CSci 2041: Advanced Programming
Principles
Afternoon Section, Fall 2017
4 Credits
Lecture: MWF 1:25-2:15, Anderson
370
Labs:
Section 14: T 1:25-2:15, Keller 1-250
Section 15: T 2:30-3:20, Keller 1-250
Section 11: T 3:35-4:25, Keller 1-250
Section 12: T 4:40-5:30, Keller 1-250
Instructor:
Nick Hopper
Keller 4-211
hoppernj AT umn edu
TAs: Course
Staff are listed in Moodle.
Office Hours:
Office hours are shown on the
course google calendar - note that there may be some changes from week
to week, so check that you are looking at the current week:
If you want to speak with
one of us about the course and can't make one of the scheduled times,
please send an email
and we'll schedule a different meeting.
Textbooks:
There is no required textbook for the course; however, the course
schedule will include links to required online readings and
notes. Many of the readings come from the unpublished manuscript "
Introduction
to Objective Caml," by Jason Hickey, which is available at no cost
online;
another free online reference that students might find helpful is "
Developing
Applications with Objective Caml" by Chailloux, Manoury and Pagano.
Course Overview:
The course is roughly divided
into three
units:
- Functional Programming in OCaml:
We'll learn the basics of structuring a program as a series of
(possibly) recursive expressions to be evaluated, examine the
relationship between general recursion, tail recursion, and iteration;
discuss using OCaml's strong static type system to build types that
match the data while abstracting away the representation of these data;
examine parametric polymorphism and higher-order types, and learn about
higher-order functions and their applications in programming.
- Analysis and Manipulation of
Programs We'll discuss the role of induction in reasoning about
recursion and iteration, both to analyze correctness and efficiency of
programs; further examine computation as expression evaluation; explore
the use of lazy evaluation to compute with cyclic and infinite data
objects; and explore programmatic representation and manipulation of
programs.
- Advanced Program Structures
We'll learn about modularity in programming and OCaml's rich
module system; techniques to express programs as units to be evaluated
concurrently and in parallel; Side effects, type-safe references and
iterative computation structures; and automated memory management in
OCaml - how objects are laid out, created and collected when no longer
needed.
Goals and Objectives:
Students who complete this
course should be able to:
- Write OCaml expressions for common programming tasks involving
iteration and recursion
- Understand common OCaml type errors and explain what they mean
- Develop simple abstract data types in OCaml
- Apply common higher-order functions to solve tasks involving
iteration
- Prove the correctness of simple recursive OCaml programs using
inductive data types
- Reason about and write programs that evaluate and transform
program expressions
- Explain and use OCaml modules
- Explain side effects, references, and simple memory management
concepts
A word about
proofs. You may
have noticed that the word "prove" plays a prominent role in this
syllabus;
you might guess this means proofs will play a prominent role in this
course. Many students in computer science believe they are "bad
at proofs." If you have done well in CSci 11X3 and 19X3 proofs should not
scare you.
You may not have realized this
before, but proofs
are
programs. This is true in many senses: metaphorically, in
that a proof
is just a list of steps to convert an input (a set of assumptions) into
an output, i.e.,
the conclusion; literally, in that many of the proofs in this class
involve reasoning
about programs; and in a very technical sense, a branch of logic known
as constructive
type theory actually establishes a one-to-one mapping between each
program and the proof
of some theorem. So if you learned to write good programs, you can
learn to write proofs
well. Ask yourself this: were you always good at writing
programs? Probably not.
How did you get better? By practicing, and seeing lots of examples of
good programming. In
this class, you will practice writing proofs; the textbook and lecture
notes for
the class will feature many examples of proofs.
Prerequisites:
The prerequisites for this
course are CSci 1913/1933 and CSci 2011. From CSci 11X3 and 19X3
you will need to understand programming
concepts like procedural abstraction, iteration and data
abstraction. From CSci
2011 you will need to understand concepts like sets, relations,
functions, and mathematical induction.
Lecture Schedule:
The course website includes a
schedule of lectures for this course.
The schedule includes the readings related to each class. Students
are responsible for reading the appropriate materials for each
lecture; we may not cover all of the reading material in the lecture
but it may still be required for exams or homework. Lecture slides will
usually be linked
from the homepage before class, but always within one day following the
corresponding lecture.
Grading:
Grading for the class will be
based on five components:
- 7 Homeworks (25%): we
will have seven homeworks, all of which will be due on Wednesdays.
The submission of any homework should be completed by 11:59pm on the Wednesday that it is due.
Due dates for all assignments are strict: all homeworks must be pushed at or before the specified time in
order to receive full credit. Late homeworks turned in within 24 hours
of the due date will be considered for 50% credit, and after that, a
homework is worth 0 points, with no exceptions. More information
about the protocol for submitting the homework and grade assignments
will be included in each homework. Note that if you have not
correctly followed the submission instructions on a given homework by
the time it is due, this will count as a late homework, and if you have
not correctly submitted a homework by the late submission cutoff, then
you will receive 0 points for the homework.
Homework grading is performed by the TAs. If you have a question about
homework grades, address it to the TAs. Only if something wholely
unreasonable has occurred will the instructor intervene.
Furthermore, there is a limit of seven days from the date that an
assignment is graded for grading problems to be dealt with. After that
period, such will not be considered.
Because everyone can have a bad week, each student's six highest homework scores will be used.
- 15 Labs (15%):
Lab work will be graded on attendance and participation, and must be
submitted by 11:59pm on the Thursday following each lab section.
- 15 Weekly Exercise Sets (10%):
Each week we will have a list of "exercise" questions similar to
problems in the lectures. Solutions must be submitted by
11:59am on Monday to receive full credit for the week's exercises.
- 12 Weekly Quizzes (25%
total): We will have a 20-minute quiz at the end of lecture each
Monday, with two exceptions noted on the class schedule. Each quiz can
cover any material up to the end of lecture on the preceding Friday. To
account for travel, illness, traffic and life's other difficulties that
might occur during the semester, each student's ten highest quiz scores
will be used.
- Final exam (25%): The
course will have a cumulative, 2-hour final exam on Monday, December 18 at 8am.. The exam is
closed-book, closed-notes, and no electronic devices may be used.
However, each student may bring a one-sided single-page "cheat sheet"
for use during the exam.
Composite scores will be
assigned to
grades as follows:
92
- 100
|
A
|
90
- 92
|
A-
|
86
- 90
|
B+
|
82
- 86
|
B
|
80
- 82
|
B-
|
76
- 80
|
C+
|
70
- 76
|
C
|
66
- 70
|
C-
|
63
- 66
|
D+
|
59
- 63
|
D
|
0
- 59
|
F
|
The dates for all quizzes,
homeworks and the final exam are currently marked on the class
schedule. Please be sure to make note of them, because there
will be no makeup exams, except in extraordinary and documentable
circumstances.
Academic
Integrity Policy:
Every student is expected to
turn in his or her own work for all assignments and exams in this
class. This is not meant to block
general discussion of HOW to approach homework problems: you are
encouraged to discuss questions that clarify what the problems on the
homework are asking, ask about possible errors in the problem
descriptions, clarify what is expected of your solutions, and what
resources you can use (for example) on the class forum. However,
it is important that you do not proceed to discuss solutions to the
problems and it is certain that sharing or copying another student's
solution, (or from another source such as the Internet) whether on an
exam or homework, is prohibited. Note that while it might be
tempting to think that you can take another person's code, modify it a
little and turn in a solution that does not look like the original,
there are several tools that can detect when this has been done and we
will be using such tools in this class. If we determine that you have
submitted such code, we will treat this as an instance of scholastic
dishonesty.
The University Student Conduct
Code defines scholastic dishonesty as:
submission of false records of academic achievement; cheating on
assignments or examinations; plagiarizing; altering, forging, or
misusing a University academic record; taking, acquiring, or using test
materials without faculty permission; acting alone or in cooperation
with another to falsify records or to obtain dishonestly grades,
honors, awards, or professional endorsement. In this course, a student
responsible for scholastic dishonesty will be assigned a penalty of an
"F" or "N" for the course. If you have any questions regarding the
expectations for a specific assignment or
exam, or are unsure about posting a particular answer to the class
forum, please ask us first.
The Disability Resource Center
The University of Minnesota is committed to providing all students
equal access to learning opportunities. The Disability Resource Center
(DRC) is the campus office that works with students who have
disabilities to provide and/or arrange reasonable accommodations.
- Students who have, or think they may have, a disability (e.g.
mental health, attentional, learning, vision, hearing, physical or
systemic), should contact DRC to arrange a confidential discussion at
612-626-1333 (V/TTY) or ds@umn.edu.
- Students registered with DRC and who have a letter requesting
accommodations, are encouraged to talk to me early in the semester to
discuss accommodations outlined in the letter.
Mental Health Resources
As a student you may experience a range of issues that can cause
barriers to learning, such as strained relationships, increased
anxiety, alcohol/drug problems, feeling down, difficulty concentrating
and/or lack of motivation. These mental health concerns or stressful
events may lead to diminished academic performance or reduce your
ability to participate in daily activities. University of Minnesota
services are available to assist you with addressing these and other
concerns you may be experiencing. You can learn more about the broad
range of confidential mental health services available on campus at
http://www.mentalhealth.umn.edu.
