Description
This course teaches imperative programming in a C-like language and
methods for ensuring the correctness of imperative programs. It is
intended for students who are familiar with elementary programming
concepts such as variables, expressions, loops, arrays, and
functions. Given these building blocks, students will learn the
process and techniques needed to go from high-level descriptions of
algorithms to correct imperative implementations, with specific
applications to basic data structures and algorithms. Much of the
course will be conducted in a subset of C amenable to verification,
with a transition to full C near the end.
This will be accomplished along three dimensions:
-
The main skill you will get out of this course is the ability to
write code that is correct by design and accounts for the needs of
its application context. You will learn about deliberate
programming as a way to write high quality code, about assessing the
performance of a program, and about comparing solutions to satisfy
deployment constraints.
-
As you do so, you will gain exposure to fundamental concepts in
Computer Science — as opposed to programming — such as
abstraction, correctness, complexity, and modularity. This will
also give you a vocabulary to communicate effectively and precisely
with other computer scientists.
-
Our vehicle for achieving these objectives will initially be C0, a
safe variant of C, and later C itself. Using them, you will gain
exposure to a number of data structures and algorithms that are used
pervasively in computer science. C is the language of choice for
system-level applications, and both are representative of the popular
imperative programming paradigm.
After completing 15-122, you will be able to
take
15-213
(
Introduction to Computer
Systems),
15-210
(
Parallel and Sequential Data Structures and Algorithms)
and
15-214
(
Principles of Software System Construction). Other
prerequisites or restrictions may apply.
Prerequisites
You must have gotten a 5 on
the
AP
Computer Science A exam or
passed
15-112
(
Fundamentals of Programming) or equivalent. You may also
get permission from an advisor if you performed very high on the CS
Assessment on Canvas.
It is
strongly advised that you either have taken or take at
the same time
either
21-127
(
Concepts of Mathematics)
or
15-151
(
Mathematical Foundations of Computer Science): historically,
students who did not do so ended up learning less, spending
considerably more time on the course and earning one letter grade
lower than their peers who did, on average.
Past Offerings
How to do Well in this Course
Our goals are for you to succeed in this course and to teach you
skills and concepts that will contribute to your success in life. To
this end, we are providing you with lots of resources and the
knowledge that comes from years of experience. Talking to some of the
thousands of students who took this course before you, here's some
advice that they found particularly useful:
-
Do not stress over grades: your goal is to learn new and
exciting things. Good grades follow naturally from deep learning
(but not necessarily vice versa). ...and employers care about what
you know not what grade you got.
-
Participate: you will get a lot more from this class if you
ask questions and engage with the course staff than if you are a fly
on the wall — and it will be more fun.
-
Manage your time wisely: allocate sufficient time for
homework and learning. Little adjustments can save you a whole lot
of time later and have a huge impact on your performance. In
particular, use class time to learn, review the material presented
in lecture the same day, and schedule time for homework
proactively.
-
Start homework early: racing against a deadline is so
stressful! Starting early will remove that stress, lead to deeper
learning and give you time to improve your solution if you feel like
it.
-
Get all the help you need: we provide plenty of resources
to help you succeed in this course
— office hours every
day, online help 24-7,
and friendly staff when you need them.
Take advantage of them: they are there for you! The only thing we
ask is that you plan a bit ahead: helping students takes time and
there are not enough of us if everybody waits up to the deadline.
-
Make time for fun: take a break from studying at least once
a day — meet with friends, go for a walk, play sports,
whatever gets you to reset your mind.
Feedback
It is our goal to make this course successful, stimulating and
enjoyable. If at any time you feel that the course is not meeting
your expectations or you want to provide feedback on how the course is
progressing for you, please
contact
us. If we are not aware about a problem, we won't know to
fix it. If you would like to provide anonymous comments, please
use
the feedback form on the course home page
or slide a note under our doors.
Resources
Course Material
There is no textbook for this course. Lecture notes and other
resources are provided through
the
Schedule tab of this page and
on
. We do not require
students to read lecture notes before lecture, but those who are
interested in reading ahead can certainly do so.
The C0 Language
In the first nine weeks, the course
uses
C0, a safe subset of C
augmented with contracts. This language has been specifically
designed to support the
learning objectives in this
course. It provides garbage collection (freeing students from
dealing with low-level details of explicit memory management), fixed
range modular integer arithmetic (avoiding the complexities of floating
point arithmetic and multiple data sizes), an unambiguous language
definition (guarding against undefined behavior), and contracts
(making code expectations explicit and localizing reasoning).
The C Language
In the last five weeks, the course transitions to C in preparation for
subsequent systems courses. Emphasis is on transferring positive
habits developed with the use of C0, and on practical advice for
avoiding the pitfalls and understanding the idiosyncrasies of C. We
use the
valgrind tool to
test proper memory management.
Programming Environments
You are welcome to use any programming environment that suits you to
write your programming assignments. However, all programming
homework will be graded by running them on a Unix system
using — you may want to make
sure they work
on Andrew
Unix. Popular environment choices
include VSCode, emacs
and vim, but you should use what
works for you: an environment that allows you to write code quickly
and efficiently. Here are some useful links:
Grading
This is a
12 unit course.
Tasks and Percentages
- 25 homework assignments: 36%
- 13 weekly practice problems (due
on Thursdays at 6pm
Pittsburgh time — strict!)
- 12 weekly programming assignments (due on Sundays at 9pm Pittsburgh time — strict!)
To encourage good work and integrity, the instructors may invite
students to their offices to explain their solutions. Should this
happen, the students' explanations will become part of their grades
for that homework.
- 12+1 check-ins: 36% (in class, closed books,
Tuesdays at 7:00pm or 7:45pm depending on section). The last
check-in of the semester is optional and may be used to
replace the grade of an earlier check-in.
- Final exam: 25%, 3 hours, closed books, on
- Precepts and activities: 3%
Each precept is worth 2.5 points given out based on effort and
rough correctness.
There will be one activity worth 0.5
points during or after each lecture. Use
the activities page to test your
configuration and do the current activity (when there is one).
The precepts and activities grade is calculated based on the bucket
system: All you need to earn the full 3% grade for this
portion of the course is to accumulate 30
points overall. There are many more points than that
for grabs, so no sweat if you miss a precept or a lecture. Do the
math: the course has
- 12 graded precepts
- 26 lectures
We are aiming to have homework and check-ins graded within
two days of submission.
Accessing and Monitoring your Grades
Posted grades are accessible by clicking on the
Grades
tab of this page. After authenticating, you will be able to see your
current grades and a projection of where you are headed given your
past performance in the class. Use this application to take action if
the trajectory does not lead to the grade you are hoping for.
Evaluation Criteria
Your assignments and exams are evaluated on the basis of:
-
Correctness: Your arguments should make sense, your proofs
should be valid, and your program should work in the reference
environment.
-
Elegance: Written material should be of the same quality as
what a professional would write. No typos, no bad grammar, clarity
is paramount. You are also expected to write code with good
programming style. See the Guide
to Success on Coding with Style about what constitutes
good style.
For a small subset of assignments, the course staff will review all
final submissions by hand. If there are significant style issues,
they may give a non-passing grade on style, accompanied by a “FIX
STYLE” annotations in their notes. Students who are told to fix
their style must address these issues and discuss their revisions
with a TA within 5 days of the homework grades being
posted. Any TA or instructor can do style re-grading at
any office hour; you do not have to go
to the TA that assigned the grade.
Late Policy
This is a fast-paced course. The late policy has the purpose to help
students from falling behind.
Aside from this, there will be no extensions on assignments in
general. If you think you really
really need an extension on
a particular assignment,
contact the
instructors as soon as possible and before the deadline.
Please be aware that extensions are entirely discretionary and will be
granted only in exceptional circumstances outside of your control
(e.g., due to severe illness or major personal/family emergencies, but
not for competitions, club-related events or interviews). The
instructors will require confirmation from University Health Services
or your academic advisor, as appropriate.
Nearly all situations that make you run late on an assignment
can be avoided
with proper planning
— often just starting early. Here are some examples:
-
I have so many deadlines this week: you know your deadlines
ahead of time — plan accordingly.
-
It's a minute before the deadline and the network is down:
you always have multiple submissions — it's foolish to wait
for the deadline for your first submission.
-
My computer crashed and I lost everything: Use Dropbox or
similar to do real-time backup — recover your files onto AFS
and finish your homework from a cluster machine.
-
My fraternity/sorority/club has that big event that is taking
all my time: Schedule your extra-curricular activities around
your classes, not vice versa.
Grade Appeals
We make mistakes too!
After each homework assignment and practice activity is graded, you
will be able to access your score by clicking on the
Grades tab of this
page. We will make the utmost effort to be fair and consistent in our
grading. If you notice any grading mistakes, proceed as follows:
-
Go to office hours and describe the
putative grading mistake to a TA.
-
If the TA does not resolve the matter convincingly, you may request
a regrade as follows:
Write an email to
explaining where and why you think there was a mistake in grading.
Make sure to specify which homework or exam this appeal is for.
Write at most 3 lines for each response you are disputing.
Email requests to the course staff will not be accepted. Please do
not make regrade requests on
.
All regrade requests must be received within 5 days of the
work being handed back on
or , which we will announce in
a post.
Final Grades
This class is not curved. However, to ensure consistency across
semesters, we set our grading standards in such a way as to compensate
for the relative difficulty of exams.
What follows is a rough guide to how course grades will be
established, not a precise formula — we will fine-tune cutoffs
and other details as we see fit after the end of the course. This is
meant to help you set expectations and take action if your trajectory
in the class does not take you to the grade you are hoping for (see
also the Grades tab on this page). So,
here's a rough, very rough heuristics about the
correlation between final grades and total scores:
- A: above 90%
- B: 80-90%
- C: 70-80%
- D: 60-70%
This assumes that the makeup of a student's grade is not wildly
anomalous: exceptionally low overall scores on programming
assignments, practice problems or check-ins will be treated
on a case-by-case basis. In particular, students who are unable to
demonstrate a basic proficiency with the C language in the last few
programming assignments will receive a D in the class (this is because
15-122 is a prerequisite to 15-213, a very C-intensive course).
Precise grade cutoffs will not be discussed at any point during or
after the semester. For students very close to grade boundaries,
instructors may, at their discretion, consider participation in
lecture and precepts, exam performance and overall grade trends when
assigning the final grade.
Academic Integrity
You are expected to comply with the
University Policy on Academic Integrity (see also
The Word and
Understanding Academic Integrity).
The university policies and procedures on academic integrity will be
applied rigorously. All students are required to fill out
a
form as part of their first assignment
indicating that they understand and accept this policy.
The value of your degree depends on the academic integrity of
yourself and your peers in each of your classes. It is expected that,
unless otherwise instructed, the work you submit as your own is your
own work and not someone or something else's work or a collaboration
between yourself and other(s).
Many students who copy code or other work do so in the heat of the
moment and regret their actions later on, when more clear-headed.
You may contact the instructors by 2pm the day after a deadline
and ask to delete your submission for
an assignment, no questions asked. Deleted submissions are not
considered when running academic integrity checks and receive a
grade of 0.
Contact us before we contact you.
The Policy (Fall'24)
Practice Problems
Practice problems are intended to be collaborative but
submissions are individual.
Specifically, you are welcome to work on any aspects of a practice
problem with other students. However, in order to ensure that the
work you submit reflects your learning, we insist that you adhere to
a whiteboard policy regarding these discussions: you are
not allowed to take any notes, files, pictures or other records away
from the discussion, nor shall you memorize answers. For example,
you may work on practice problems at the whiteboard with another student,
but then you must erase the whiteboard, stop discussing the problem,
wait some time (15
minutes is a safe heuristic) and write up your solution individually.
We take your ability to recreate the solution independently as proof
that you understand the work that you submit.
Programming Assignments
Programming assignments are strictly individual.
You may ask other students clarifications on the writeup
(e.g., "What does this sentence mean?", "Can you explain
this notation?") but you may not discusses approaches to solving
any aspect of the assignment (e.g., "How would you do
this?", "Can you walk me through an example?").
You are not allowed to refer to solutions and/or code written by
past or present students, ChatGPT or other AI-based tools, or found
on the web, not even to "double-check" your own solution. You may
not post code from this course publicly (e.g., to Bitbucket or
GitHub).
We will be using the MOSS system to detect software plagiarism.
Whenever a programming assignment is similar to a homework from a
previous course edition, we will run MOSS on all submissions from
that edition as well. All solutions from the Web are also in MOSS
— you should assume that if you were able to find it, we have
already found it.
Check-ins and the Final
Check-ins and the final exam are strictly
individual.
Studying and General Help
You are welcome to freely discuss course material (lecture
notes/slides, practice exams, precept handouts), as well as to review
graded assignments or check-ins with students taking the
course in the current semester. You may give or receive help with
computer systems, compilers, debuggers, profilers, or other facilities
(as long as answers and/or code are never visible).
You are not allowed to use any materials from previous iterations of the
course, including your own. You may not discuss or receive any help on
homework assignments with students who have previously taken the
course (excluding current TAs).
If you are uncertain whether your actions will violate this policy,
please reach out to a member of course staff to ask beforehand.
Penalties and Specifics
Please read
the University
Policy on Academic Integrity carefully to understand the
penalties associated with academic dishonesty at Carnegie Mellon. In
this class, cheating/copying/plagiarism means obtaining all or part
of a program or homework solution from another student or tool, or
unauthorized source such as the Internet, having someone else do a
homework or take an exam for you, knowingly or by negligence giving
such information to another student, reusing answers or solutions
from previous editions of the course, or giving or receiving
unauthorized information during an examination. In general, each
solution you submit (practice problem, programming assignment,
check-in or final exam) must be your own work. In the
event that you use information written by others in your solution,
you must cite the source of this information (and receive prior
permission if unsure whether this is permitted). It is considered
cheating to compare complete or partial answers, copy or adapt
others' solutions, or sit near another person who is taking (or has
taken) the same course and complete the assignment together.
For programming assignments,
working on code together, showing code to another student and
looking at another student's code are considered cheating. If you
need help debugging, make a post on or go to office hours.
It is also considered cheating for a repeating student to reuse
one's solutions from a previous semester, or any instructor-provided
sample solution. It is a violation of this policy to hand in work
for other students.
Your course instructors reserve the right to determine an
appropriate penalty based on the violation of academic dishonesty
that occurs. Penalties go from negative points in an assignmnent
all the way to expulsion from Carnegie Mellon University. If you
have any questions about this policy and any work you are doing in
the course, please feel free to contact
the instructors for help.
Repeat Students
If you took this course in full or in part in a past semester, we
ask that you delete all your previous work so you won't look
at it. In particular, copying or referencing
one's own solutions from an earlier
semester is a violation of the academic integrity policy and will be
handled as such. Doing so may save time close to a deadline but it
will not have the effect of learning the material, which will be a
serious handicap in exams and in follow-up courses.
Other Policies
Class presence and participation
Active participation by you and other students will ensure that
everyone has the best learning experience in this class. We may
take participation in lecture and precepts into account when setting
final grades. Fire safety rules require that we never exceed the
stated capacity of a classroom. For this reason, we require that
you attend the lecture, check-in slot, and precept you
are registered for.
Laptops and mobile devices
As research on learning shows, unexpected noises and movement
automatically divert and capture people's attention, which means you
are affecting everyone's learning experience if your cell phone,
laptop, etc, makes noise or is visually distracting during
class. Therefore, please silence all mobile devices during
class. You may use laptops for note-taking only, but please do so
from the back of the classroom. Do not work on assignments for this
or any other class while attending lecture or precept.
Students with disabilities
If you wish to request an accommodation due to a documented
disability, please inform your instructor and
contact Disability
Resources as soon as possible
(). Once your accommodation has been approved, you
will be able to request extra-time for each exam separately
by filling this
form a week in advance.
Getting Help
Personal Health
Take care of yourself.
Do your best to maintain a healthy lifestyle this semester by eating
well, exercising, avoiding drugs and
alcohol, getting
enough sleep and taking some time to relax. This will help you
achieve your goals and cope with stress.
All of us benefit from support during times of struggle. You are not
alone. There are many helpful resources available on campus and an
important part of the college experience is learning how to ask for
help. Asking for support sooner rather than later is often helpful.
If you or anyone you know experiences any academic stress, difficult
life events, or feelings like anxiety or depression, we strongly
encourage you to seek support. Counseling and Psychological Services
(CaPS) is here to help: call 412-268-2922 and visit
their website. Consider
reaching out to a friend, faculty or family member you trust for help
getting connected to the support that can help.
If you or someone you know is feeling suicidal or in danger of
self-harm, call someone immediately, day or night:
- CaPS: 412-268-2922
- Re:solve Crisis Network: 888-796-8226
- If the situation is life threatening, call the police:
- On campus (CMU Police): 412-268-2323
- Off campus: 911
If you have questions about this or your coursework, please
let us know.
Communication
For assistance with the written or oral communication assignments in
this class, visit the Communication and Language Support Center within
SASC.
Consultants there
can provide instruction on a range of communication topics and can
help you improve your papers and presentations. This is a free
service and open to all students. Visit the
SASC website
for more
information.
External Academic Support
The Student Academic
Success Center
is providing various services aimed at helping
students master the contents of this course. These optional
services are free and voluntary. They are led by trained personnel
who have successfully completed the course. Leaders are not members
of the course staff. These services are are designed to supplement
— not replace — class lectures and precepts. They do
not cover homework.
-
Supplemental Instruction (SI)
- is a weekly session in which the leader prepares review material
based on the current course content, but adapts the focus of the
session based on the attendees' questions and requests.
-
Drop-in Tutoring
- Students can drop in during the slot scheduled for 15-122. No
appointment is necessary, just walk-in.
- One-on-one Tutoring
- Students can book an appointment for a virtual tutoring session.
We ask that students do not seek help from upperclassmates
who have successfully completed the course. Doing so often leads to
violations of the academic integrity policy of the
course. In particular, upper-classmates found to violate this
policy will be reported and will incur a grade penalty.
Learning Objectives
Computational Thinking
Students who complete this course should be able to explain
abstraction and other key computer science concepts, apply these
fundamental concepts as problem-solving tools, and wield contracts as
a tool for reasoning about the safety and correctness of programs. In
particular, we expect students to be able to:
- develop contracts (preconditions, postconditions, assertions, and loop invariants) that establish the safety and correctness of imperative programs.
- develop and evaluate proofs of the safety and correctness of code with contracts.
- develop and evaluate informal termination arguments for programs with loops and recursion.
- evaluate claims of both asymptotic complexity and practical efficiency of programs by running tests on different problem sizes.
- define the concept of programs as data, and write programs that use the concept.
- defend the use of abstractions and interfaces in the presentation of algorithms and data structures.
- identify the difference between specification and implementation.
- compare different implementations of a given specification and different specifications that can be applied to a single implementation.
- explain data structure manipulations using data structure invariants.
- identify and evaluate the use of fundamental concepts in computer science as problem-solving tools:
- order (sorted or indexed data),
- asymptotic worst case, average case, and amortized analysis,
- randomness and (pseudo-)random number generation, and
- divide-and-conquer strategies.
Programming Skills
Students who complete this course should be able to read and write
code for imperative algorithms and data structures. In particular, we
expect students to be able to:
- trace the operational behavior of small imperative programs.
- identify, describe, and effectively use basic features of C0 and C:
- integers as signed modular arithmetic,
- integers as fixed-length bit vectors,
- characters and strings,
- Boolean operations with short-circuiting evaluation,
- arrays,
- loops (
while and for),
- pointers,
- structs,
- recursive and mutually recursive functions,
void pointers and casts between pointer types,- generic data structures using
void and function pointers,
- contracts (in C0), and
- casts between different numeric types (in C).
- translate between high-level algorithms and correct imperative code.
- translate between high-level loop invariants and data structure invariants and correct contracts.
- write code using external libraries when given a library interface.
- develop, test, rewrite, and refine code that meets a given specification or interface.
- develop and refine small interfaces.
- document code with comments and contracts.
- identify undefined and implementation-defined behaviors in C.
- write, compile, and test C programs in a Unix-based environment
using
make, gcc, and valgrind.
Algorithms and Data Structures
Students who complete this course should be able to describe the
implementation of a number of basic algorithms and data structures,
effectively employ those algorithms and data structures, and explain
and interpret worst-case asymptotic complexity arguments. In
particular, we expect students to be able to:
- determine the big-O complexity of common code patterns.
- compare common complexity classes like O(1), O(log n), O(n), O(n log n), O(n2), and O(2n).
- explain the structure of basic amortized analysis proofs that use potential functions.
- apply principles of asymptotic analysis and amortized analysis to new algorithms and data structures.
- recognize properties of simple self-adjusting data structures.
- recognize algorithms and data structures using divide-and-conquer.
- describe and employ a number of basic algorithms and data structures:
- integer algorithms,
- linear search,
- binary search,
- sub-quadratic complexity sorting (mergesort and quicksort),
- stacks and queues,
- pseudo-random number generators,
- hash tables,
- priority queues,
- balanced binary search trees,
- disjoint-set data structures (union/find), and
- simple graph algorithms.
