Courses in Computer Science (Division 353)

181. Introduction to Computer Systems. No credit granted to those who have completed CS 280 or 283 or Engr. 103. (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.

280(270). Computer Science I. Math. 115 or equivalent. Credit is granted for only one course from among CS 280 and 283. (4). (NS).

Elements of a high-level programming language. Techniques of algorithm development and effective programming, with emphasis on top-down analysis, structured programming, analysis of algorithms, debugging and program verification. Study of algorithms for symbol manipulation and for numerical computation.

283(274). Elementary Programming Concepts. Math. 105 or the equivalent. Credit is granted for only one course from among CS 280 and 283. (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.

380(370). Computer Science II. CS 280. (4). (NS).

Study of abstract data types and implementations: lists, stacks, queues, arrays, strings, sets, trees, graphs, and files. Related topics include searching, sorting, and dynamic memory management. A high-level language is used for programming.

381(271). Assembly Language Programming. CS 280 or CS 283. (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 discussions per week.

383(374). Programming and Computer Systems. CS 283 or the equivalent. (4). (NS).

Advanced topics in Pascal, including the implementation of linked lists, trees, and hashing. Searching and sorting techniques. Assembly language and computer architecture. Selected topics in programming language theory. Students will write several programs in Pascal and assembly language.

476(400). Foundations of Computer Science. CS 303 or Math. 312 or permission of instructor. (3). (NS).

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

480(476). Data Structures. CS 380 or 383 and 476 or the equivalent. (4). (NS).

Data structuring principles of use in a wide variety of problem solving areas are covered. Alternatives are considered with respect to utilization of storage and time.

481(478). Software Engineering. CS 380 or 480, and senior standing. (4). (NS).

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 in usually required.

482(473). Operating Systems. CS 380 and 381, or equivalent. (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. Compiler Construction. CS 380 or 480. (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. Intended for undergraduates.

492. Artificial Intelligence for Undergraduates. CS 480 or permission of instructor. (3). (NS).

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

582(573). Advanced Operating Systems. CS 380, 381, 480 and 482; and in CS Honors program or graduate standing. (4). (NS).

Review of operating systems and their functions followed by discussion of hierarchical memory systems, virtual machine systems, object oriented systems, multiprocessing and multicomputers, scheduling and synchronization, networks and network systems, simulation and performance analysis.

592(565). Artificial Intelligence. EECS 492, graduate standing or CS Honors undergraduate. (4). (NS).

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.

595(541). Theory of Natural Language Structure. Permission of instructor. (3). (NS).

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. Coursework will include the use of existing natural language computer systems.

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