Courses in Computer Science (Division 353)

181/EECS 181. Introduction to Computer Systems. Credit is granted for only one course among CS 181, Engin. 103, and Engin. 104. (4). (Excl). (BS).

Computer Science 181 is meant for students in the liberal arts and related areas with little or no background in computing systems who wish to become computer literate. Lectures cover general computing topics: hardware, networks, operating systems, programming, history and social issues. Students get hands-on experience in the laboratories using software packages for text processing (Microsoft Word), databases (FileMaker Pro), and spreadsheets (Excel); students also sign on a central computing system to send and receive electronic messages and to participate in an electronic conference. Assignments include three major projects. The course pack contains a syllabus, course rules, and tutorials on laboratory topics. Students are graded on laboratory participation, quality of their project work, quizzes, and exams. A text is required. Students are urged to be waitlisted. Explanation for resolution of the waitlist is given at the first lecture. Students not attending the first laboratory session are assumed to have dropped the course.

183/EECS 183. Elementary Programming Concepts. (4). (NS). (BS).

This is an introductory course for students who desire a good working knowledge of basic programming techniques using a high-level language. The course is suitable for both non-concentrators and pre-concentrators in Computer Science and Computer Engineering. Suggested as a prerequisite for CS 280 for students whose programming background is not strong. Introduction to a high-level programming language, top-down design, and structured programming. Basic searching and sorting techniques. Basic data structures; arrays and records; introduction to pointers and dynamic data structures. No previous experience in computing or programming is assumed. Students will write and debug several computer programs. Computer Usage: five or six assignments are given, each requiring the student to write and debug programs using THINK Pascal on the Macintosh microcomputer.

216/EECS 216. Circuit Analysis. Prior or concurrent enrollment in Math. 215. (4). (Excl). (BS).

Resistive circuit elements; mesh and node analysis, network theorems; network graphs and independence; energy storage elements; one- and two-time-constant circuits; phasors and a.c. steady-state analysis; complex frequency and network functions; frequency response and resonance. Lecture and laboratory.

270/EECS 270. Introduction to Logic Design. (4). (Excl). (BS).

Binary and non-binary systems, Boolean algebra digital design techniques, logic gates, logic minimization, standard combinational circuits, sequential circuits, flip-flops, synthesis of synchronous sequential circuits, PLA's, ROM's, RAM's, arithmetic circuits, computer-aided design. Laboratory includes hardware design and CAD experiments.

280/EECS 280. Programming and Introductory Data Structures. Math. 115 and (CS 183 or 284 or Engineering 104, or by placement test in PASCAL). Two credits granted to those who have completed CS 283. (4). (NS). (BS).

The goals of this course include concepts of information representation, algorithms, processes and processors, syntax, semantics, data structures and grammar. Students learn the basics of programming style, debugging, error control, computational correctness, and program verification. Prerequisites include advanced algebra and first term calculus, and computer literacy (knowledge of Pascal). Topics include techniques of algorithm development and effective programming in Pascal and in the C language, top-down analysis, structured programming, testing and program correctness. Program language syntax and static and run-time semantics. Scope, procedure instantiation, recursion, abstract data types, and parameter passing methods. Structured data types, pointers, linked data structures, stacks, queues, arrays, records, and trees. Cost:1 WL:1

284/EECS 284. Introduction to a Programming Language or System. Some programming knowledge is required.No credit granted for the C minicourse to those students who have completed CS 280. (1). (Excl). (BS).
Section 001 C.
This course is for students who already know how to program in some language other than C. It is a 14-lecture one-credit mini-course which will focus on covering the fundamentals of the C language. Topics will range from basic C control structures (if, switch, while, do while, for, and functions) through the use of basic data structures such as arrays, strings, structures, pointers and linked lists. We will cover as many of the standard C library functions as possible. ANSI standard C is utilized.

303/EECS 303. Discrete Structures. Math. 115. (4). (Excl). (BS).

Fundamental concepts of algebra; partially ordered sets, lattices, Boolean algebras, semi-groups, rings, polynomial rings. Graphical representation of algebraic systems; graphs, directed graphs. Application of the concepts to various areas of computer science and engineering.

370/EECS 370. Introduction to Computer Organization. CS 270 and CS 280. (4). (Excl). (BS).

Computer organization will be presented as a hierarchy of virtual machines representing the different abstractions from which computers can be viewed. These include the logic level, microprogramming level, and assembly language level. Lab experiments will explore the design of a micro-programmed computer.

380/EECS 380. Data Structures and Algorithms. CS 280 and CS 303. (4). (NS). (BS).

Abstract data types. Recurrence relations and recursions. Advanced data structures: sparse matrices, generalized lists, strings. Tree-searching algorithms, graph algorithms, general searching and sorting. Dynamic storage management. Analysis of algorithms and 0-notation. Complexity. Top-down program development: design, implementation testing, modularity. Several programming assignments.

400/EECS 400/Math. 419. Linear Spaces and Matrix Theory. Four terms of college mathematics beyond Math. 110. No credit granted to those who have completed or are enrolled in Math. 217 or Math. 513. One credit granted to those who have completed Math. 417. (3). (Excl). (BS).

See Mathematics 419.

426/EECS 426. Fundamentals of Electronic Computer-Aided Design. CS 280 and senior standing. (3). (Excl). (BS).

Course will address, in roughly equal proportion: (1) modeling, simulation, and verification at various abstraction levels; (2) behavioral and logic synthesis; and (3) placement and routing. Emphasis will be on understanding the underlying techniques and algorithms of these various CAD areas rather than on the use of specific CAD tools.

442/EECS 442. Computer Vision. CS 303 and CS 380. (3). (Excl). (BS).

Computational methods for the recovery, representation, and application of visual information. Topics from image formation, binary images, digital geometry, similarity and dissimilarity detection, matching, curve and surface fitting, constraint propagation and relaxation labeling, stereo, shading, texture, object representation and recognition, dynamic scene analysis, and knowledge based techniques. Hardware /software techniques.

470/EECS 470. Computer Architecture. CS 370. (4). (Excl). (BS).

Basic concepts of computer architecture and organization. Computer evolution. Design methodology. Performance evaluation. Elementary queuing models. CPU architecture. Introductions sets. ALU design. Hardwired and microprogrammed control. Nanoprogramming. Memory hierarchies. Virtual memory. Cache design. Input-output architectures. Interrupts and DMA. I/O processors. Parallel processing. Pipelined processors. Multiprocessors.

476/EECS 476. Foundations of Computer Science. CS 280 and 303 or equivalent. (4). (Excl). (BS).

An introduction to computation theory: finite automata, regular languages, pushdown automata, context-free languages. Turing machines, recursive languages and functions, and computational complexity.

477/EECS 477. Introduction to Algorithms. CS 380. (3). (Excl). (BS).

Fundamental techniques for designing efficient algorithms and basic mathematical methods for analyzing their performance. Paradigms for algorithm design: divide-and-conquer, greedy methods, graph search techniques, dynamic programming. Design of efficient data structures and analysis of the running time and space requirements of algorithms in the worst and average cases.

478/EECS 478. Switching and Sequential Systems. CS 270 and CS 303, and senior or graduate standing. (3). (Excl). (BS).

An introduction to the theory of switching networks and sequential systems. Switching functions and realizations, threshold logic, fault detection, connectedness and distinguishability, equivalence and minimality, state identification, system decomposition.

481/EECS 481. Software Engineering. CS 380. (4). (Excl). (BS).

Pragmatic aspects of the production of software systems, dealing with structuring principles, design methodologies and informal analysis. Emphasis is given to development of large, complex software systems. A term project is usually required. WL:1

482/EECS 482. Introduction to Operating Systems. CS 370 and 380. (4). (Excl). (BS).

Operating system functions and implementations: multitasking; concurrency and synchronization; deadlock; scheduling; resource allocation; real and virtual memory management; input/output; file systems. Students write several substantial programs dealing with concurrency and synchronization in a multitask environment.

483/EECS 483. Compiler Construction. CS 380 and 476. (4). (Excl). (BS).

Introduction to compiling techniques including parsing algorithms, semantic processing, and optimization. Students implement a compiler for a substantial programming language using a compiler generating system.

484/EECS 484/IOE 484. Database Management Systems. CS 380 or IOE 373. (3). (Excl). (BS).

Concepts and methods for the design, creation, query and management of large enterprise databases. Functions and characteristics of the leading database management systems. Query languages such as SQL, forms, embedded SQL, and application development tools. Database design, normalization, access methods, query optmization, transaction management and concurrency control, recovery, and integrity.

487/EECS 487/IOE 478. Interactive Computer Graphics. CS 380 or IOE 373, and senior standing. (3). (Excl). (BS).

Graphics devices and fundamentals of operation. Two dimensional and three dimensional transformations. Interactive graphical techniques and applications. Three dimensional graphics, perspective transformation, hidden line elimination. Data structures and languages for graphics. Interactive graphical programming.

492/EECS 492. Introduction to Artificial Intelligence. CS 380. (4). (Excl). (BS).

Basic artificial intelligence methods using LISP. Topics covered include search, rule-based systems, logic, constraint satisfaction, and knowledge representation.

493/EECS 493/IOE 437. User Interface Design and Analysis. CS 481. (3). (Excl). (BS).

Current theory and design techniques concerning how user interfaces for computer systems should be designed to be easy to learn and use. Focus on cognitive factors, such as the amount of learning required, and the information-processing load imposed on the user, rather than ergonomic factors.

500. Special Study. Graduate or undergraduate concentration in Computer Science; and permission of instructor. (1-6). (Excl). (INDEPENDENT). May be repeated for credit.

Students are introduced to the frontiers of System Science research. Sections 001, 002, and 003 are devoted, respectively, to Communications, Control, and Signal Processing. The tutorials are delivered by leaders of the respective research fields, invited from academia and industry. The presentations are self-contained and accessible to all graduate students in Systems Science.

CS 505/EECS 505/IOE 511/Aero. 577/Math 562. Continuous Optimization Methods. Math. 217, 417 or 419. (3). (Excl). (BS).

See Math 562.

506/EECS 506. Computing System Evaluation. CS 183 or 280, and CS 370 and EECS 501. (3). (Excl). (BS).

Theory and application of analytic methods for evaluating the performance of reliability of computing systems. Measures of performance, reliability, and performability. Reliability evaluation: classification and representation of faults, stochastic process models, coherent systems. Performance evaluation: Markovian queueing models, networks of queues. Unified performance-reliability evaluation. WL:1

543/EECS 543. Knowledge-Based Systems. CS 492 and permission of instructor. (3). (Excl). (BS).

Application of topics in AI to Computer Vision. Central issues are introduced through a critical examination of working image-interpretation systems. Topics: representation of geometric structure, and non-geometric characteristics relation of image features to object structure, reasoning, dealing with uncertainty, and dynamic interpretation. Programming required.

570/EECS 570. Parallel Computer Architecture. CS 470. (3). (Excl). (BS).

Pipelining and operation overlapping, SIMD and MIMD architectures. Numeric and non-numeric applications. VLSI, WSI architectures for parallel computing, performance evaluation. Case studies and term projects. WL:1

574/EECS 574. Theoretical Computer Science I. CS 476. (4). (Excl). (BS).

Formal grammars, recursive functions, logic, complexity theory. Cost:2 WL:1

595/EECS 595/Ling. 541. Natural Language Processing. Senior standing. (3). (Excl). (BS).

See Linguistics 541. (DeGraff)

598/EECS 598. Special Topics in Electrical Engineering and Computer Science. Permission of instructor or advisor. (1-4). (Excl). (BS). May be repeated for credit.

Topics of current interest in electrical engineering and computer science. Lectures, seminar or laboratory.


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