|
Chair: Prasad Jayanti
Associate Chair: Hany Farid
Professors T. H. Cormen, B. R. Donald, R. L. Drysdale III, P. Jayanti,
D. F. Kotz, F. Makedon, D. Rockmore, P. Winkler; Associate Professors A.T.
Campbell, H. Farid, L. Fleischer, S. W. Smith; Assistant Professors C. J.
Bailey-Kellogg, D. Balkcom, A. Chakrabarti, F. Pellacini, A. J. Zomorodian;
Instructors K. M. Forbes-Riley, M. J. Fromberger; Research Associate Professor
P. Thompson; Research Assistant Professors J. C. Ford, T. N. Henderson, L.
Loeb; Visiting Professors M. D. McIlroy, W. M. McKeeman; Visiting Associate
Professor C. S. McDonald; Adjunct Professor R. H. Granger.
INTRODUCTORY COURSES
Students wishing to devote one course to the study of computer science may
choose Computer Science 4 or 5, depending on their background and interests.
Students wishing to devote two or more courses to the study of computer science
should begin with Computer Science 5 and 18.
MAJOR IN COMPUTER SCIENCE
The major in computer science is intended for those students who plan
careers in computer science or in fields that make use of computing, for those
who plan graduate study in computer science, and also for those who simply find
computer science interesting. Undergraduates majoring in computer science will
have opportunities to participate with faculty in activities outside formal
coursework. These activities include assisting in courses, writing a thesis or
doing a project under the guidance of a faculty member, and assisting a faculty
member in research or in a programming project.
To fulfill the major in computer science, a student must complete the
courses prerequisite to the major and satisfy the requirements of the major.
For additional requirements for the Honors Program see the section 'The Honors
Program in Computer Science' below.
The basic first courses for students planning advanced work in computer
science are Computer Science 5, Computer Science 18, Computer Science 19, and
Mathematics 3. Computer Science 5 should be taken before Computer Science 18.
Computer Science 19 should be taken after, or concurrently with, Computer
Science 18. Next in the sequence of Computer Science courses will normally be
Computer Science 23, 25, and 37; these can be taken in any order. (Note that
Computer Science 19 should be taken before Computer Science 25.) Computer
Science 37 may be taken any time after Computer Science 5, but most students
will take Computer Science 18 first.
REQUIREMENTS FOR THE COMPUTER SCIENCE MAJOR
Prerequisite courses: A student must complete Computer Science 5,
18, 19, and Mathematics 3, or the equivalent honors or advanced placement
course.
Requirements: A student who wishes to major in Computer Science
must obtain approval of her or his program of study from the Departmental
Undergraduate Advisor. To complete the major, it is necessary to pass at least
nine courses in addition to taking the four prerequisite courses. Among these
nine courses must be the following:
1. Computer Science 23;
2. Computer Science 25;
3. Computer Science 37;
4. Computer Science 39;
5. Computer Science 58 or 78;
6. Computer Science 48 or 68;
7. at least one course in mathematics related to computer science
(Mathematics 16, 20, 22, 25, 26, 28, 29, 31, 38, 39, 40, 50, 56 or their honors
equivalent);
8. one other Computer Science course numbered from 33 to 38 or from 43 to
88. This may include 48, 58, 68, or 78, if not used to satisfy requirements 5
or 6;
9. Computer Science Culminating Experience Course (2 terms of Computer
Science 98 or 1 term of Computer Science 99) or Thesis (Computer Science
97).
MINORS IN COMPUTER SCIENCE
The following minors are available to all students who are not majoring in
Computer Science and who do not have a modified major with Computer Science.
For each minor, the prerequisites and required courses are listed below.
Approval of a minor can be obtained through the Undergraduate Advisor.
I. Computer Science
Prerequisites: Computer Science 5, 18, and 19.
Courses: Computer Science 23, 25, 37; any one of Computer Science
39, 48, 58, 68, 78, or 85; plus one other Computer Science course numbered from
33 to 38 or from 43 to 88.
II. Operations Research
Prerequisites: Mathematics 3, 8, 13, and Computer Science 19.
Courses: Computer Science 25; Mathematics 16, 20, 22; and one of
Mathematics 38 or 88 or Computer Science 85 with approval of the Undergraduate
Advisor.
III. Digital Arts
Prerequisites: Computer Science 4 or 5.
Courses: Computer Science 22, 32, 42; one of Film Studies 31, Film
Studies 35, Film Studies 38, Studio Art 16, Studio Art 29, Theater 30; and one
other course from the following list: Film Studies 31, Film Studies 35, Film
Studies 38, Studio Art 16, Studio Art 29, Theater 30, Computer Science 12,
Computer Science 52, Computer Science 82, Psychology 21.
THE HONORS PROGRAM IN COMPUTER SCIENCE
For completion of the Honors Program in Computer Science, and to be eligible
to graduate with Honors or High Honors, a student must complete either an
independent study project or a written thesis (for High Honors the thesis is
required), and have his or her program of study approved as an Honors Program
by the Undergraduate Advisor. In addition, the recommendation of the
thesis/project advisor to award Honors or High Honors must be ratified by a
departmental vote. College requirements for the Honors Program are discussed on
pages XXX. The Honors project is undertaken by a student under the guidance of
a faculty member. Usually the subject of the project or thesis will be
motivated by the concepts or content of an advanced course taken as a part of
the student's major, and will normally be completed over a period of two or
three terms. A variety of activities, such as participation in a department
seminar, can lead to a project or thesis. Student suggestions for both projects
and theses are welcome. The student should consult with his/her prospective
project advisor and submit to the Undergraduate Advisor a brief written
proposal of the project that has the written approval of the project advisor.
The Undergraduate Advisor will review the student's proposal and the courses
that have been selected for the Honors major. Approval of the proposal and
course selection will constitute formal admission into the Honors Program. This
procedure is normally completed before the end of fall term, senior year. The
student may then register for (at most two terms of) Computer Science 97,
Honors Thesis Research.
Admission to the Honors Program requires a general College average of B, and
a B average in the major at the time of admission and at the time of
graduation. Moreover, a B+ average is required in the work of the Honors
project/thesis. The B average in the major is determined as follows: Courses
prerequisite to the major are not counted, but all other courses used as part
of the major are counted, as are all courses titled Computer Science (beyond
prerequisites, excluding 97), including courses cross-listed with Computer
Science. Note that in the case of modified majors, courses used as part of the
major may include courses from other departments. The B+ average required in
the work of the Honors program is defined to be a grade of B+ given by the
thesis/project advisor on the thesis or project. Questions about this
requirement should be addressed to the Departmental Undergraduate Advisor.
PREGRADUATE STUDY IN COMPUTER SCIENCE
Most graduate departments of computer science require applicants to take the
Graduate Record Examination in Computer Science. This examination primarily
covers material in Computer Science 5, 18, 19, 23, 25, 37, 39, 58, and 68, plus
material in Engineering Sciences 31. Those considering graduate school should
take many of these courses. Less emphasis is placed on material in Computer
Science 33, 44, 48, 52, and 78, and the various advanced topics covered in
Computer Science 85 and 88 (although advanced topics are very good preparation
for graduate study). Material from all courses listed as 'mathematics related
to computer science' may appear on the examination, and it is hard to say that
any of these courses is better preparation than the others. This examination is
only one part of an application for graduate school. Letters of recommendation,
particularly from professors who know you well through an advanced class or
work on a project, usually are given more weight.
MODIFIED MAJORS
Many students have created modified majors with Computer Science being
either the primary or the secondary part. Particularly common modified majors
are with engineering, mathematics, or economics, but modified majors with
philosophy, music, film studies, psychology, physics, geography, studio art,
and many other subjects have been approved.
A modified major with Computer Science as the primary part must satisfy the
first three requirements of the Computer Science major, two of requirements 4
through 6, and both of requirements 8 and 9. Students should discuss their
plans with the Department's Undergraduate Advisor to ensure a coherent
major.
A modified major with Computer Science as the secondary part normally
contains Computer Science 23, 25, and 37, and must contain at least two of
these courses.
THE COMPUTER SCIENCE MAJOR MODIFIED WITH ENGINEERING
The Computer Science major modified with engineering requires satisfying
most of the requirements of the computer science major, along with four
engineering courses related to computer science. The prerequisites are Computer
Science 5, 18, 19; Mathematics 3, 8, 13; and Physics 13, 14. The requirements
are as follows:
1. Computer Science 23;
2. Computer Science 25;
3. Computer Science 37;
4. Satisfy two out of a, b, and c:
a) Computer Science 39;
b) One of Computer Science 58 or 78;
c) One of Computer Science 48 or 68;
5. One other Computer Science course numbered from 33 to 39 or from 43 to
88. This may include 39, 48, 58, 68, or 78 if not used to satisfy requirement
4; it may not include Computer Science 47, which is identical to requirement 7
(Engineering Sciences 31);
6. Engineering Sciences 22;
7. Engineering Sciences 31;
8. Engineering Sciences 62 or 63;
9. Engineering Sciences 26, 32, 61, 62, 63 or 91. (The same course cannot
satisfy both 8 and 9).
10. Computer Science Culminating Experience Course (two terms of Computer
Science 98 or 1 term of Computer Science 99) or Thesis (Computer Science
97).
GRADUATE STUDY IN COMPUTER SCIENCE
The Department of Computer Science offers programs leading to the Ph.D. and
M.S. degrees in Computer Science. Each is described below.
REQUIREMENTS FOR THE DOCTOR'S DEGREE (PH.D.)
During the first two years, the students take a set of core graduate
courses, topics courses, research seminars, and begin to become involved in
research projects. In the third year and beyond, the main activities will be
research and participation in seminars and topics courses.
The requirements for the Ph.D. degree in Computer Science are as
follows:
1. Admission to the degree program by an admissions committee of the
Computer Science faculty.
2. Completion of a course of study that includes:
(a) Computer Science 105, 107, 108, and 118.
(b) Two of Computer Science 104, 106, and 109. If 109 is not taken then
Computer Science 39 must be taken, unless the departmental advisor to Ph.D.
students certifies that the student has taken an equivalent course
elsewhere.
(c) Two advanced topics courses numbered between 181 and 188.
(d) Two additional courses, which may be chosen from advanced topics courses
numbered between 181 and 188, the courses Computer Science 33, 38, 52, 54, and
78 taken for graduate credit (which involves additional work not required of
undergraduates), whichever of Computer Science 104, 106, and 109 was not used
to satisfy requirement (b) above, and Computer Science 110.
A student's course of study is subject to the approval of the departmental
advisor to Ph.D. students. Students normally take the six core courses
specified in requirements (a) and (b) above by the end of their second
year.
3. Students are expected to pass the Research Presentation Exam by the end
of the winter term of their third year. An examining committee consisting of
three faculty members, appointed by the departmental advisor to the Ph.D.
Program, will select a paper for the student to present. The paper is selected
in the area of Computer Science that the student chooses to be examined in. The
student will have a month to read the paper, and will then present the paper to
the committee and will orally answer questions on the paper. The committee will
evaluate the student's presentation and performance answering questions, and
will determine if the student passes the examination. A student repeats this
exam until he/she eventually passes the exam. In each attempt, the student is
assigned a new paper, but not necessarily a new committee. Passing the Research
Presentation Exam is a prerequisite to thesis proposal (see requirement 5
below). For more details on this exam, consult the Computer Science department
web page.
4. At least one term of participation in undergraduate teaching. That is,
the student must pass Computer Science 257.
5. Each student must display readiness for research in one area by giving a
written and a public oral presentation of their research plan. This thesis
proposal will be judged by a faculty committee chosen by the student; the rules
used for the composition of this committee are the same as for a Ph.D. defense
committee; this committee does not require the approval of the Dean of Graduate
Studies, but must be approved by the departmental advisor to Ph.D. students.
The presentation will be followed by a question period in which the student
demonstrates mastery of the relevant area, and defends their proposed thesis
plan.
6. Six terms in residence at Dartmouth. (This is a College requirement.)
7. Preparation of a thesis acceptable to a faculty committee and a public
defense of this thesis. The committee shall be formed for the purpose of
guiding the student's research, according to the rules of the College. This
committee must be approved by the Dean of Graduate Studies. All members of the
committee shall read and sign the thesis in its final form.
REQUIREMENTS FOR THE MASTER OF SCIENCE DEGREE (M.S.)
The requirements for the M.S. degree in Computer Science are as follows:
1. Course requirements:
(a) Satisfactory completion of six Computer Science courses taken for
graduate credit. At least three of these courses must be numbered above
100.
(b) Satisfactory completion of three additional courses taken for graduate
credit, at least one of which is an advanced topics graduate course in Computer
Science (listed as Computer Science 181-188). Any courses taken outside of the
Computer Science department must be approved by the departmental advisor to
Master's students. Students are expected to complete the M.S. degree in a
maximum period of seven consecutive terms.
2. Research requirements:
Six course equivalents of research from Computer Science 297-299 is the
minimum amount of research required towards the development and writing of a
Master's Thesis.
3. Thesis requirements:
(a) A thesis proposal, consisting of a written document and a public
presentation, shall be completed by the end of the fourth term of study. This
thesis proposal will be judged by a faculty committee chosen by the student;
the rules used for the composition of this committee are the same as for an
M.S. defense committee as noted in the Graduate Student Handbook, “three
faculty members from the student's department/program (including the
dissertation advisor). One of the three may be from outside the
department/program, but this is not a requirement.”
(b) Preparation of a thesis acceptable to a faculty committee and a public
defense of this thesis. The committee shall be formed for the purpose of
guiding the student's research, according to the rules of the College. This
committee must be approved by the Dean of Graduate Studies. All members of the
committee shall read and sign the thesis in its final form. We expect that the
thesis, including a copy of the signature page, shall be published as a
departmental Technical Report.
UNDERGRADUATE COURSES
Course Numbering System: For Computer Science courses numbered
above 20, the last digit in the course number indicates the field of computer
science as follows: graphics, 2;s application ystems, 3; artificial
intelligence, 4; algorithms, 5; numerical analysis, 6; hardware systems, 7;
software systems, 8; theory of computation, 9.
Note: Among the prerequisites for courses listed below, Computer
Science 14 may substitute for Computer Science 5, but only if taken before or
during 04S.
4. Concepts in Computing
07W: 2 07X: 12 08W: 2
This course provides an overview of computing and computer science,
including such topics as the history of computers, computer applications,
introductory concepts in digital electronics and computer architecture,
computer languages, theory of computation, artificial intelligence, and the
impact that computers have had on society and are likely to have in the future.
Students will be introduced to computing through appropriate high-level
software, such as World Wide Web, hypertext, and scripting languages. For
example, in recent offerings students learned HTML and Javascript, and wrote
significant HTML projects.
This course is intended for students who plan to take only one course in
computer science, although students who take this course are welcome to take
Computer Science 5 later. This course is not open to students who have taken or
received credit for Computer Science 5, Engineering Sciences 20, or any
Computer Science course numbered 18 to 26, or 33 to 99. Dist: TAS.
Pellacini (winter), the staff (summer).
5. Introduction to Computer Science
06F, 07S, 07F, 08S: 2
This course provides an introduction to fundamental concepts and techniques
of computer science. The framework is an object-oriented programming language.
Both programming and algorithm analysis are covered. Programming topics include
basics of data and control; problem decomposition; recursion; simple graphics;
objects and abstraction; and arrays. Good programming style is emphasized
throughout the course. Algorithm topics include searching, sorting, and linked
lists.
In past years Engineering Sciences 20 could substitute for Computer Science
5 as a prerequisite for Computer Science courses, but since its content has
changed this is no longer the case. Students considering the computer science
major, or majors modified with computer science, or courses that require
Computer Science 5 as a prerequisite should take Computer Science 5 instead of
Engineering Sciences 20. Dist: TLA. Cormen (fall), Balkcom
(spring).
7. First-Year Seminar in Computer Science
Consult special listings
12. Motion Study: Using Motion Analysis for Science, Art and Medicine
07S: 2A 08S: 11
For hundreds of years, scientists and artists have studied motion in order
to create better machines, detect injuries, improve athletic performance,
express concepts and feelings, create more efficient factories, and understand
hidden motivations. This interdisciplinary course will look at what is known
and how it is used. We will also do our own motion analysis, complete projects
using motion data, explore some of the languages that have been developed to
describe human motion, and consider the relationship between the artistic
representation of motion and scientific reality. Students will keep a motion
journal, write two papers, and complete a research project that will be
presented to the class in lieu of a final exam. There are no prerequisites for
the course. Students from all departments are encouraged to attend. Dist:
TAS. Loeb.
16. Linear Programming (Identical to Mathematics 16)
07S: 11 08S: Arrange
This course introduces one of the fundamental tools of modern business
planning and an exciting area of current mathematical and computer science
research. The course begins with a discussion of the kinds of problems to which
linear programming applies, followed by an introduction to the simplex
algorithm and duality and shadow prices. After a discussion of some pitfalls of
the simplex algorithm, the course turns to the revised simplex method, the
solution of general linear programming problems, the general theory of duality
and feasibility, a discussion of the applications of linear programming to the
efficient allocation of scarce resources, and problems such as production
scheduling and inventory. The course will close with topics selected from
applications to matrix games, connections with geometry, connections to optimal
matchings, network flows and transportation problems, or the nature and
implications of interior point methods in linear programming.
Prerequisite: Mathematics 6 or 8 or equivalent knowledge of matrix algebra
and permission of the instructor. Dist: TAS. The staff
18. Structure and Interpretation of Computer Programs
06F: 10 07W: 11 07F: 10 08W: 11
A challenging introduction to programming languages and computer science
that emphasizes alternative modes of algorithmic expression. Topics include
recursive and higher-order procedures, performance analysis of algorithms,
proof of program correctness, probabilistic algorithms, symbolic hierarchical
data, abstract data types, polymorphic functions, object oriented programming,
infinite data types, simulation, and the interpretation of programs.
Prerequisite: Computer Science 5, or placement in Computer Science 18 via
Advanced Placement or departmental exam. Dist: TAS. Fromberger.
19. (former 21) Discrete Mathematics in Computer Science
(Identical to Engineering Sciences 66)
07W, 08W: 10
This course integrates discrete mathematics with algorithms and data
structures, using computer science applications to motivate the mathematics. It
is designed to be taken simultaneously with Computer Science 18. However,
students who are unable to complete it in this way may take it after Computer
Science 18 but before Computer Science 25.
The course introduces counting techniques and number theory, with an
emphasis on the application to RSA public key cryptography. It covers logic and
proofs, including mathematical induction. Relationships among recursive
algorithms, recurrence relations, and mathematical induction are discussed with
particular attention to trees as a recursive data structure. Issues of expected
running time for algorithms and the technique of “hashing” data files for
quick recovery of information guides the discussion of probability through
independent trials experiments and expected values. The course also covers
basic graph theory.
Mathematics 19 is identical to Computer Science 19 and may substitute for it
in any requirement.
Prerequisite: Concurrent enrollment in Computer Science 18 or completion of
Computer Science 18. Dist: QDS. Zomorodian.
22. 3D Digital Modeling
06F, 07F: 10A
This projects-based lab course teaches the principles and practices of 3D
modeling. Lectures focus on principles of modeling, materials, shading, and
lighting. Students create a fully rigged character model while learning their
way around a state-of-the-art 3D animation program. Assignments are given
weekly. Students are graded on the successful completion of the projects, along
with a midterm examination. Work will be evaluated on a set of technical and
aesthetic criteria. Dist: TLA. Loeb.
23. Software Design and Implementation
07W, 07S: 12 08W, 08S: Arrange
Techniques for building large, reliable, maintainable, and understandable
software systems. Topics include object-oriented design, user interface design,
software project management, techniques for increasing reliability, and
testing. Concepts are reinforced through a small number of medium-scale
programs and one team programming project. This course requires a significant
time commitment on the part of the student.
Prerequisite: Computer Science 18. Dist: TAS. McDonald.
25. Algorithms
06F, 07S, 07F: 10 08S: Arrange
A survey of fundamental algorithms and algorithmic techniques, including
divide-and-conquer algorithms, lower bounds, dynamic programming, greedy
algorithms, amortized analysis, and graph algorithms. Presentation,
implementation and formal analysis, including space/time complexity and proofs
of correctness, are all emphasized.
Prerequisite: Computer Science 18 and Computer Science 19. Dist:
QDS. Drysdale.
26. Numerical Methods in Computation (Identical to Mathematics 26 and
to Engineering Sciences 91)
06F, 07F: 12
A study and analysis of important numerical and computational methods for
solving engineering and scientific problems. The course will include methods
for solving linear and nonlinear equations, doing polynomial interpolation,
evaluating integrals, solving ordinary differential equations, and determining
eigenvalues and eigenvectors of matrices. The student will be required to write
programs and run them on the computer.
Prerequisite: Computer Science 5 and Mathematics 23. Dist: QDS.
Shepherd.
32. (former 13) Computer Animation: The State of the Art
07W, 08W :2
This hands-on course focuses on state-of-the-art computer animation,
presenting techniques for traditional animation and how they apply to 3D
computer animation, motion capture, and dynamic simulations. Facial and
full-body animation are covered through projects, readings, and presentations,
including physical simulation, procedural methods, image-based rendering, and
machine-learning techniques. Students will create short animations. This course
focuses on methods, ideas, and practical applications, rather than on
mathematics. Dist: ART. Loeb.
33. Information Systems
07S: 12 Not offered every year
This course studies the management of large bodies of data or information.
This includes schemes for the representation, manipulation, and storage of
complex information structures as well as algorithms for processing these
structures efficiently and for retrieving the information they contain. This
course will teach the student techniques for storage allocation and
deallocation, retrieval (query formulation), and manipulation of large amounts
of heterogeneous data. Students are expected to program and become involved in
a project in which they study important aspects of a database system: ways to
organize a distributed database shared by several computers; transactions that
are processed locally and globally; robustness guarantees of the stored data
against failure; security and data integrity guarantees from unauthorized
access; privacy; object-oriented schemes for multimedia data; indexing,
hashing, concurrency control, data mining, data warehousing, mobile databases
and storage file structures.
Prerequisite: Computer Science 23 or equivalent, as approved by instructor.
Dist: TAS. Fromberger.
37. Computer Architecture
07S, 07X: 11 08S: Arrange
The architecture and organization of a simple computer system is studied.
Topics covered include how information is represented in memory,
machine-language instructions and how they can be implemented at the digital
logic level and microcode level, assembly language programming, and
input/output operations. Speedup techniques, such as pipelining and caching,
are also covered.
Prerequisite: Computer Science 5. Computer Science 18 is recommended.
Dist: TAS. Forbes-Riley.
38. Security and Privacy
07S: 2 08S: Arrange
The migration of important social processes to distributed, electronic
systems raises critical security and privacy issues. Precisely defining
security and privacy is difficult; designing and deploying systems that provide
these properties is even harder. This course examines what security and privacy
mean in these settings, the techniques that might help, and how to use these
techniques effectively. Our intention is to equip computer professionals with
the breadth of knowledge necessary to navigate this emerging area.
Prerequisite: completion of Computer Science 23 and completion of (or
concurrent enrollment in) Computer Science 37; or instructor's permission.
Dist: TAS. Smith.
39. (former 49) Theory of Computation
06F, 07F: 12 08F: Arrange
This course serves as an introduction to formal models of languages and
computation. Topics covered include finite automata, regular languages,
context-free languages, pushdown automata, Turing machines, computability, and
NP-completeness.
Prerequisite: Computer Science 25 (students who have not taken Computer
Science 25, but have a strong mathematical background, may take Computer
Science 39 with permission of the instructor). Dist: QDS.
Chakrabarti.
42. Projects in Digital Arts
07S, 08S: Arrange
This is the culminating course for the Digital Arts Minor. Students from
arts and sciences come together to complete projects in digital arts,
including: 3D computer animations; innovative digital installations; creative
mobile media; interactive pieces; 2D digital projects. Students work in small
teams to complete work of a high production quality or work that incorporates
innovations in technology. This course has a required laboratory period.
Prerequisite: Computer Science 32 and one of the following courses: Film
Studies 31, 35, 38; Studio Art 16, 29; Theater 30; Computer Science 12, 42, 82;
or Psychology 21. Dist: ART. Pellacini.
43. Introduction to Bioinformatics
Not offered in the period from 06F through 07S
Bioinformatics is broadly defined as the study of molecular biological
information, and this course introduces computational techniques for the
analysis of biomolecular sequence, structure, and function. While the course is
application-driven, it focuses on the underlying algorithms and information
processing techniques, employing approaches from search, optimization, pattern
recognition, and so forth. The course is hand-on: programming lab assignments
provide the opportunity to implement and study key algorithms.
Prerequisite: Computer Science 23 and Computer Science 25. Dist.
TLA.
44. Artificial Intelligence (Identical to Cognitive Science
44)
07W: 10 08W: Arrange
An introduction to the field of Artificial Intelligence. Topics include
games, robotics, Lisp, Prolog, image understanding, knowledge representation,
logic and theorem proving, understanding of natural languages, and discussions
of human intelligence.
Prerequisite: Computer Science 23 and 25. Dist: TAS. Balkcom.
47. (former 27) Digital Electronics (Identical to Engineering
Sciences 31)
07S: 12 Laboratory 07X: 9 Laboratory 08S: 12 Laboratory
This course teaches classical switching theory including Boolean algebra,
logic minimization, algorithmic state machine abstractions, and synchronous
system design. This theory is then applied to digital electronic design.
Techniques of logic implementation, from Small Scale Integration (SSI) through
Application-Specific Integrated Circuits (ASICs), are encountered. There are
weekly laboratory exercises for the first part of the course followed by a
digital design project in which the student designs and builds a large system
of his or her choice. In the process, Computer-Aided Design (CAD) and
construction techniques for digital systems are learned. Dist: TLA.
Cooley (spring), Hansen (summer).
48. Implementation of Programming Languages
07S: 2A Offered in alternate years
Techniques for automatic translation of programming languages are discussed.
The course includes a brief survey of various techniques and formalisms that
can be used for describing the syntax and semantics of programming languages,
for describing abstract and concrete machine architectures, and for describing
program translation and transformation. This course includes a project to
construct a compiler that will translate a program written in a high-level
language into machine code for a conventional-architecture machine.
Prerequisite: Computer Science 23 and 37. Computer Science 25 and 39 are
strongly recommended. Dist: TAS. McKeeman.
52. (former 43) Computer Graphics
06F: 2A 07F: Arrange
This course is about how to mathematically model and computationally render
(draw) two- and three-dimensional scenes and images. Two basic modes of
rendering studied are (1) fast, interactive, real-time rendering, where realism
is sacrificed for speed or (2) photo-realistic rendering, where the primary
goal is a realistic image. Topics include two- and three-dimensional
primitives, geometrical transformations (e.g., three-dimensional rotations,
perspective and parallel projections), curves and surfaces, light, visual
perception, visible surface determination, illumination and shading, and ray
tracing. Assignments typically consist of a mixture of written work and
“hands-on” projects. Knowledge of basic linear algebra is assumed.
Prerequisite: Computer Science 19 and 23. Computer Science 25 is
recommended. Dist: TAS. Pellacini.
54. Principles of Robot Design and Programming
08S: 2A Offered in alternate years
This project course is a hand-on introduction to robotics. The course will
introduce students to the basic concepts in robotics, focusing on the
mechanics, and electronic principles behind building robots and on the classic
algorithms, architectures, and theories behind controlling and programming
robots. Topics include: basic mechanics, basic electronics, control
architectures (planning, subsumptionism, and behavior-based robotics),
configuration sensing, motion planning, uncertainty in robotics, map making,
grasping, manipulation, shape and object recognition, distributed robotics, and
applications of robotics. Students will build a robot in teams using a robot
building kit. They will use this robot to implement the algorithms discussed in
class in the context of a concrete task (for example, a robo-rat system for the
foraging task).
Prerequisite: facility with computers and programming (especially C), and
some exposure to algorithms and formal methods. Computer Science 23 and 25 are
recommended. Dist. TLA. Balkcom.
56. Numerical Analysis (Identical to Mathematics 56)
Not offered in the period from 06F through 07S
This course introduces the student to the concepts of modern numerical
analysis. The main emphasis will be on developing effective numerical methods
to solve problems in ordinary and partial differential equations. Other topics
will be chosen from optimization, approximation, Fourier Transform, and Monte
Carlo methods. The specific content will depend in part on the instructor.
Prerequisite: Computer Science 5 and Mathematics 33, or permission of the
instructor. Dist: QDS.
58. Operating Systems
06F, 07F: 11
This course studies how computer operating systems allocate resources and
create virtual machines for the execution of user jobs. Topics covered include
storage management, scheduling, concurrent processing, shared access to files,
synchronization, and data protection. Both abstract models and actual examples
of operating systems will be studied.
Prerequisite: Computer Science 23 and 37.
Computer Science 25 is recommended. Dist: TAS. Smith.
68. Principles of Programming Languages
07W: 2 08W: Arrange
This course provides a study of the principles of programming languages. The
course will focus on the similarities and differences among imperative,
functional, logical, and object-oriented programming languages. Topics include
formal definitions of languages and tools for automatic program translation,
control structures, parameter passing, scoping, types, and functions as
first-class objects. For each language category, implementation issues will be
discussed, and program development strategies illustrated through programming
exercises.
Prerequisite: Computer Science 23. Computer Science 25 and 37 are
recommended. Dist: TAS. Fromberger.
78. Computer Networks
07S: 2A 08S: Arrange
This course focuses on the communications protocols used in computer
networks: their functionality, specification, verification, implementation, and
performance; and how protocols work together to provide more complex services.
Aspects of network architectures are also considered. Laboratory projects are
an integral part of the course in which networking concepts are explored in
depth.
Prerequisite: Computer Science 23 and 37. Computer Science 25 is
recommended. Dist: TAS. Campbell.
80. (former 82) Reading Course
All terms: Arrange
Advanced undergraduates occasionally arrange with a faculty member a reading
course in a subject not occurring in regular courses.
82. Topics in Computer Graphics
Not offered in the period from 06F through 07S
85. Topics in Theoretical Computer Science
06F: 11 07W, 07S: Arrange
Each year a course in an advanced topic in theoretical computer science is
offered. Topics covered in recent years include combinatorial optimization,
computational geometry, cryptography, network flows, and distributed
algorithms. Students may receive credit for Computer Science 85 more than
once.
Prerequisite: Computer Science 25 or permission of instructor required.
Recommended prerequisite will vary with term. Consult the Instructor for the
topic. Dist: QDS. Jayanti (fall), Drysdale (winter), Fleischer,
Zomorodian (spring).
88. Topics in Computer Systems
06F: 10A, 2A
Each year a course in an advanced topic in Computer Systems is offered.
Topics covered in recent years include robotics, electronic commerce, and
multimedia. Students may receive credit for Computer Science 88 more than
once.
Prerequisite: Computer Science 23 or permission of instructor required.
Computer Science 25 and/or Computer Science 37 may be required in certain
terms. Recommended prerequisites will vary with term. Consult the Instructor
for the topic. Dist: TAS. Balkcom, Campbell (fall).
97. Honors Thesis Research
All terms: Arrange
Open only to students who are officially registered in the Honors Program.
Permission of the Undergraduate Advisor and thesis advisor required. This
course does not serve for distributive credit, and may be taken at most
twice.
98. EPICS: Engineering Projects in Community Service
06F, 07W, 07S, 07F, 08W, 08S: 10A
Participation in a software engineering group project in the context of
on-going partnerships with community service agencies. Group members are
responsible for all aspects of a software system, including iterative
requirements analysis, design, implementation, testing, and maintenance. The
course also stresses customer interactions, documentation, process, and
teamwork. The result is a software product of significant scope and significant
benefit to the community.
Prerequisite: Computer Science 23, 25 and 37, or permission of instructor.
Bailey-Kellogg.
99. Current Trends and Ethical Issues in Computer Science
Not offered in the period 06F through 07S
This course will survey current technological trends and ethical issues in
computer science. By the nature of the course, the specific topics will change
from year to year, but the emphasis will be on the basic components of computer
science. These include history, human-computer interaction, industry, hot or
speculative technologies, connectivity and access, parallel computing,
scientific computing, cryptography and privacy, current computing as reflected
in the popular press, and fault-tolerant computing. The ethical issues covered
will include the societal impact of information technology, invasion of
privacy, computer crime, ethical codes for professional organizations,
legislation for the information age, ethics at school and in the workplace,
intellectual property rights, and software patents.
Prerequisites: Computer Science 23, 25, and 37 or permission of the
instructor. This course is intended to be for seniors; any non-seniors must
receive permission from the instructor and the undergraduate advisor.
GRADUATE COURSES
Graduate students wishing to take a graduate course who have not passed the
listed Dartmouth prerequisite courses with a grade at least as good as the
median grade in the course must get written permission from the instructor in
order to enroll in the graduate course. Any undergraduate enrolling in a
graduate course must have the written permission of the instructor.
Some advanced undergraduate courses may be taken for graduate credit when
supplemented by work not required of undergraduates. The web contains
information about these courses.
104. Artificial Intelligence
Not offered in the period from 06F through 07S
This course is a graduate-level survey of artificial intelligence. It covers
the basic principles underlying artificial intelligence (search methods,
knowledge representation and 'expert systems,' planning, learning, etc.) and
examples of particular artificial intelligence applications areas (natural
language understanding, vision, robotics).
Prerequisite: Computer Science 44.
105. Algorithms and Data Structures
07W: Arrange
This course provides an introduction to algorithms and algorithm design
techniques at a level more advanced than a typical undergraduate course in
algorithms, yet basic enough to be applicable widely across the many subfields
of computer science. There is a strong emphasis on rigorously proving the
correctness of and running time bounds on the algorithms studied. Typical
techniques covered include, but are not limited to, randomization, amortized
analysis, linear programming and approximation. Typical problems include, but
are not limited to, splay trees, perfect hashing, skip lists, fast randomized
algorithms for minimum cuts and minimum spanning trees, maximum matching,
pattern matching, and some simple approximation algorithms: both combinatorial
and based on linear programming relaxation.
Prerequisites: Computer Science 25 and 39. Additionally, students are
expected to be familiar with basic concepts from graph theory, discrete
mathematics, linear algebra, and probability. Fleischer.
106. Numerical Linear Algebra (Identical to Engineering Science 106 and
Mathematics 116)
06F: 2 Not offered every year
The course examines in the context of modern computational practice
algorithms for solving linear systems Ax = b and Az = μx. Matrix decomposition
algorithms, matrix inversion, and eigenvector expansions are studied.
Algorithms for special matrix classes are featured, including symmetric
positive definite matrices, banded matrices, and sparse matrices. Error
analysis and complexity analysis of the algorithms are covered. The algorithms
are implemented for selected examples chosen from elimination methods (linear
systems), least squares (filters), linear programming, incidence matrices
(networks and graphs), diagonalization (convolution), sparse matrices (partial
differential equations).
Prerequisite: Computer Science 26, Mathematics 26, or Engineering Sciences
91. Students are to be familiar with approximation theory, error analysis,
direct and iterative techniques for solving linear systems, and discretization
of continuous problems to the level normally encountered in an undergraduate
course in numerical analysis. Rockmore.
107. Computer Architecture (Identical to Engineering 116)
06F, 07F: 10
This course provides an introduction to the field of computer architecture.
The history of the area will be examined from the first stored program computer
to current research issues. Topics covered will include successful and
unsuccessful machine designs, cache memory, virtual memory, pipelining,
instruction set design, RISC/CISC issues, and hardware/software tradeoffs.
Readings will be from the text and an extensive list of papers. Assignments
will include homeworks and a substantial project, intended to acquaint students
with open questions in computer architecture.
Prerequisite: Computer Science 37; Computer Science 58 is recommended.
Berk.
108. Advanced Operating Systems
07W, 08W: Arrange
This course covers advanced topics in operating systems, including issues
such as the hardware/software interface, operating-system structure, CPU
scheduling, concurrency, virtual memory, interprocess communication, file
systems, protection, security, fault tolerance, and transaction processing. The
course also considers many of these topics in the context of distributed
systems.
Prerequisite: Computer Science 58. Smith.
109. Theory of Computation
07S: Arrange
Building on the material covered in a standard undergraduate course, this
course studies aspects of both computability and complexity. The study of
computability includes Reductions, Rice's theorems, Post Correspondence
Problem, Valid Computations, Kleene Hierarchy, and the Recursion Theorem. The
study of complexity covers some results on space complexity (Savitch's Theorem,
Immerman's Theorem, Pspace), Cook-Levin Theorem and the Hardness of
Approximation. Additional topics are covered if there is time.
Prerequisite: Computer Science 39. Jayanti.
110. Writing, Presenting, and Evaluating Technical Papers in Computer
Science
Not offered in the period from 06F through 08S
Students will learn how to write technical papers in computer science, how
to present technical papers in a conference-talk setting, and how program
committees and journal editors evaluate technical papers. Writing topics
include the proper use of technical typesetting software, organization of
technical papers, and English usage. Students will write technical papers,
produce official course notes, and give oral presentations.
Prerequisite: Each student must submit a short expository piece to be
evaluated by the instructor at the start of the course; only those students
meeting a required level of competence will be permitted to take the course for
a grade. Students should also have a Computer Science background sufficient to
understand research papers.
Enrollment limited.
118. Programming Languages
07S: 10A 08S: Arrange
This course covers fundamental and advanced topics in the design,
implementation and use of imperative, functional, logical and object-oriented
programming languages. Topics covered include formal definitions of languages,
tools for automatic program translation, parameter passing, scoping, type
systems, control structures and automatic memory management. For each language
category, implementation issues will be discussed, and program development
strategies illustrated through programming exercises.
Prerequisite: Computer Science 68. Undergraduate courses in compilers
(Computer Science 48) are recommended. McIlroy, McKeeman.
180. Reading Course
181. Special Topics Seminar
182. Topics in Computer Graphics.
Not offered in the period from 06F through 07S
185. Algorithms Seminar
06F: 11 (Jayanti).
07W: Arrange (Drysdale).
07S: Arrange (Fleischer),Arrange (Zomorodian).
186. Numerical Analysis Seminar
187. Computer Architecture and Hardware Seminar
188. Computer Systems Seminar
06F: 10A (Balkcom), 2A (Campbell).
Prerequisite: Computer Science 23, 25, and 37, or permission of the
instructor. Computer Science 58 may be recommended.
257. Supervised Undergraduate Teaching
May be taken multiple times for credit. One course equivalent.
297. Graduate Research
Student participates in research under the supervision of a faculty member.
May be taken multiple times for credit. One course equivalent.
298. Thesis Research
Student participates in research under the supervision of a faculty member.
May be taken multiple times for credit. Two course equivalents.
299. Full-Time Thesis Research
Student participates in research under the supervision of a faculty member.
May be taken multiple times for credit. Three course equivalents.
|
