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CMSC Computer Science( Computer, Mathematical and Physical Sciences)CMSC102 Introduction to Information Technology; (3 credits) Grade Method: REG/P-F/AUD.For non-majors only. Also offered as UNIV 133. Not open to students who have completed CMSC 106, CMSC 114 or CMSC 214. Credit will be granted for only one of the following: CMSC 102, UNIV 133 or CMSC 214. If CMSC 102 is taken before CMSC 214, then credit will be granted for both. Computer terminology and concepts. Introduction to database management systems, spreadsheets, and work processors. Introduction to networks and to the Internet in particular. Importing information from network to local application. CMSC114 (PermReq) Computer Science I; (4 credits) Grade Method: REG/P-F/AUD. Prerequisite: CMSC 106 with a grade of C or better; and permission of department based on satisfactory performance on the department's placement exams. Corequisite: MATH 141. Not open to students who have completed CMSC 214 or higher. Credit will be granted for only one of the following: CMSC 114 or CMSC 113. With CMSC 214, this course forms a one-year sequence for computer science majors. Introduction to UNIX. Procedural and data abstraction using C++. CMPS and Computer Engineering students will be given priority for registration until the first day of classes. CMSC131 (PermReq) Object-Oriented Programming I; (4 credits) Grade Method: REG/P-F/AUD. Corequisite: MATH 140 and permission of department. For CMSC majors only. Not open to students who have completed CMSC 114. Introduction to programming and computer science. Emphasizes understanding and implementation of applications using object-oriented techniques. Develops skills such as program design and testing as well as implementation of programs using a graphical IDE. Programming done in Java. CMSC214 (PermReq) Computer Science II; (4 credits) Grade Method: REG/P-F/AUD. Prerequisites: CMSC 114 with a grade of C or better; or a score of 4 or 5 on either the A or the AB C++ AP exam; or permission of department based on satisfactory performance on the department placement exam. Corequisite: CMSC 250. Credit will be granted for only one of the following: CMSC 214 or CMSC 113. Elementary data structures, recursion, and object-oriented programming using C++. CMSC250 (PermReq) Discrete Structures; (4 credits) Grade Method: REG/P-F/AUD. Prerequisite: MATH 141 and permission of department. Formerly CMSC 150. Fundamental mathematical concepts related to computer science, including finite and infinite sets, relations, functions, and propositional logic. Introduction to other techniques, modeling and solving problems in computer science. Introduction to permutations, combinations, graphs, and trees with selected applications. CMSC298A (PermReq) Special Topics in Computer Science; (1-4 credits) Grade Method: S-F. Individual Instruction course: contact department or instructor to obtain section number. CMSC311 (PermReq) Computer Organization; (3 credits) Grade Method: REG. Prerequisite: CMSC 214 with a grade of C or better and CMSC 250 with a grade of C or better and permission of department. Introduction to assembly language. Design of digital logic circuits. Organization of central processors, including instruction sets, register transfer operations, control microprogramming, data representation, and arithmetic algorithms. Memory and input/output organization. CMSC330 (PermReq) Organization of Programming Languages; (3 credits) Grade Method: REG. Prerequisite: CMSC 214 with a grade of C or better and CMSC 250 with a grade of C or better and permission of department. The semantics of programming languages and their run-time organization. Several different models of languages are discussed, including procedural (e.g., C, Pascal), functional (e.g., ML, LISP), rule-based (e.g., Prolog), and object-oriented (e.g., C++, Smalltalk). Run-time structures, including dynamic versus static scope rules, storage for strings, arrays, records, and object inheritance are explored. CMSC351 (PermReq) Algorithms; (3 credits) Grade Method: REG. Prerequisites: CMSC 214 with a grade of C or better and CMSC 250 with a grade of C or better and permission of department. CMSC 351 may not count as one of the required upper level CMSC courses for students who are required to have 24 upper level CMSC credits for graduation, i.e. for students who became computer science majors prior to Fall, 2002. Credit will be granted for only one of the following: CMSC 251 or CMSC 351. Formerly CMSC 251. A systematic study of the complexity of some elementary algorithms related to sorting, graphs and trees, and combinatorics. Algorithms are analyzed using mathematical techniques to solve recurrences and summations. CMSC390 (PermReq) Honors Paper; (3 credits) Grade Method: REG. Individual Instruction course: contact department or instructor to obtain section number. Prerequisite: admission to CMSC Honors Program. Special study or research directed toward preparation of honors paper. CMSC411 Computer Systems Architecture; (3 credits) Grade Method: REG. Prerequisites: a grade of C or better in CMSC 311 and CMSC 330; and permission of department; or CMSC graduate student. Input/output processors and techniques. Intra-system communication, buses, caches. Addressing and memory hierarchies. Microprogramming, parallelism, and pipelining. CMSC412 Operating Systems; (4 credits) Grade Method: REG. CORE Capstone (CS) Course. Prerequisites: A grade of C or better in (CMSC 311 or ENEE 350) and a grade of C or better in CMSC 330; and permission of department; or CMSC graduate student. An introduction to batch systems, spooling systems, and third-generation multiprogramming systems. Description of the parts of an operating system in terms of function, structure, and implementation. Basic resource allocation policies. CMSC417 Computer Networks; (3 credits) Grade Method: REG. Prerequisites: A grade of C or better in CMSC 251, a grade of C or better in CMSC 311, and a grade of C or better in CMSC 330 and permission of department; or CMSC graduate student. Computer networks and architectures. The OSI model including discussion and examples of various network layers. A general introduction to existing network protocols. Communication protocol specification, analysis, and testing. CMSC420 Data Structures; (3 credits) Grade Method: REG. Prerequisites: A grade of C or better in CMSC 330 and in CMSC 351; and permission of department; or CMSC graduate student. Description, properties, and storage allocation of data structures including lists and trees. Algorithms for manipulating structures. Applications from areas such as data processing, information retrieval, symbol manipulation, and operating systems. CMSC421 Introduction to Artificial Intelligence; (3 credits) Grade Method: REG. Prerequisites: (a grade of C or better in CMSC 251 and a grade of C or better in CMSC 330) or a grade of C or better in CMSC 420; and permission of department; or CMSC graduate student. Areas and issues in artificial intelligence, including search, inference, knowledge representation, learning, vision, natural languages, expert systems, robotics. Implementation and application of programming languages (e.g. LISP, PROLOG, SMALLTALK), programming techniques (e.g. pattern matching, discrimination networks) and control structures (e.g. agendas, data dependencies). CMSC424 Database Design; (3 credits) Grade Method: REG. CORE Capstone (CS) Course. Prerequisite: CMSC 420 with a grade of C or better; and permission of department; or CMSC graduate student. Motivation for the database approach as a mechanism for modeling the real world. Review of the three popular data models: relational, network, and hierarchical. Comparison of permissible structures, integrity constraints, storage strategies, and query facilities. Theory of database design logic. CMSC426 Image Processing; (3 credits) Grade Method: REG. Prerequisite: CMSC 420 and permission of department; or CMSC graduate student. An introduction to basic techniques of analysis and manipulation of pictorial data by computer. Image input/output devices, image processing software, enhancement, segmentation, property measurement, Fourier analysis. Computer encoding, processing, and analysis of curves. CMSC427 Computer Graphics; (3 credits) Grade Method: REG. Prerequisites: MATH 240; and a grade of C or better in CMSC 420; and permission of department; or CMSC graduate student. An introduction to the principles of computer graphics. Includes an introduction to graphics displays and systems. Introduction to the mathematics of affine and projective transformations, perspective, curve and surface modeling, algorithms for hidden-surface removal, color models, methods for modeling illumination, shading, and reflection. CMSC430 Theory of Language Translation; (3 credits) Grade Method: REG. Prerequisites: a grade of C or better in CMSC 330; and permission of department; or CMSC graduate student. Formal translation of programming languages, program syntax and semantics. Finite state recognizers and regular grammers. Context-free parsing techniques such as recursive descent, precedence, LL(k) and LR(k). Code generation, improvement, syntax-directed translation schema. CMSC433 Programming Language Technologies and Paradigms; (3 credits) Grade Method: REG. Prerequisite: CMSC 330; and permission of department; or CMSC graduate student. Programming language technologies (e.g., object-oriented programming), their implementations and use in software design and implementation. CMSC434 Introduction to Human-Computer Interaction; (3 credits) Grade Method: REG. Prerequisites: CMSC 330 with a grade of C or better and PSYC 100; or permission of department; or CMSC graduate student. Assess usability by quantitative and qualitative methods. Conduct task analyses, usability tests, expert reviews, and continuing assessments of working products by interviews, surveys, and logging. Apply design processes and guidelines to develop professional quality user interfaces. Build low-fidelity paper mockups, and a high-fidelity prototype using contemporary tools such as graphic editors and a graphical programming environment (eg: Visual Basic, Java). CMSC435 Software Engineering; (3 credits) Grade Method: REG. CORE Capstone (CS) Course. Prerequisites: (CMSC 412, CMSC 417, CMSC 420, CMSC 430, or CMSC 433) with a grade of C or better and permission of department; or CMSC graduate student. State-of-the-art techniques in software design and development. Laboratory experience in applying the techniques covered. Structured design, structured programming, top-down design and development, segmentation and modularization techniques, iterative enhancement, design and code inspection techniques, correctness, and chief-programmer teams. The development of a large software project. CMSC450 Logic for Computer Science; (3 credits) Grade Method: REG. Prerequisites: (CMSC 251 and MATH 141) with grade of C or better and permission of department; or CMSC graduate student. Also offered as MATH 450. Credit will be granted for only one of the following: MATH 445 or CMSC 450/MATH 450. Elementary development of propositional and first-order logic accessible to the advanced undergraduate computer science student, including the resolution method in propositional logic and Herbrand's Unsatisfiability Theorem in first-order logic. Included are the concepts of truth, interpretation, validity, provability, soundness, completeness, incompleteness, decidability and semi-decidability. CMSC451 Design and Analysis of Computer Algorithms; (3 credits) Grade Method: REG. Prerequisite: a grade of C or better in CMSC 351; and permission of department; or CMSC graduate student. Fundamental techniques for designing efficient computer algorithms, proving their correctness, and analyzing their complexity. General topics include sorting, selection, graph algorithms, and basic algorithm design paradigms (such as divide-and-conquer, dynamic programming and greedy algorithms), lower bounds and NP-completeness. CMSC456 Cryptology; (3 credits) Grade Method: REG. Prerequisites: Any two 400-level MATH courses; OR CMSC 330 and CMSC 251; and permission of department; or CMSC graduate student. Also offered as MATH 456. Credit will be granted for only one of the following: CMSC 456 or MATH 456. Importance in protecting data in communications between computers. The subject lies on the border between mathematics and computer science. Mathematical topics include number theory and probability, and computer science topics include complexity theory. CMSC460 Computational Methods; (3 credits) Grade Method: REG. Prerequisites: MATH 240; and MATH 241; and CMSC 106 or CMSC 114 or ENEE 114; and permission of department;or CMSC greaduate student. Also offered as AMSC 460. Credit will be granted for only one of the following: AMSC/CMSC/MAPL 460 or AMSC/CMSC/MAPL 466. Basic computational methods for interpolation, least squares, approximation, numerical quadrature, numerical solution of polynomial and transcendental equations, systems of linear equations and initial value problems for ordinary differential equations. Emphasis on methods and their computational properties rather than their analytic aspects. Intended primarily for students in the physical and engineering sciences. CMSC466 Introduction to Numerical Analysis I; (3 credits) Grade Method: REG. Prerequisites: MATH 240; and MATH 241; and CMSC 106 or CMSC 114 or ENEE 114; and permission of department;or CMSC graduate student. Also offered as AMSC 466. Credit will be granted for only one of the following: AMSC/CMSC/MAPL 460 or AMSC/CMSC/MAPL 466. Floating point computations, direct methods for linear systems, interpolation, solution of nonlinear equations. CMSC475 Combinatorics and Graph Theory; (3 credits) Grade Method: REG. Prerequisites: MATH 240 and MATH 241; and permission of department; or CMSC graduate student. Also offered as MATH 475. General enumeration methods, difference equations, generating functions. Elements of graph theory, matrix representations of graphs, applications of graph theory to transport networks, matching theory and graphical algorithms. CMSC498A (PermReq) Special Problems in Computer Science; (1-3 credits) Grade Method: REG. Individual Instruction course: contact department or instructor to obtain section number. CMSC498P Special Problems in Computer Science: Industrial Practices Apprenticeship; (1-3 credits) Grade Method: REG. CMSC498W Special Problems in Computer Science: Semantic Web; (3 credits) Grade Method: REG. CMSC598 (PermReq) Practical Training; (1 credit) Grade Method: S-F. Individual Instruction course: contact department or instructor to obtain section number. CMSC661 Scientific Computing II; (3 credits) Grade Method: REG. Prerequisite: AMSC/CMSC/MAPL 460, AMSC/CMSC/MAPL 466, or knowledge of basic numerical analysis (linear equations, nonlinear equations, integration, interpolation) with permission of instructor. Knowledge of C or Fortran. Also offered as AMSC 661. Credit will be granted for only one of the following: AMSC, CMSC 661 or MAPL 661. Fourier and wavelet transform methods, numerical methods for elliptic partial differential equations, numerical linear algebra for sparse matrices, Finite element methods, numerical methods for time dependent partial differential equations. Techniques for scientific computation with an introduction to the theory and software for each topic. Course is part of a two course sequence (660 and 661), but can be taken independently. CMSC664 Advanced Scientific Computing II; (3 credits) Grade Method: REG. Prerequisite: CMSC 663 and permission of instructor. Also offered as AMSC 664. Credit will be granted for only one of the following: AMSC 664, CMSC 664 or MAPL 664. In the sequence CMSC 663, CMSC 664 students work on a year-long individual project to develop software for a scientific task in a high performance computing environment. Lectures will be given on code development and validation, parallel algorithms for partial differential equations, nonlinear systems, optimization. CMSC666 Numerical Analysis I; (3 credits) Grade Method: REG/AUD. Prerequisites: AMSC/CMSC/MAPL 466; and MATH 410. Also offered as AMSC 666. Credit will be granted for only one of the following: AMSC 666, CMSC 666 or MAPL 666. Iterative methods for linear systems, piecewise interpolation, eigenvalue problems, numerical integration. CMSC667 Numerical Analysis II; (3 credits) Grade Method: REG/AUD. Prerequisite: AMSC/CMSC/MAPL 666. Also offered as AMSC 667. Credit will be granted for only one of the following: AMSC 667, CMSC 667 or MAPL 667. Nonlinear systems of equations, ordinary differential equations, boundary value problems. CMSC711 Computer Networks; (3 credits) Grade Method: REG/AUD. Prerequisite: CMSC 412 or equivalent. Priciples, design, and performance evaluation of computer networks. Network architectures including the ISO model and local area networks (LANs). Communication protocols and network topology. CMSC723 Natural Language Processing; (3 credits) Grade Method: REG/AUD. Prerequisite: CMSC 421 or equivalent or permission of instructor. Provides brief overview of field, relating natural language to computation and linguistics. Examines theories and formalisms in areas of syntax, semantics, and the lexicon. Examines key issues in designing computer systems for understanding, generating, and translating natural language. Studies field from engineering perspective (i.e., the development of specific practical systems that involve natural language) and from scientific perspective (i.e., the testing of syntactic, semantic, and lexical theories proposed by theoretical linguists. CMSC724 Database Management Systems; (3 credits) Grade Method: REG/AUD. Prerequisite: CMSC 624 or permission of instructor. Theoretical and implementation issues in advanced database systems. Topics include distributed databases, parallel databases, database client-server architectures, multimedia access methods, advanced query optimization techniques, data semantics and models, object-oriented databases, and deductive and expert database systems. CMSC726 Machine Learning; (3 credits) Grade Method: REG/AUD. Prerequisite: CMSC 421 or equivalent or permission of instructor. Reviews and analyzes both traditional symbol-processing methods and genetic algorithms as approaches to machine learning. (Neural network learning methods are primarily covered in CMSC 727.) Topics include induction of decision trees and rules, version spaces, candidate elimination algorithm, exemplar-based learning, genetic algorithms, evolution under artificial selection of problem-solving algorithms, system assessment, comparative studies, and related topics. CMSC733 Computer Processing of Pictorial Information; (3 credits) Grade Method: REG/AUD. Prerequisite: CMSC 420. Input, output, and storage of pictorial information. Pictures as information sources, efficient encoding, sampling, quantization, approximation. Position-invariant operations on pictures, digital and optical implementations, the pax language, applications to matched and spatial frequency filtering. Picture quality, image enhancement and image restoration. Picture properties and pictorial pattern recognition. Processing of complex pictures; figure extraction, properties of figures. Data structures for pictures description and manipulation; picture languages. Graphics systems for alphanumeric and other symbols, line drawings of two- and three-dimensional objects, cartoons and movies. CMSC740 Advanced Computer Graphics; (3 credits) Grade Method: REG/AUD. Prerequisites: (MATH 240 and CMSC 420) or permission of instructor. An introduction to the principles of computer graphics. Includes an introduction to graphics displays and systems, introduction to the mathematics of affine and projective transformations, perspective, curve and surface modeling, algorithms for hidden-surface removal, color models, methods for modeling illumination, shading, and reflection. CMSC751 Parallel Algorithms; (3 credits) Grade Method: REG/AUD. Prerequisite: CMSC 451 or equivalent. A presentation of the theory of parallel computers and parallel processing. Models of parallel processing and the relationships between these models. Techniques for the design and analysis of efficient parallel algorithms including parallel prefix, searching, sorting, graph problems, and algebraic problems. Theoretical limits of parallelism, inherently sequential problems, and the theory of P-completeness. CMSC798 (PermReq) Graduate Seminar in Computer Science; (1-3 credits) Grade Method: REG/AUD. Individual Instruction course: contact department or instructor to obtain section number. CMSC798A (PermReq) Graduate Seminar in Computer Science; (1-3 credits) Grade Method: REG/AUD. Individual Instruction course: contact department or instructor to obtain section number. CMSC majors only. Other majors require permission of department. CMSC799 (PermReq) Master's Thesis Research; (1-6 credits) Grade Method: REG/S-F. Individual Instruction course: contact department or instructor to obtain section number. CMSC818A (PermReq) Advanced Topics in Computer Systems; (1-3 credits) Grade Method: REG/AUD. Individual Instruction course: contact department or instructor to obtain section number. CMSC818S Advanced Topics in Computer Systems: Grid Computing; (3 credits) Grade Method: REG/AUD. CMSC828A (PermReq) Advanced Topics in Information Processing; (1-3 credits) Grade Method: REG/AUD. Individual Instruction course: contact department or instructor to obtain section number. CMSC828C Advanced Topics in Information Processing: Human Factors in Computer and Information Systems; (3 credits) Grade Method: REG. CMSC828O Advanced Topics in Information Processing; (3 credits) Grade Method: REG/AUD. CMSC828R Advanced Topics in Information Processing: Medical Image Processing and Understanding; (3 credits) Grade Method: REG/AUD. CMSC838A (PermReq) Advanced Topics in Programming Languages; (1-3 credits) Grade Method: REG/AUD. Individual Instruction course: contact department or instructor to obtain section number. CMSC838G Advanced Topics in Programming Languages: New Devices for New Interactions; (3 credits) Grade Method: REG/AUD. CMSC838I Advanced Topics in Programming Languages: HOW TO DO RESEARCH; (1 credit) Grade Method: REG/AUD. CMSC838P Advanced Topics in Programming Languages: Software Engineering: Remote Analysis and Measurement of Software Systems; (3 credits) Grade Method: REG/AUD. CMSC838T Advanced Topics in Programming Languages: Systems Software for High Performance Computing, Emphasis on Bioinformatic Applications; (3 credits) Grade Method: REG/AUD. CMSC838Z Advanced Topics in Programming Languages; (3 credits) Grade Method: REG/AUD. CMSC858A (PermReq) Advanced Topics in Theory of Computing; (1-3 credits) Grade Method: REG/AUD. Individual Instruction course: contact department or instructor to obtain section number. CMSC858G Advanced Topics in Theory of Computing: Complexity Theory; (3 credits) Grade Method: REG/AUD. CMSC858K Advanced Topics in Theory of Computing: Advanced Topics in Cryptography; (3 credits) Grade Method: REG/AUD. CMSC878A (PermReq) Advanced Topics in Numerical Methods; (1-3 credits) Grade Method: REG/AUD. Individual Instruction course: contact department or instructor to obtain section number. CMSC899 Doctoral Dissertation Research; (1-8 credits) Grade Method: REG/S-F. Individual Instruction course: contact department or instructor to obtain section number.
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