Data structures play a central role in modern computer science. You interact with data structures even more often than with algorithms (think Google, your mail server, and even your network routers). In addition, data structures are essential building blocks in obtaining efficient algorithms. This course covers major results and current research directions in data structures:
TIME TRAVEL | We can remember the past efficiently (a technique called persistence), but in general it's difficult to change the past and see the outcomes on the present (retroactivity). So alas, Back To The Future isn't really possible. |
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GEOMETRY | When data has more than one dimension (e.g. maps, database tables). |
DYNAMIC OPTIMALITY | Is there one binary search tree that's as good as all others? We still don't know, but we're close. |
MEMORY HIERARCHY | Real computers have multiple levels of caches. We can optimize the number of cache misses, often without even knowing the size of the cache. |
HASHING | Hashing is the most used data structure in computer science. And it's still an active area of research. |
INTEGERS | Logarithmic time is too easy. By careful analysis of the information you're dealing with, you can often reduce the operation times substantially, sometimes even to constant. We will also cover lower bounds that illustrate when this is not possible. |
DYNAMIC GRAPHS | A network link went down, or you just added or deleted a friend in a social network. We can still maintain essential information about the connectivity as it changes. |
STRINGS | Searching for phrases in giant text (think Google or DNA). |
SUCCINCT | Most “linear size” data structures you know are much larger than they need to be, often by an order of magnitude. Some data structures require almost no space beyond the raw data but are still fast (think heaps, but much cooler). |
Most course material is covered in video lectures recorded in 2010 (already watched by over 350,000 people), which you can conveniently play at faster speed than real time. There may also be some new material presented by the professor and/or guest lecturers, which will be recorded for asynchronous viewing.
But synchronous meeting time (also online) will focus on collaborative problem solving with your fellow students and the course staff. Particularly unusual is that the problems we'll solve in groups will include a choose-your-own-mix of problem-set style problems with known solutions, coding problems for those who love programming, and open research problems that no one knows the answer to, with the goal of publishing papers about whatever we discover. (Past offerings of this class have led to several published papers.) You can work on whatever type of problem most interests you. To facilitate collaboration, we'll be using our open-source software platform called Coauthor, along with GitHub for (optional) coding.
Times for synchronous session(s) will be scheduled to accommodate students' schedules and timezones. Please sign up to the 6851-students mailing list if you might be interested in taking the class, so you can help decide the schedule.
We recommend a drawing tablet for online collaboration, so be sure to apply for one if you don't have one. We'll be using a bunch of custom bleeding-edge open-source software tools for online collaboration, including our own Coauthor, Cocreate, and Comingle, which aim to reproduce the in-person experience as best as possible. Join us to help make this possible!
Synchronous Class Time: | Mondays at 4:00pm–5:30pm Eastern and/or Thursdays at 7:00–8:30pm Eastern Attending both sessions is strongly recommended; for-credit students must attend at least one. |
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Synchronous Class Room: | online, via Comingle (Fill out the sign-up form and join the mailing list (see below) to get the private link to the class.) |
First Class: | Thursday, February 18, 2021 at 7:00–8:30pm Eastern |
Second Class: | Monday, February 22, 2021 at 4:00–5:30pm Eastern |
Office Hours: | Mondays at noon Eastern Tuesday evenings at 7:00pm Eastern Wednesday evenings at 10:00pm Eastern |
Professor: | Erik Demaine, edemaine at mit.edu |
TAs: | Josh Brunner, brunnerj at mit.edu
Yevhenii Diomidov, diomidov at mit.edu Dylan Hendrickson, dylanhen at mit.edu |
Staff Email: | 6851-staff at csail.mit.edu |
Units: | 3-0-9 |
Prerequisites: | 6.046 or equivalent background in discrete mathematics and algorithms.
Alternatively, permission from the instructor. |
Credit: | H-level and TCS AAGS credit |
If you are interested in attending the class, for credit or as a listener, please do the following:
required | Watch all video lectures, measured by thumbs-upping completion questions on Coauthor. |
required | Watch recorded portions of synchronous classes that you didn't attend. |
required | Participate during synchronous classes, at least one per week (email 6851-staff about exceptions) |
required |
Participate in class discussion,
measured as coauthoring at least one nontrivial Coauthor post each week.
See your
statistics view to check for zero weeks.
(Example of a trivial post for a solved problem: "Use a tree." Example of a nontrivial post for a solved problem: Describing the solution techniques you tried but failed. Deleted and unpublished posts do not count, but private posts do.) |
choice | Problem sets. Problem sets will be posted weekly, and follow a “one-page in, one-page out” rule. |
choice | Project write-up and presentation based on in-class work. |
We're experimenting with a flexible grading scheme this semester:
Each component will be graded on a 100-point scale, then weighted according to the percentages above, then summed to produce your overall score. Your letter grade (A, B, etc.) will be assigned according to this score (where 90+ = A, 80+ = B, 70+ = C, 60+ = D, <60 = F). However, we reserve flexibility in assigning the annotation (+, −, or straight letter) according to other factors such as going above and beyond in participation or just scraping by.
The percentage weights sum to 140%, so you can skip the project (40%) or the problem sets (40%) and still get to 100% total work. Alternatively, you can make up for lost points in any component by working on the other components. The intent is to make projects optional, but reward those who do them by requiring fewer problem sets.
One additional rule is that you cannot pass the class without both watching most of the lectures and in-class participation most weeks (according to the fairly minimal requirements above), which is the meaning of "required".
The class is offered once every two years or so. It was given in Spring 2003 and Spring 2005 as 6.897, and in Spring 2007, Spring 2010, Spring 2012, Spring 2014, and Fall 2017, as 6.851.