Overview

Successful software projects require more than just technical expertise. Figuring out what the client wants, collaborating in a team, managing complexity, mitigating risks, staying on time and budget, and determining, under various constraints, when a product is "good enough" to be shipped are equally important topics that often have a significant human component. This course explores these issues broadly and covers the fundamentals of modern software engineering and analysis.

This course focuses on software engineering and analysis. At a high level, the course is organized around five core topics:

A culminating assignment involves making a contribution to an open source project: identifying an issue, understanding the local development process, and then actually fixing a bug or adding a feature, with extra credit awarded if your contribution is merged into the project.

This course draws inspiration from Carnegie Mellon's Foundations of Software Engineering (15-313) course as well as from the insights of Drs. Prem Devanbu, Christian Kästner, Marouane Kessentini, and Claire Le Goues.

Technical Elective

This course is an upper-level CS technical elective for both CS-Eng and CS-LSA. (It does not show up in some versions of the CS-LSA Program Guide, but it does, in fact, count. Students can check their Audits to confirm.)

It is not a capstone course or a major design experience course. It focuses on individual mastery of key software engineering concepts. It does not feature a large team project.

The expected workload for this class is "moderate" — one notch harder than UI Design, but two notches easier than Operating Systems.

Attendance

This course has mandatory attendance, including in-class examinations and graded quizzes. Students will not be able to take this course and another course that meets at the same time. The lectures are recorded, but serve mostly as a review aid. You have my sympathies: I wish we were able to set the course schedule to minimize such course conflicts. (Disclaimer: the course staff are not responsible for candy-based injuries.)

Reading and Comprehension

One of the most common student complaints is about buying textbooks that are both expensive and out of date. As a result, I have structured this course so that there is no textbook and all of the readings are available on-line for free.

Because software engineering is often more engineering than science, the basic concepts are often easy to grasp but the trouble is found in the details. Questions such as "which of these methods works best in the real world?" and "what are successful companies actually doing?" are paramount. As a result, many of the readings are experience reports from companies (e.g., Microsoft, Google, etc.) or academic papers (e.g., with human studies). These detailed readings serve to flesh out high-level concepts that can otherwise be introduced via Wikipedia without costing you money.

The flip side of this is that you should actually do the reading. It will help you both in terms of understanding the lectures and also in terms of completing the assignments.

Finally, you may notice that some of the readings are marked optional. Next to each such optional reading I have included a small "advertisement" for why you might want to take a look. The optional readings are not required for any class assignments, but there may be extra credit questions on exams that reference them.

Homework Assignments

There are six homework assignments for this course. The assignments involve the electronic submission of artifacts. Some (e.g., test cases) are graded automatically and admit immediate feedback. Others (e.g., prose descriptions) are graded manually. For certain assignments it is possible to work as a team.

Grading Examinations

There will be two in-class written examinations for this course. No final examination is currently planned. Course grading will center on homework assignments and examinations. The approximate grading breakdown is as follows:

Regrade and Makeup Policy

Regrade requests for exams, assignments, or written assignments must be received within one week of you receiving your score. All regrade requests should be made via Gradescope (if a request absolutely cannot be made via Gradescope for a certain assignment, please submit it privately on the course forum). When we regrade an assignment we will look over it very carefully for correctness: it is possible that after a regrade you will end up with fewer points than before the regrade. Regrades should be treated with caution and used only when the graders have made a clear mistake evaluating your work.

If you miss an assignment deadline or in-class activity, we can be very lenient about extensions or makeups but only if you provide documentation. For example, for death or bereavement, a copy of the obituary or funeral program suffices; for illness or injury, any sort of doctor's note suffices. This policy follows that of other professors in the department. You may email EECS481Staff@gmail.com with supporting documentation (rather than posting it to Gradescope).

If you miss an assignment deadline without an approved, documented extension, you may receive no points. for that assignment. In some extenuating cases you may receive h% off, where h is the number of hours late.

The dates for the in-class examinations are posted well in advance. To request a rescheduled examination (e.g., for reasons other than a documented one as above, etc.), you must notify us via email at EECS481Staff@gmail.com (privately) at least one week before the date of the examination. Note that requests need not be granted.

All course materials submitted for a grade must be turned in by midnight on the last date listed on the course syllabus (Tue Dec 10).

The Waiting List, Course Permission, Overrides

Historically, the single most common student question about this class relates to the waiting list. The question is some variant of (or logically reduces to) "I am currently at position X on the waiting list; am I likely to get in to the class before the deadline?"

• If you are on the waiting list, you should complete any assignments and bring me any forms (e.g., SSD forms) as if you were a registered student. If you come in off the waiting list, all of the assignments are due for you at the usual time, with no extension.
• If you are on the waiting list and do not have access to the Autograder or Gradescope submission websites, please email the course staff.
• It is my firm intention to fill the class up to the enrollment limit with students from the waiting list, in order. There are two relevant details:
  1. Obnoxiously, the system keeps two separate orderings: one for the lecture and one for the discussion sections. We try to use the lecture ordering.
  2. The undergraduate advising office may direct that certain students be let in (or swapped between electives or sections or whatever) so that everyone can graduate on time. This is basically the only reason we would not use the default waiting list ordering.
• For various reasons, students are let in to this course every few days, in batches, not every minute. If you are first on the waiting list and the course is currently at 99/100, rest easy: you will be let in to the course in the next batch.
• Although your apparent deadline to sign up for courses is Day X, if you are on the waiting list for this class and a slot opens up after that date, you will still be added. Punam Vyas, the Course Scheduling Coordinator, adds students to this class manually from the waiting list, and she has the power to add students after Day X even though you do not. Yes, it is scary to trust that you will be added to a course after the manual student deadlines.
• If you are a graduate student, know that the EECS undergraduate advising office policy is that graduate students only be allowed to take the course for credit after all undergraduates are off the waiting list. There is a special list the graduate students can sign up on; contact the CSE Undergraduate Advising Office (ugadmin@eecs.umich.edu) for more information. (This is not the policy I, personally, would make, but it is the current policy. Yes, this makes it very unlikely for a graduate student to take this class for credit.)
• Regardless of your enrollment status, you are welcome to sit in on the class. Anyone who is interested may attend the lectures.

Now, for the most common student question:

• The first time this class was offered, it started with 100/100 students enrolled and 60 on the waiting list. By the time things settled down, we ended up with 102/100 students enrolled and 20 on the waiting list (i.e., 20 who did not get in). (The "extra" students relate to that advising office exception detailed above.)
• The second time this class was offered, it started with 120/120 students enrolled and 22 on the waiting list. It ended with 118/120 and 0 on the waiting list.
• The third time this class was offered, it started with 154/154 students enrolled and 58 on the waiting list. At the add/drop deadline, it had 153 students enrolled and 0 on the waiting list.

There is really no other information I can tell you. Because of our policy of letting people in directly off the waiting list, all questions that sound similar to "what are my odds of getting in from position X?" or "should I stick with this class even though I am at slot Y on the waiting list and there are Z days left?" logically reduce to "what are the odds that K other people drop the class?". This is because once the class is full we only let another student in when someone drops. So questions about you adding are really questions about someone else dropping.

Unfortunately, I cannot predict the future. I have no special insight here (i.e., it has never happened that a student has said to me "I plan to drop in X days but won't drop today", so I do not have any secret information about the plans of other students). The best we can do is use the past to predict the future (see raw data above).

In the past the instructor spent multiple hours going over this with individual students; going forward, all waiting list questions will be directed here. No additional information is available.

Research

Your class work might be used for research purposes. For example, we may use anonymized student assignments to design algorithms or build tools to help programmers. Any student who wishes to opt out can contact the instructor or teaching assistant to do so after final grades have been issued. This has no impact on your grade in any manner.

Students interested in considering undergraduate research should make an appointment to talk about it. I am happy to discuss independent study projects, senior projects, paid research work over the summer, research work for credit, and graduate school.