Computer Science Department

Chair: Jennifer Walter; Professor: Nancy M. Ide; Associate Professors: Thomas Ellmanab, Luke Hunsberger, Jennifer Walter; Assistant Professor: Marc L. Smith; Visiting Assistant Professor: Barry Jones; Adjunct Associate Professor: James Ten Eyck; Adjunct Instructor: Alan G Labouseur; Lab Coordinator: Greg Priest-Dorman.

Requirements for Concentration: 13 units, including Computer Science 101, 102, 145, 203, 224, 240, 241, 245, 331, 334, plus any two other graded 300-level Computer Science courses, and Mathematics 221. No course numbered 200 or higher may be elected NRO and counted toward the requirements for concentration.

Requirements for the Correlate: Computer Science 101, 102 and 145; 240 or 241, plus at least one additional 200-level Computer Science course and one 300-level Computer Science course. Students are advised to consult with the department to determine the courses most appropriate to their interests. No course numbered 200 or higher may be elected NRO and counted toward the requirements for the correlate.

Advanced Placement: Students eligible for Advanced Placement may be able to bypass Computer Science 101 or 102 with permission of the department.  A bypassed course cannot be counted toward the 13-unit requirement for the Computer Science concentration or the 6-unit requirement for the Computer Science correlate.

Departmental Honors : Satisfactory completion of Computer Science 300-301, a graded research experience for senior majors, is required for departmental honors. Computer Science 300-301 may not be substituted for 300-level elective courses satisfying the requirements for the major.

Non-Majors: Students majoring in the sciences are advised to complete Computer Science 101, 102, and 145, or to complete a correlate sequence in Computer Science.

I. Introductory

101a or b. Computer Science I: Problem-Solving and Abstraction (1)

Introduces the fundamentals of computer science by describing the functional and object-oriented styles of programming, examining basic sequential and recursive algorithms, and studying linear data structures including arrays and linear collection classes such as vectors, stacks, queues, and lists. Discusses elementary programming patterns. Presents techniques for the creation of simple graphical user interfaces. Applies these ideas to sample applications that illustrate the breadth of computer science. A weekly laboratory period provides guided hands-on experience.

Open to all classes.

Two 75-minute meetings plus laboratory.

102a or b. Computer Science II: Data Structures and Algorithms (1)

Continues CMPU 101. Examines object-oriented programming and associated algorithms using more complex data structures as the focus. Discusses nested structures and non-linear structures including hash tables, trees, and graphs. Emphasizes abstraction, encapsulation, inheritance, polymorphism, recursion, and object-oriented design patterns. Applies these ideas to sample applications that illustrate the breadth of computer science. A weekly laboratory period provides guided hands-on experience.

Open to all classes.

Two 75-minute meetings plus laboratory.

Prerequisite: Computer Science 101.

145b. Foundations of Computer Science (1)

Introduces the theoretical, structural and algorithmic foundations of computer science. Topics include: sets, relations, functions, recursive data structures, recursive functions, induction, structural induction, probability, logic, boolean algebra, proving program correctness, the lambda calculus. Concepts are reinforced by regular programming assignments and a weekly laboratory period provides guided hands-on experience.Mr. Hunsberger.

Open to all classes.

Prerequisite: Computer Science 101.

II. Intermediate

203a. Computer Science III: Software Design and Implementation (1)

Develops techniques for design and implementation of complex software systems. Topics include object-oriented modeling, design patterns, component libraries, inheritance, parametric polymorphism, generic algorithms, containers, iterators, function objects and storage management. Development of a software system of significant complexity is required. A weekly laboratory period provides guided hands-on experience. Mr. Jones.

Prerequisite: Computer Science 102.

224b. Computer Organization (1)

Examines the hierarchical structure of computing systems, from digital logic and microprogramming through machine and assembly languages. Topics include the structure and workings of the central processor, instruction execution, memory and register organization, addressing schemes, input and output channels, and control sequencing. The course includes a weekly hardware/software laboratory where digital logic is explored and assembly language programming projects are implemented. Mr. Jones.

Prerequisite: Computer Science 102 and 145.

240a. Language Theory and Computation (1)

Study of regular sets, context free grammars and languages, finite and push-down automata, as well as more powerful models of computation, such as Turing machines. Provides theoretical foundations for Computer Science 331, Compiler Design. Ms. Ide.

Prerequisite: Computer Science 145.

241b. Algorithmics (1)

Introduces the systematic study of algorithms and their analysis with regard to time and space complexity. Topics include divide-and-conquer, dynamic programming, greediness, randomization, upper and lower-bound analysis, and introduction to NP completeness. Emphasis is placed on general design and analysis techniques that underlie algorithmic paradigms. Builds a foundation for advanced work in computer science. The department.

Prerequisite: Computer Science 145.

245b. Declarative Programming Models (1)

Declarative programming languages are important alternatives to the imperative languages used in most software systems. This course covers two kinds of declarative programming: functional programming and logic programming. Topics include the semantics of declarative languages, techniques for programming in declarative languages, and the use of mathematical logic as a tool for reasoning about programs. Mr. Hunsberger.

Prerequisite: Computer Science 145.

250b. Modeling, Simulation and Analysis (1)

Principles of computation in the sciences, driven by current applications in biology, physics, chemistry, natural and social sciences, and computer science. Topics include: Discrete and continuous stochastic models, random number generation, elementary statistics, numerical analysis and algorithms, discrete event simulation, and point and interval parameter estimation. Students pursue projects that involve modeling phenomena in 2-3 different fields and simulate the model in order to understand mechanisms and/or explore new hypotheses or conditions. In 2010/2011, the course includes modules on applications to problems in chemistry, physics, and cognitive science. Ms. Ide.

Prerequisite: Cmpu 102, Math 122 or 125. Cmpu 241 and /or Math 221 recommended but not required.

290a or b. Field Work (1/2 or 1)

295a or b. Special Topics (1/2 or 1)

Intermediate-level treatment of specialized topics in computer science.

Prerequisite: permission of instructor.

298a or b. Independent Work (1/2 or 1)

Prerequisite: permission of instructor

III. Advanced

Two units of 200-level computer science are prerequisite for entry into 300-level courses; see each course for specific courses required or exceptions.

300a. Senior Research and Thesis (1/2)

Investigation and critical analysis of a topic in experimental or theoretical computer science. Experimental research may include building or experimentation with a non-trivial hardware or software system. A student electing this course must first gain, by submission of a written research proposal, the support of at least one member of the computer science faculty with whom to work out details of a research strategy. The formal research proposal, a written thesis, and oral presentation of results are required for the course. A second faculty member participates in both the planning of the research and final evaluation. The department.

Year-long course, 300-301.

Prerequisite: Permission of the department.

301b. Senior Research and Thesis (1/2)

Investigation and critical analysis of a topic in experimental or theoretical computer science. Experimental research may include building or experimentation with a nontrivial hardware or software system. A student electing this course must first gain, by submission of a written research proposal, the support of at least one member of the computer science faculty with whom to work out details of a research strategy. The formal research proposal, a written thesis, and oral presentation of results are required for the course. A second faculty member participates in both the planning of the research and final evaluation. The department.

Year-long course, 300-301.

Prerequisite: Minimum 3.5 GPA in 200 and 300-level Computer Science coursework at the end of the junior year, and permission of the department.

324b. Computer Architecture (1)

An exploration of current research areas in computer organization including an examination of data-flow, microcode, cache memory, distributed, parallel, and other nonstandard architectures, and related topics.

Offered Alternate years.

Prerequisite: Computer Science 224.

325. Microcomputers and Digital Electronics (1)

Advanced seminar in the architecture and implementation of microprocessors. Topics include digital logic, memory and processor interfaces, interrupt handling, and serial I/O methods. Differences among logic implementations such as TTL, CMOS, and ECL are considered. Students participate in the design and implementation of a microcomputer.

Alternate years.

Prerequisite: Computer Science 224.

331b. Compilers (1)

Studies the theory of automata for language recognition as well as the implementation of actual compilers for programming languages. During the semester students develop modules comprising the front-end of a compiler for a high-level computer. Ms. Ide.

Prerequisite: Computer Science 224, 240, 245, or permission of instructor.

334a. Operating Systems (1)

Deals with the theory and implementation of the software that governs the management of system resources. Topics that are covered include file organization, process scheduling, system services, memory management, security methods, resource contention, and design principles. Operating systems for parallel and distributed processing, real-time processing, virtual machines, and networking are also considered. Mr. Jones.

Prerequisite: Computer Science 203, 224.

353b. Bioinformatics (1)

(Same as Biology 353) DNA is the blueprint of life. Although it's composed of only four nucleotide "letters" (A, C, T, G), the order and arrangement of these letters in a genome gives rise to the diversity of life on earth. Thousands of genomes have been partially sequenced, representing billions of nucleotides. How can we reach this vast expanse of sequence data to find patterns that provide answers to ecological, evolutionary, agricultural, and biomedical questions? Bioinformatics applies high-performance computing to discover patterns in large sequence datasets. In this class students from biology and computer science work together to formulate interesting biological questions and to design algorithms and computational experiments to answer them. Mr. Smith.

Prerequisite: Computer Science 203 or permission of the instructor.

365a. Artificial Intelligence (1)

An introduction to Artificial Intelligence as a discipline of Computer Science, covering the traditional foundations of the field and a selection of recent advances. Traditional topics include: search, two-player adversarial games, constraint satisfaction, knowledge representation and reasoning, and planning. Additional topics will vary from year to year and will be selected from the following: reasoning about time, probabilistic reasoning, neural networks, philosophical foundations, multi- agent systems, robotics, and recent advances in planning. Significant programming assignments and a course project complement the material presented in class. Mr. Hunsberger.

Offered Alternate years.

Prerequisite: Computer Science 245.

366. Computational Linguistics (1)

Addresses the fundamental question at the intersection of human languages and computer science: how can computers acquire, comprehend and produce natural languages such as English? Introduces computational methods for modeling human language, including morphology, syntax, semantics and discourse; corpus-based and statistical methods for language analysis; and natural language applications such as information extraction and retrieval, summarization, and machine translation. Students gain experience with sophisticated systems for linguistic analysis and machine learning.

Prerequisite: Computer Science 240 or permission of the instructor.

375. Networks (1)

Provides an introduction to the design of network-based applications. Topics include Internet protocols, client/server-based paradigms (including peer-to-peer), relational database design, data normalization techniques, SQL, and security. Web-based applications provide an infrastructure and motivation for the intersection of networks and database systems. Programming assignments and projects emphasize key concepts.

Prerequisite: Computer Science 203 or permission of instructor.

Offered Alternate years.

377a. Parallel Programming (1)

An introduction to parallel computing, with coverage of parallel architectures, programming models, and techniques. Topics include SIMD and MIMD models, shared-memory and message-passing styles of computation, synchronization, deadlock, and parallel language design. Students are exposed to common techniques for solving problems in sorting, searching, numerical methods, and graph theory, and gain practical experience through programming assignments run on a parallel processing system. Mr. Smith.

Prerequisite: Computer Science 203, 224.

Offered Alternate years.

378a. Graphics (1)

A survey of computational and mathematical techniques for modeling and rendering realistic images of three-dimensional scenes. Topics include: event-driven user interfaces; geometric transformations and projections; scene graphs; implicit and parametric surfaces; models of color and light; surface shading and texturing; local and global rendering algorithms; and an introduction to computer animation. The department.

Offered Alternate years.

Prerequisite: Computer Science 203 and Mathematics 221.

379. Computer Animation: Art, Science and Criticism (1)

(Same as Art 379b and Media Studies 379b) An interdisciplinary course in Computer Animation aimed at students with previous experience in Computer Science, Studio Art, or Media Studies. The course introduces students to mathematical and computational principles and techniques for describing the shape, motion and shading of three-dimensional figures in Computer Animation. It introduces students to artistic principles and techniques used in drawing, painting and sculpture, as they are translated into the context of Computer Animation. It also encourages students to critically examine Computer Animation as a medium of communication. Finally, the course exposes students to issues that arise when people from different scholarly cultures attempt to collaborate on a project of mutual interest. The course is structured as a series of animation projects interleaved with screenings and classroom discussions. A weekly laboratory period provides guided hands-on experience.

Prerequisite: Permission of the instructor.

Offered Alternate years.

Not offered in 2010/11.

395. Special Topics (1)

In-depth treatment of specialized topics in Computer Science.

399a or b. Senior Independent Work (1/2 or 1)