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). (NS).

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 (MacWrite), databases (FileMaker Pro), and spreadsheets (Excel); students also sign on the 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 an outline of lecture notes, selected articles on social issues, and tutorials on laboratory topics. (Finerman)

183(283)/EECS 183. Elementary Programming Concepts. (4). (NS).

This is an introductory course for students who may or may not plan to concentrate in computer science or engineering. It is designed to give students a good fundamental knowledge of programming techniques in a high-level language. Suggested as a prerequisite for CS/EECS 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. (Ford-Holevinski)

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

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).

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). (4). (NS).

The goals of this course include concepts of information representation, algorithms, processes and processors, syntax, semantics, 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.

283(383)/EECS 283. Programming and Computer Systems. CS 183 or Engin. 103 or 104. Not intended for CS or Computer Engineering concentrators. (4). (NS).

This course is an extension of CS 183. A firm knowledge of Pascal which need not include dynamic data structures is prerequisite. Advanced topics in Pascal, including the implementation of linked lists, trees, and hashing. Searching and sorting techniques. Students will write several programs in Pascal. Computer Usage: four or five homework assignments requiring use of an IBM mainframe computer are required. (Flanigan)

284/EECS 284. Introduction to a Programming Language or System. (1). (Excl).
Section 001.
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. (Ford-Holevinski)

Section 002. This course is for students who already know how to program in some language other than Pascal. It is a 14-lecture one-credit mini-course which will focus on preparing students for CS 280, the first required programming course for Computer Science concentrators, but is suitable for anyone wanting to learn to program in Pascal. Topics will range from basic Pascal control structures (IF, CASE, WHILE, REPEAT, and FOR loops; PROCEDURES and FUNCTIONS) through the use of data structures such as arrays, strings, records, pointers and linked lists. (Ford-Holevinski)

300/EECS 300/Math. 300. Mathematical Methods in System Analysis. Math. 216 or 316 or the equivalent. No credit granted to those who have completed or are enrolled in Math. 448. (3). (Excl).

An introductory course in operational mathematics as embodied in Laplace Transforms, Fourier Series, Fourier Transforms and Complex Variables, with emphasis on their application to the solution of systems of linear differential equations. The response of linear systems to step, impulse, and sinusoidal forcing functions.

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

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).

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. Lecture and laboratory.

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

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.

381/EECS 381. Systems Programming. CS 380. (4). (Excl).

Design and implementation of basic systems programming tools and infrastructure. Topics to be covered include assembly language programming, assemblers, macro processors, linkers and loaders, and I/0 drivers, etc., and programming projects will involve the design and implementation of such systems. Students will also write some programs in assembly language.

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. 417 or 513. (3). (Excl).

See Mathematics 419 for description.

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

Basic concepts of computer architecture and organization. Computer evolution. Design methodology. Performance evaluation. Elementary queueing 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).

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

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

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.

482/EECS 482. Introduction to Operating Systems. CS 370 and 381. (4). (Excl).

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 370 and 381. (4). (Excl).

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 473. (3). (Excl).

Concepts and methods in the definition and management of large integrated data bases for organizational information systems. Functions and objectives of existing file and data management will be considered and methods of analyzing proposals for new data management software will be studied; database administration, database design, and data security problems.

485/EECS 485. Principles of Programming Languages. CS 380. (4). (Excl).

Principles of programming languages including Algol-like languages, logic programming and an introduction to program verification and semantics.

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

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.

489/EECS 489. Computer Networks. CS 482. (3). (Excl).

Hardware and software architectures employed in building modern computer networks. Emphasis is placed on architectural and design considerations over actual implementation issues. Tradeoffs in network architectures and in understanding what choices are available. Software problems assigned.

492/EECS 492. Introduction to Artificial Intelligence. CS 303 and CS 380. (4). (Excl).

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

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.

543/EECS 543. Knowledge-Based Computer Vision. CS 442 and CS 492. (3). (Excl).

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.

545/EECS 545. Machine Learning. CS 492. (3). (Excl).

Survey of recent research in learning in artofocoa; intelligent systems. Topics include learning based on examples, instructions, analogy, discovery, experimentation, observation, problem solving and explanation. The cognitive aspects of learning will also be studied.

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

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.

571/EECS 571. Principles of Real-Time Computing. CS 470 and CS 482 or permission of instructor. (3). (Excl).

Principles of real-time computing based on high performance, ultra reliability and environmental interface. Architectures, algorithms, operating systems and applications that deal with time as the most important source. Real-time scheduling, communications and performance evaluation.

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

Formal grammars, recursive functions, logic, complexity theory.

575/EECS 575. Theoretical Computer Science II. CS 574. (4). (Excl).

Advanced computational complexity, intractability, classical probability and information theory, algorithmic information theory, and special topics such as computational algebra, concurrency, semantics, and verification.

579/EECS 579. Digital System Testing. CS 478. (3). (Excl).

Overview of fault-tolerant computing. Fault sources and models. Testing process. Combinational circuit testing. D-Algorithm and PODEM. Sequential circuit testing. Checking experiments. RAM and microprocessor testing. Fault simulation. Design for testability. Testability measures. Self-testing circuits and systems.

581/EECS 581. Software Engineering Tools. CS 481 or equivalent programming experience. (3). (Excl).

Fundamental areas of software engineering including life cycle paradigms, metrics, and tools. Information hiding architecture, modular languages, design methodologies, incremental programming, and very high level languages.

582/EECS 582. Advanced Operating Systems. CS 482. (4). (Excl).

Course discusses advanced topics and research issues in operating systems. Topics will be drawn from a variety of operating systems areas such as distributed systems and languages, networking, security and protection, real-time systems, modelling and analysis, etc.

584/EECS 584. Distributed Database Concepts. CS 484. (3). (Excl).

Database design methodologies, distributed database technology and developments in heterogeneous systems. Distributed database design and implementation issues such as transaction management, concurrency control, security, and query optimization. Database design includes semantic data modeling, transformation to SQL, normalization theory, physical design and data allocation strategies.

586/EECS 586. Design and Analysis of Algorithms. CS 380. (3). (Excl).

Design of algorithms for nonnumeric problems involving sorting, searching, scheduling, graph theory, and geometry. Design techniques such as approximation, branch-and-bound, divide-and-conquer, dynamic programming, greed, and randomization applied to polynomial and NP-hard problems. Analysis of time and space utilization.

588/EECS 588/IOE 578/ME 551. Geometric Modeling. CS 487 or ME 454 or permission of instructor. (3). (Excl).

Individual or group study of topics in geometric modeling and computer graphics. Geometric data structures for curves, surfaces, and volume parameterization, and topological data structures for vertices, edges, faces, and bodies. Algorithms for set operations, Euler operations and deformations. Design and experimentation with geometric modelling facilities.

589/EECS 589. Raster Graphics-Principles and Applications. CS 487. (3). (Excl).

A detailed account of modern raster-based computer graphics. Topics include solid area scan conversion, color theory and application, hidden surface elimination, shading, highlights, animation, painting, and standardized graphics software.

592/EECS 592. Advanced Artificial Intelligence. CS 492, or permission of instructor. (4). (Excl).

Advanced topics in artificial intelligence. Issues in knowledge representation, knowledge based systems, problem solving, planning and other topics will be discussed. Students work on several projects.

594/EECS 594. Introduction to Adaptive Systems. CS 303 and Math. 425. (3). (Excl).

Programs and automata that "learn" by adapting to their environment; programs that utilize genetic algorithms for learning. Samuel strategies, realistic neural networks, connectionist systems, classifier systems, and related models of cognition. Artificial intelligence systems, such as NETL and SOAR, are examined for their impact upon machine learning and cognitive science.

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

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


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