The study of data structures studies the problem of preprocessing and organizing large data that mostly does not change over time such that we can answer queries on this data efficiently. You encounter these types of problems more often than you think: think of interactions with Google search (return a document among many that contains a query text), finding directions (return the shortest path between two points on a large map that mostly does not change), querying employee databases (return all employees that satisfy certain criteria, e.g. fall within some salary and age ranges), etc.
There have been many recent results in the area of data structures with many more problems remaining open. The course will provide an overview of existing data structuring results, present indepth understanding of some of the specific results, teach specific data structuring techniques, and provide the students with an opportunity to tackle some of the open problems.
To get a flavor of the types of problems studied in this course, consider the following questions:
I am traveling during the first week of classes and the following Monday is a holiday. So the first "real" lecture will not be until after the add date, if you are considering registering for the course after attending the first couple of lectures. Therefore, if you are wondering if this course is for you, I suggest you email me as soon as possible.
During the first week (in lieu of the lectures), there will be a takehome assessment exam, which is posted on this webpage. I will use the results of the exam to determine students' level of preparation for the prerequisites and to adjust the course and topics approriately. Therefore, to give an accurate picture of students' knowlege, the exam should be individual effort.
This is a course on advanced algorithmic concepts, so you should be very comfortable with asymptotic notation, design and analysis of basic algorithms, and the algorithms taught in ICS 311 (most of the material from the CLRS textbook). Therefore, unless you received an 'A' in ICS 311 or equivalent, I suggest you talk to me before registering for the course.
There is no textbook for the material in this course because the material consists mostly of recent research results. The articles covering the material will be posted here.
The grade in the course will consist of the following components:
Content. The notes you write should cover all the material covered during the relevant lecture, plus real references to the papers containing the covered material. Your notes should be understandable to someone who has not been to the lecture. You should write in full sentences where appropriate; point form (like I write on the board) is often too terse to follow without a sound track (though occasionally it is appropriate). Use numbered sections, subsections, etc. to organize the material hierarchically and with meaningful titles. If you feel it is appropriate, use nested bullets to organize material hierarchically even deeper. Try to preserve the motivation, difficulties, solution ideas, failed attempts, and partial results obtained along the way in the actual lecture.
Format. Write your notes using LaTeX, with figures in Encapsulated PostScript (generated from xfig, ipe, Adobe Illustrator or whatever you want). Start from the Latex template, which sets the style.
Timing. Try to write the lecture notes for a class on the same day while the material is fresh in your mind and it will save you time. You should finish the first draft of your notes and send it to me by two days after the lecture. Then I'll either send you comments via email or we'll schedule a meeting to go over your writeup, I'll make suggestions, you'll make a second pass, and send it to me. I'll make the final pass, and post it on the webpage. The goal will be to get the notes out by one week after the corresponding class.
There will be 35 homeworks (once every 23 weeks) throughout the semester. Each homework will contain as many problems as there are students in class. You may collaborate with anyone on the homeworks, but you must write up your own solutions. You must write the names of everyone you discussed the solution with in your homework writeup. The homework must be typed up. It will be due at the beginning of the lecture on the day it is due and can be either submitted in person in lecture (preferred) or emailed to me. Homework solutions will be discussed in class on that day, therefore, no late homeworks will be accepted (even if you miss that lecture).
Homework grading. This semester I will be testing a new method of grading homeworks: on the day the homework is due, for each problem I will ask by show of hands who solved that problem. If you don't raise your hand, you will receive 0 pts for that problem. If you raise your hand, you must be ready to explain your solution on the board. Among those who raised their hand, I will randomly ask one of you to the board to explain your solution to the class. If the student called to the board stumbles or has an incorrect solution, I will randomly ask another person who raised their hand to help out. You will receive points to the problem based on the correctness and presentation of your solution. If you raised your hand and weren't called to explain the solution, you receive credit based on the writeup of your solution. I reserve the right to change the grading method to grading just the writeup for any of the homeworks.
Goal. Ideal outcome of the project at the end of the class is for you to obtain results that can be published at an algorithms conference. To receive full credit on the project, you do not have to achieve this goal (that's the nature of research), but that should be your goal. If you do not achieve publishable results, your writeup should describe the ideas and approaches you took to solve the problem.
Topic. The topic of your research project should be related to data structures. I will be available for brainstorming during office hours for possible topic of interest. You must be interested in the topic, but I must approve the topic, so check with me first.
Format. Here is a list of possible formats of the project. This list is not exhaustive, so if you have an interesting idea that you don't see on the list below, come discuss it with me.
Writeup. The project must be written up in a research paper format. It should be somewhere between 6 to 15 singlespaced pages with 1 inch margins. It should start with a title, author and a 12 paragraph abstract. The body of the writeup should consist of introduction, the body and the conclusions. The introduction should describe the problem you are addressing, present a brief literature review of related results on the topic, and a summary of your results. The body should describe your solution, teachnique/approach to solving it and results. If you haven't achieved significant results, you should still describe the techniques/approaches you have tried and why they didn't work. The conclusions should summarize what you have presented and present possible directions for future research, e.g. open problems that remain unsolved and/or possible approaches that you might have tried if you had more time. You are welcome to collaborate on the project with anyone (even outside the class), including me, but you should give credit to people you have collaborated with. This is the nature of research.
Presentation. At the end of the semester you should give a 30 minute presentation about your project.
The class will cover a subset of the following topics:
Specific topic covered will depend on the students' interest. The schedule below will be updated with the topics as they are covered.
Class  Day  Date  Topic  Scribe Notes  Notes 
1  Mon  Jan 11  NO CLASS (Nodari is at a conference): Takehome assessment exam  Due 5:00pm on Thursday, Jan 14 (either by email or in POST 309C) 

2  Wed  Jan 13  NO CLASS (Nodari is at a conference): Finish the takehome assessment exam  
  Mon  Jan 18  HOLIDAY: Martin Luther King Day  
3  Wed  Jan 20  Review of the assessment exam  Kyle  
4  Mon  Jan 25  Amortized Analysis: Aggregation, accounting, potential methods  Ben (Notes 01)  Reading: [CLRS, Ch. 17], [T] 
5  Wed  Jan 27  Selfadjusting Data Structures: Movetofront  Ben (Notes 02)  Reading: [ST85a] 
6  Mon  Feb 1  Selfadjusting Data Structures: Splay Trees  Ben (Notes 03)  Reading: [ST85b] 
7  Wed  Feb 3  Splay tree access properties. Geometry of BSTs  Ben (Notes 04)  Reading: [ST85b], [Iac01], [Col00], [DHIKP09] 
8  Mon  Feb 8  Geometry of BSTs: offline equivalence  Kyle (Notes 05)  Reading: [DHIKP09] 
9  Wed  Feb 10  Geometry of BSTs: online equivalence  Maria  Reading: [DHIKP09] 
  Mon  Feb 15  HOLIDAY: Presidents' Day  
10  Wed  Feb 17  Online BSTs: Lower bounds  Maria  Reading: [DHIKP09], [W89] 
11  Mon  Feb 22  Guest Lecture: Riko Jacob External Memory Search Trees 
Ben (Notes 08)  Reading: [BF03] 
12  Wed  Feb 24  Predecessor search: van Emde Boas Trees  Ben  Reading: [CLRS, Ch 20], [V75], [V77] 
13  Mon  Feb 29  Predecessor search: van Emde Boas Trees (cont.)  Kyle (Notes 10)  Reading: [CLRS, Ch 20], [V75], [V77] 
14  Wed  Mar 2  Lowest Common Ancestors (LCA), Range Minima Queries (RMQ) 
Maria  Reading: [HT84], [BF00] 
15  Mon  Mar 7  Level Ancestors  Maria  Reading: [BF04] 
16  Wed  Mar 9  String Matching: Tries  Kyle (Notes 13)  Reading: [CKL06] 
17  Mon  Mar 14  Nodari is at a conference  
18  Wed  Mar 16  Nodari is at a conference  
  Mon  Mar 21  SPRING BREAK  
  Wed  Mar 23  SPRING BREAK  
19  Mon  Mar 28  Tries (cont.), Suffix Trees  Kyle (Notes 14)  Reading: [CKL06] 
20  Wed  Mar 30  Suffix Array construction, DC3 algorithm  Kyle (Notes 15)  Reading: [KSB06] 
21  Mon  Apr 4  Succinct data structures: binary trees, rank, select  Ben  Reading: [MR01], [P08] 
22  Wed  Apr 6  NO CLASS: Nodari is sick  
23  Mon  Apr 11  Persistent Data Structures  Kyle (Notes 17)  Reading: [DSST89] 
24  Wed  Apr 13  Fractional Cascading  Kyle (Notes 18)  Reading: [CG86a], [CG86b] 
25  Mon  Apr 18  Range Trees  Kyle  Reading: [BCKO08, Ch. 5] 
26  Wed  Apr 20  
27  Mon  Apr 25  Interval Trees, Priority Search Trees  Ben  Reading: [BCKO08, Ch. 10] 
28  Wed  Apr 27  Segment Trees  Kyle  Reading: [BCKO08, Ch. 10] 
29  Mon  May 2  Dictionaries, Hash Tables  Ben  
30  Wed  May 4  Project presentations  project due 