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).

Introduces students to computers. Focuses on software, hardware, and social impact of computers. Elementary programming concepts, software packages and applications, word processing, data communications, information management, input-output, data entry, computer hardware components and storage devices, microcomputers, and ethics in computing. Programming assignments using a personal computer. Term paper required. Cost:2 WL:1

183(283)/EECS 183. Elementary Programming Concepts. Not intended for CS or Computer Engineering concentrators. No credit granted to those who have completed or are enrolled in Engin. 103 or 104. (4). (NS).

Introduction to a high level programming language, top-down analysis, and structured programming. Basic searching and sorting techniques. No previous experience in computer or programming is assumed. Students will write and debug several computer programs. Not intended for computer science or computer engineering majors. Cost:2 WL:1

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. Lectures and laboratory. Cost:3 WL:1

280/EECS 280. Programming and Introductory Data Structures. Math. 115 and familiarity with programming. Students with credit for CS 183 can only elect CS 280 for 2 credits. (4). (NS).

Techniques of algorithm development and effective programming, top-down analysis, structured programming, testing and program correctness. Program language syntax and static and run-time semantics. Scope, procedure instantation, recursion, abstract data types, and parameter passing methods. Structured data types, pointers, linked data structures, stacks, queues, arrays, records, and trees. Cost:2 WL:1

283(383)/EECS 283. Programming and Computer Systems. CS 183 or equivalent. (4). (NS).

Advanced topics in PASCAL, including the implementation of linked lists, trees, and hashing. Searching and sorting techniques. Selected topics in programming language theory. Students will write several programs in Pascal. Cost:2 WL:1

284/EECS 284. Introduction to a Programming Language or System. CS 184 or equivalent. (1). (Excl). May be repeated for a total of 3 credits.

A seven week mini-course covering the fundamentals of a programming language such as C, PASCAL, LISP, SNOBOL, Prolog, or Modular-2, or a system such as UNIX. Programming problems will be assigned. Specific languages or systems to be offered will be announced in advance. Cost:3 WL:1

300/EECS 300/Math. 300. Mathematical Models in System Analysis. Math. 216. No credit granted to those who have completed or are enrolled in CS 300 and 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. WL:1

303/EECS 303. Algebraic Foundations of Computer Engineering. Math. 115. (3). (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 these concepts to various areas of computer science and engineering. WL:1 Cost:2

370/EECS 370. Introduction to Computer Organization. CS 270 and CS 280; or CS 303 and CS 381. (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. Cost:3 WL:1

380/EECS 380. Data Structures and Algorithms. CS 280; and CS 303 or Math. 312. (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 0-notation. Complexity. Top-down program development: design, implementation testing modularity. Several program assignments. Cost:4 WL:1

381/EECS 381. Assembly Language Programming. CS 280. (3). (NS).

Machine structure and organization, data representation, memory addressing methods, use of registers, bit manipulation, integer and floating point arithmetic, program linking and subroutines, macro-instructions, program debugging, assemblers and loaders. Students write several programs in IBM 370 Assembler language. Three one-hour lectures and a one-hour discussion per week. Cost:3 WL:1

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

Finite dimensional linear spaces and matrix representations of linear transformations. Bases, subspaces, determinants, eigenvectors, and canonical forms. Structure of solutions of systems of linear equations. Applications to differential and difference equations. The course provides more depth and content than Math 417. Math 513 is the proper election for students contemplating research in mathematics.

470/EECS 470. Computer Architecture. CS 370. (3). (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. Cost:3 WL:1

474/EECS 474. Digital Design Laboratory. EECS 373 or CS 470. (2). (Excl).

Realistic design problems in digital system engineering. Design, construction, and demonstration of devices which operate alone or in conjunction with digital computers in the laboratory. Lecture and laboratory. WL:1

476/EECS 476. Foundations of Computer Science. CS 280, and either CS 303 or Math. 312 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. Cost:3 WL:1

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. Cost:3 WL:1

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

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. Cost:3 WL:1

482/EECS 482. Introduction to Operating Systems. CS 370, CS 380, and CS 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. Cost:2 WL:1

483/EECS 483. Compiler Construction. CS 370, CS 380, and CS 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. Cost:2 WL:1

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 systems will be considered and methods of analyzing proposals for new data management software will be studied; database administration, database design, and data security problems. Cost:2 WL:1

486/EECS 486. Ada Based Software Environment CS 380. (3). (Excl).

Software design concepts such as data and program abstraction, package based decomposition of large systems, real-time task control, and Ada based programming environment. The Ada language will be used. The student is required to complete one medium size and several small size programming projects. Cost:2 WL:1

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. Cost:2 WL:1

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. Cost:3 WL:1

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. Cost:2 WL:1

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

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. WL:1

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

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

542/EECS 542. Vision Processing. CS 442. (3). (Excl).

Details of image formation theory, including the consideration of dynamic image sequences. The theoretical frameworks for edge detection, feature extraction, and surface description are presented. The relationship between image formation and object features is examined in detail. Programming required. WL:1

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

Survey of recent research on learning in artificial intelligence 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. WL:1

546/EECS 546. Cognitive Theory and Artificial Intelligence. CS 492. (3). (Excl).

Survey of scientific theory and results from cognitive psychology that are relevant to research in Artificial Intelligence. Topics include perceptual information processing, attention, short and long term memory systems, memory organization and the representation of knowledge, mechanisms of learning, natural language processing, problem solving, mental models and expertise. WL:1

547/EECS 547. Cognitive Architecture. CS 492. (3). (Excl).

Survey of architectures of symbolic systems in artificial intelligence. Architectures such as blackboards, production systems, logic systems, reflective systems, discovery systems and learning systems. Also integrated cognitive architectures such as ACT*, SOAR, MRS, and EURISKO. WL:1

568/EECS 568. Informational Aspects of Biology. Graduate standing or permission of instructor. (3). (Excl).

A survey of the role of information and control processes in biology. Tentative topics: Evolution and adaptation; cells and cellular self-reproduction; molecular information processing; discrete and dynamical models in biology; cellular control systems; development and morphogenesis; self-recognition and immunity; information processing in the nervous system and brain; physiological control systems; community and ecosystems. WL:1

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. Cost:3 WL:1

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

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

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. Cost:1 WL:1

577/EECS 577. Reliable Computing Systems. CS 280 and 478. (3). (Excl).

An introduction to models and methods used in the analysis and design of reliable hardware systems, software systems and computing systems. Aspects of reliability considered include fault tolerance, fault detection and diagnosis, reconfiguration, design verification and testing, and reliability evaluation. WL:1

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. Cost:1 WL:1

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, modeling and analysis, etc. WL:1

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. WL:1

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. Cost:5 WL:1

588/EECS 588/IOE 578/ME 551. Geometric Modeling. CS 487. (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 modeling facilities. Cost:2 WL:1

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 will work on several projects. Cost:1 WL:1

595/EECS 595/Ling. 541. Theory of Natural Language Structure. CS 492. (3). (Excl).

A survey of structural or syntactic theories of natural language, including phrase-structure and unification-based grammars, methods of parsing, and connections with semantics and pragmatics. Course work will include the use of existing natural language computer systems. WL:1

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. Cost:7 WL:1


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