collaboration on Lab Exercises is allowed and encouraged. These are a great opportunity to help one another on work that counts towards your final grade. Just make sure that you understand any solutions you submit as per the PRIME DIRECTIVE.
  • Discussing assignments/projects at a high level with other course students is fair so long as no code is shared. Take great care at the point of directly showing your work to others as your answers are subsequently out of your own control.
  • Asking public questions on the course discussion board so long as limited information about your own solution is included. To convey details of your solution, use private posts.
  • Asking any course staff member questions in person or online is acceptable and encouraged. Staff members may initiate small group discussions in which collaboration is fine.
  • If you are unsure whether a given collaboration is fair or not, stop the activity and clear it with your instructor.

At all times keep the PRIME DIRECTIVE in mind when studying with another student. The above collaborations should be limited to getting someone over a hurdle, not carrying them across the finish line.

5 General Policies

General university policies which apply to our course are listed here: https://policy.umn.edu/education/syllabusrequirements-appa

Summaries of those policies are below.

Students are expected to maintain a high level of civility for all participants in and out of class meetings. This includes respecting participants of all genders, ethnicities, and social backgrounds. Harassment of any type will not be tolerated and failure to behave in a respectful manner will be reported to the University.

Observance of religious events will be accommodated for students of any faith. All possible accommodations will be made for students with disabilities. Please contact the Disability Resource Center and the instructor for further information.


Author: Chris Kauffman (kauffman@umn.edu)
Date: 2018-09-28 Fri 14:38