The current plan for online instruction is to hold our lectures during their normally scheduled times using Zoom video conferencing software. I will use the shared whiteboard feature in conjunction with a writing tablet to simulate the blackboard. For now, I'll record the classes as well, though if I notice a sharp decline in attendance I might stop the practice.
We will use the same recurring meeting for all lectures. The link was sent to you via email. Let me know if you need it.
The only change to the problem set process is that comlpeted problem sets will now be submitted electronically. We will likely use Canvas for this purpose. Instructions on the submission process will be posted before the next problem set is due.
I will be holding my offices hours at my normal times using Zoom [video conference link]. I am also available via email for any questions or concerns you have about this course, or the shift to online instruction more generally.
This course covers foundational results in theoretical computer science, with a focus on how we model computation and how we use these models to explore key questions about what can and cannot be solved (efficiently) with computing devices. Many of the concepts in this course will come up often in the life of a computer scientist (e.g., NPcompleteness, decidability, grammars, etc).
During the final lectures of the course, we will tackle some cutting edge topics from the field (time permitting), to provide guidance to those who might be interested in pursuing research in this topic in graduate school.
This course is open to PhD and Masters students. Wellprepared undergraduates can take the course with professor's permission (space permitting).
The textbook for this course is Introduction to the Theory of Computation, 3rd Edition, Michael Sipser, 2012. Most of the topics covered in this course will be drawn from this text.
Grades in the course will be based on five problem sets and two exams.
In determining your final grade, I will add up the total number of points you earned and assign your grade based on this sum. I will provide a guide for each problem set and exam that shows how your point score roughly maps to letter grades.
The point values of the exams and problem sets are calibrated so they they contribute approximately the following percentage toward your final point total:
Problem sets  40% 
Midterm  30% 
Final  30% 
I hold regular office hours in my office at 356 Saint Mary's Hall from 2:00 to 3:00 on Tuesday and Thursdays. I'm also available to answer quick questions before and after class, and via email (cn248@georgetown.edu).
The teaching assistant for this course is Alex Weaver. He is available to answer questions about problem set problems via email (baw4ux@gmail.com) or by appointment.
Problem sets will be posted for download on the schedule below on the day they are assigned. Detailed sample solutions and notes will be handed back to students along with the graded problem sets. I try to grade and return problem sets within one week.
The following rules describe my expectations and grading policies for problem sets:
There will be two exams in the course: a midterm and a final. The midterm covers automata and computability theory and the final covers complexity theory (i.e., it is not cumulative).
I take academic integrity seriously. To repeat the problem set instructions from above: You must work alone on problem sets. You may only discuss problems with me. The only materials you can reference when working on these problems are your course notes and the assigned textbook. In particular, you may not reference online sources or talk to other students.
You may not bring any outside material into exams.
You may not reference any problem sets, exams, or solutions from prior teachings of this course.
When in doubt, ask me what is allowed.
Below is the current schedule for the course (changes will occur during the semester as some things take long and other shorter than expected). Problem sets will be posted for download on the schedule as they become available. The readings column lists the chapters from the Sipser textbook that cover the corresponding lecture's material.
Class Number  Date  Description  Readings 
Part 1: Automata and Languages  
1  1/9  Intro; finite automata  1.1 
2  1/14  Nondeterminism; regular operation closure properties
 1.2 
3  1/16  Equivalence of regular languages and regular expressions  1.3, 1.4 
4  1/21  Equivalence of regular languages and regular expressions (cont)  1.3, 1.4 
5  1/23  Regular language pumping lemma; context free languages; pushdown automata  1.4, 2.2 
6  1/28  Equivalence of pushdown automta and contextfree lanuages  2.2, 2.3 
Part 2: Computability Theory  
7  1/30  Contextfree pumping lemma; Turing machines  2.3, 4.1 
8  2/4  Some decidable and recognizable
languages. Proof of undecidable and unrecognizable
languages.
 4.1, 4.2 
9  2/6  Reducibility  5.1, 5.3, 6.3 
10  2/11  Reducibility (cont); LBAs  5.1, 5.2, 5.3, 6.3 
11  2/13  Recursion Theorem  6.1 
2/18  No Class: President's Day (Monday Schedule)  
12  2/20  Lecture overflow; midterm review  
13  2/25  Midterm  
Part 3: Complexity Theory  
14  2/27  Time complexity; TIME and NTIME classes
 7.1 
15  3/3  Time complexity (continued)  7.1 
16  3/5  The class P  7.2, 7.3 
3/10  No Class: Spring Break  
3/12  No Class: Spring Break  
17  3/17  NPcompleteness [Zoom conference link]  7.4 
18  3/19  CookLevin Theorem  7.4 
19  3/24  NPcomplete problems  7.4 
20  3/26  Space Complexity; SPACE and NSPACE complexity classes  8.0 
21  3/31  Savitch's Theorem

8.1, 8.2, 8.3 
22  4/2  PSPACE and PSPACECompleteness  8.1, 8.2, 8.3 
23  4/7  L and NL  8.4, 8.5, 8.6 
4/9  No Class: Easter Break  
24  4/14  NLCompleteness, and NL =
coNL
 8.4, 8.5, 8.6 
25  4/16  Hierarchy Theorems  9.0, 9.1 
26  4/21  Relativization  9.0, 9.2 
27  4/23  BPP  10.1, 10.2 
28  4/28  Overflow/Advanced Topics  10.1, 10.2 