Courses

CS 110X. INTRODUCTION TO PROGRAMMING FOR NON-MAJORS

This course introduces students to the fundamental principles of programming in imperative and scripting languages. Topics include control structures, iterators, functional decomposition, basic data structures (such as records). Students will be expected to implement, test and debug programs. Through the use of compelling applications and lab exercises, students will learn how to interface with external data systems and control devices. Recommended background: none.

CS 220X. APPLICATION BUILDING WITH OBJECT-ORIENTED CONCEPTS

This course introduces students to an object-oriented model of programming, with an emphasis on the programming approaches useful in creating software applications. Students will be expected to design, implement, and debug object-oriented programs. Topics include inheritance, user interfaces, and database access. This course is for non-CS majors with prior programming experience and an interest in building software applications. Recommended background: CS 110x or CS 1101/1102. Students may not receive undergraduate credit for CS 220x after receiving credit for either CS 2102 or CS 2118.

CS 403X. MOBILE AND UBIQUITOUS COMPUTING

The goal of this course is to expose participants to fundamental concepts and state-of-the-art computer science literature in mobile and ubiquitous computing. Topics to be covered include mobile systems issues, human activity and emotion sensing, location sensing, mobile HCI, mobile social networking, mobile health, power saving techniques, energy and mobile performance measurement studies and mobile security. The course will introduce the programming of mobile devices such as smartphones running the Android operating system. Weekly projects, presentations and a term project will be assigned. Recommended background: The course will assume knowledge of the following material: ? Object-oriented concepts including classes, inheritance, exceptions, interfaces, polymorphism, proficiency in the Java programming language or a course equivalent to CS 2102 (object-oriented design concepts) ? Processes, threads, process management, synchronization, input/output devices, interrupts, memory management, file systems or a course equivalent to CS 3013 (operating systems) ? OSI reference seven-layer stack, wireless networking, Internetworking, network protocols, socket programming or a course equivalent to CS 3516 (computer networks)

CS 1004. INTRODUCTION TO PROGRAMMING FOR NON-MAJORS

This course introduces students to the fundamental principles of programming in imperative and scripting languages. Topics include control structures, iterators, functional decomposition, basic data structures (such as records). Students will be expected to implement, test and debug programs. Through the use of compelling applications and lab exercises, students will learn how to interface with external data systems and control devices. Recommended background: none. All Computer Science students and other students wishing to prepare for 3000-level courses in Computer Science should take CS 1101/1102 instead of CS 1004. This course provides sufficient background for CS 2301 Systems Programming for Non-Majors.

CS 1101. INTRODUCTION TO PROGRAM DESIGN

Cat. I This course introduces principles of computation and programming with an emphasis on program design. Topics include design and implementation of programs that use a variety of data structures (such as records, lists, and trees), functions, conditionals, and recursion. Students will be expected to design, implement, and debug programs in a functional programming language. Recommended background: none. Either CS 1101 or CS 1102 provide sufficient background for further courses in the CS department. Undergraduate credit may not be earned for both this course and CS 1102. Undergraduate credit may not be earned both for this course and for CS 2135.

CS 1102. ACCELERATED INTRODUCTION TO PROGRAM DESIGN

Cat. I This course provides an accelerated introduction to design and implementation of functional programs. The course presents the material from CS 1101 at a fast pace (so students can migrate their programming experience to functional languages), then covers several advanced topics in functional programming (potential topics include macros, lazy programming with streams, and programming with higher-order functions). Students will be expected to design, implement, and debug programs in a functional programming language. Recommended background: prior programming background covering lists, trees, functions, and recursion. Undergraduate credit may not be earned for both this course and CS 1101. Undergraduate credit may not be earned both for this course and for CS 2135.

CS 2011. INTRODUCTION TO MACHINE ORGANIZATION AND ASSEMBLY LANGUAGE

Cat. I This course introduces students to the structure and behavior of modern digital computers and the way they execute programs. Machine organization topics include the Von Neumann model of execution, functional organization of computer hardware, the memory hierarchy, caching performance, and pipelining. Assembly language topics include representations of numbers in computers, basic instruction sets, addressing modes, stacks and procedures, low-level I/O, and the functions of compilers, assemblers, linkers, and loaders. The course also presents how code and data structures of higher-level languages are mapped into the assembly language and machine representations of a modern processor. Programming projects will be carried out in the C language and the assembly language of a modern processor. Recommended background: CS 2301 or CS 2303, or a significant knowledge of C/C++.

CS 2022. DISCRETE MATHEMATICS

Cat. I This course serves as an introduction to some of the more important concepts, techniques, and structures of discrete mathematics, providing a bridge between computer science and mathematics. Topics include functions and relations, sets, countability, groups, graphs, propositional and predicate calculus, and permutations and combinations. Students will be expected to develop simple proofs for problems drawn primarily from computer science and applied mathematics. Undergraduate credit may not be earned both for this course and for CS 501. Recommended background: none.

CS 2102. OBJECT-ORIENTED DESIGN CONCEPTS

Cat. I This course introduces students to an object-oriented model of programming. Building from the design methodology covered in CS 1101/CS 1102, this course shows how programs can be decomposed into classes and objects. By emphasizing design, this course shows how to implement small defect-free programs and evaluate design decisions to select an optimal design under specific assumptions. Topics include inheritance, exceptions, interface, design by contract, basic design patterns, and reuse. Students will be expected to design, implement, and debug object-oriented programs composed of multiple classes and over a variety of data structures. Recommended background: CS 1101 or CS 1102. Undergraduate credit may not be earned both for this course and for CS 2136.

CS 2118. OBJECT-ORIENTED DESIGN CONCEPTS FOR BUSINESS APPLICATIONS

Cat. I This course introduces students to an object-oriented model of programming, with an emphasis on the programming approaches useful in creating business applications. Building from the design methodology covered in CS 1101/ CS 1102, this course shows how programs can be decomposed into classes and objects. Students will be expected to design, implement, and debug objectoriented programs in Visual Basic. Topics include inheritance, building user interfaces, and database access. This course is primarily for non-CS majors with prior program design experience and an interest in building business applications. Recommended background: CS 1101 or CS 1102. Students may receive credit for only one of the following: MG 2720, MIS 2720, CS 2136, or CS 2118.

CS 2223. ALGORITHMS

Cat. I Building on a fundamental knowledge of data structures, data abstraction techniques, and mathematical tools, a number of examples of algorithm design and analysis, worst case and average case, will be developed. Topics include greedy algorithms, divide-and-conquer, dynamic programming, heuristics, and probabilistic algorithms. Problems will be drawn from areas such as sorting, graph theory, and string processing. The influence of the computational model on algorithm design will be discussed. Students will be expected to perform analysis on a variety of algorithms. Undergraduate credit may not be earned both for this course and for CS 507. Recommended background: CS 2102 and CS 2022.

CS 2301. SYSTEMS PROGRAMMING FOR NON-MAJORS

This course introduces the C programming language and system programming concepts to non-CS majors who need to program computers in their own fields. The course assumes that students have had previous programming experience. It quickly introduces the major concepts of the C language and covers manual memory management, pointers and basic data structures, the machine stack, and input/output mechanisms. Students will be expected to design, implement, and debug programs in C. Recommended background: CS 1004 or CS 1101/1102 or previous experience programming a computer. All Computer Science students and other students wishing to prepare for upper-level courses in Computer Science should take CS 2303 instead of CS 2301. Students who have credit for CS 2303 may not receive subsequent credit for CS 2301.

CS 2303. SYSTEMS PROGRAMMING CONCEPTS

Cat. I This course introduces students to a model of programming where the programming language exposes details of how the hardware stores and executes software. Building from the design concepts covered in CS 2102, this course covers manual memory management, pointers, the machine stack, and input/ output mechanisms. The course will involve large-scale programming exercises and will be designed to help students confront issues of safe programming with system-level constructs. The course will cover several tools that assist programmers in these tasks. Students will be expected to design, implement, and debug programs in C++ and C. The course presents the material from CS 2301 at a fast pace and also includes C++ and other advanced topics. Recommended background: CS 2102 and/or substantial object-oriented programming experience.

CS 3013. OPERATING SYSTEMS

Cat. I This course provides the student with an understanding of the basic components of a general-purpose operating system. Topics include processes, process management, synchronization, input/output devices and their programming, interrupts, memory management, resource allocation, and an introduction to file systems. Students will be expected to design and implement a large piece of system software in the C programming language. Undergraduate credit may not be earned both for this course and for CS 502. Recommended background: CS 2303 or CS 2301, and CS 2011.

CS 3041. HUMAN-COMPUTER INTERACTION

Cat. I This course develops in the student an understanding of the nature and importance of problems concerning the efficiency and effectiveness of human interaction with computer-based systems. Topics include the design and evaluation of interactive computer systems, basic psychological considerations of interaction, interactive language design, interactive hardware design, and special input/output techniques. Students will be expected to complete several projects. A project might be a software evaluation, interface development, or an experiment. Recommended background: CS 2102 or CS 2118.

CS 3043. SOCIAL IMPLICATIONS OF INFORMATION PROCESSING

Cat. I This course makes the student aware of the social, moral, ethical, and philosophical impact of computers and computer-based systems on society, both now and in the future. Topics include major computer-based applications and their impact, humanmachine relationships, and the major problems of controlling the use of computers. Students will be expected to contribute to classroom discussions and to complete a number of significant writing assignments. This course is recommended for juniors and seniors. Undergraduate credit may not be earned both for this course and for CS 505. Recommended background: a general knowledge of computers and computer systems.

CS 3133. FOUNDATIONS OF COMPUTER SCIENCE

Cat. I This course introduces the theoretical foundations of computer science. These form the basis for a more complete understanding of the proficiency in computer science. Topics include computational models, formal languages, and an introduction to compatibility and complexity theory, including NP-completeness. Students will be expected to complete a variety of exercises and proofs. Undergraduate credit may not be earned both for this course and for CS 503. Recommended Background: CS 2022 and CS 2223. Students who have credit for CS 4121 cannot receive credit for CS 3133.

CS 3431. DATABASE SYSTEMS I

Cat. I This course introduces the student to the design, use, and application of database management systems. Topics include the relational data model, relational query languages, design theory, and conceptual data design and modeling for relational database design. Techniques that provide for data independence, and minimal redundancy will be discussed. Students will be expected to design and implement database system applications. Undergraduate credit may not be earned both for this course and for CS 4431 or CS 542. Recommended background: CS 2022 and either CS 2102 or CS 2118.

CS 3516. COMPUTER NETWORKS

Cat. I This course provides a broad view of computer networks. The course exposes students to all seven layers of OSI Reference Model while providing an introduction into newer topics such as wireless networking and Internet traffic concerns. The objective is to focus on an understanding of fundamental concepts of modern computer network architecture from a design and performance perspective. Topics covered include: physical layer considerations, network protocols, wide area networks, local area networks, wireless networks, switches and routing, congestion, Internet traffic and network security. Students will be expected to do extensive systems/network programming and will be expected to make use of simulation and measurement tools to gain an appreciation of current network design and performance issues. This course is also highly recommended for RBE and IMGD majors. Recommended background: CS 2301 or CS 2303, or a significant knowledge of C/C++.

CS 3733. SOFTWARE ENGINEERING

Cat. I This course introduces the fundamental principles of software engineering. Modern software development techniques and life cycles are emphasized. Topics include requirements analysis and specification, analysis and design, architecture, implementation, testing and quality, configuration management, and project management. Students will be expected to complete a project that employs techniques from the topics studied. This course should be taken before any course requiring a large programming project. Undergraduate credit may not be earned both for this course and for CS 509. Recommended background: CS 2102.

CS 4032. NUMERICAL METHODS FOR LINEAR AND NONLINEAR SYSTEMS

Cat. I This course provides an introduction to modern computational methods for linear and nonlinear equations and systems and their applications. Topics covered include: solution of nonlinear scalar equations, direct and iterative algorithms for the solution of systems of linear equations, solution of nonlinear systems, the eigenvalue problem for matrices. Error analysis will be emphasized throughout. Recommended background: MA 2071. An ability to write computer programs in a scientific language is assumed.

CS 4033. NUMERICAL METHODS FOR CALCULUS AND DIFFERENTIAL EQUATIONS

Cat. I This course provides an introduction to modern computational methods for differential and integral calculus and differental equations. Topics covered include: interpolation and polynomial approximation, approximation theory, numerical differentiation and integration, numerical solutions of ordinary differential equations. Error analysis will be emphasized throughout. Recommended background: MA 2051. An ability to write computer programs in a scientific language is assumed. Undergraduate credit may not be earned for both this course and for MA 3255/CS 4031.

CS 4100. ARTIFICIAL INTELLIGENCE FOR INTERACTIVE MEDIA AND GAMES

Algorithms and programming techniques from artificial intelligence (AI) are key contributors to the experience of modern computer games and interactive media, either by directly controlling a non-player character (NPC) or through more subtle manipulation of the environment. This course will focus on the practical AI programming techniques currently used in computer games for NPC navigation and decision-making, along with the design issues that arise when AI is applied in computer games, such as believability and real-time performance. The course will also briefly discuss future directions in applying AI to games and media. Students will be expected to complete significant software development projects using the studied techniques. Recommended background: object-oriented design concepts (CS 2102), algorithms (CS 2223), and knowledge of technical game development (IMGD 3000).

CS 4120. ANALYSIS OF ALGORITHMS

This course develops the skill of analyzing the behavior of algorithms. Topics include the analysis, with respect to average and worst case behavior and correctness, of algorithms for internal sorting, pattern matching on strings, graph algorithms, and methods such as recursion elimination, dynamic programming, and program profiling. Students will be expected to write and analyze programs. Undergraduate credit may not be earned both for this course and for CS 504. Recommended background: CS 2223 and some knowledge of probability.

CS 4123. THEORY OF COMPUTATION

Building on the theoretical foundations from CS 3133, this course addresses the fundamental question of what it means to be ?computable,? including different characterization of computable sets and functions. Topics include the halting program, the Church-Turing thesis, primitive recursive functions, recursive sets, recursively enumerable sets, NP-completeness, and reducibilities. Students will be expected to complete a variety of exercises and proofs. Recommended Background: CS 3133.

CS 4233. OBJECT-ORIENTED ANALYSIS AND DESIGN

This Software Engineering course will focus on the process of Object-Oriented Analysis and Design. Students will be expected to complete a large number of exercises in Domain Modeling, Use Case Analysis, and Object-Oriented Design. In addition, the course will investigate Design Patterns, which are elements of reusable object-oriented software designs. This course will survey a set of design patterns and consider how these patterns are described and used to solve design problems. Recommended Background: CS 2303 and CS 3733.

CS 4241. WEBWARE: COMPUTATIONAL TECHNOLOGY FOR NETWORK INFORMATION SYSTEMS

Cat. I This course explores the computational aspects of network information systems as embodied by the World Wide Web (WWW). Topics include: languages for document design, programming languages for executable content, scripting languages, design of WWW based human/computer interfaces, client/server network architecture models, high level network protocols (e.g., http), WWW network resource discovery and network security issues. Students in this course will be expected to complete a substantial software project (e.g., Java based user interface, HTML/CGI based information system, WWW search mechanisms). Recommended background: CS 2102 and CS 3013.

CS 4341. INTRODUCTION TO ARTIFICIAL INTELLIGENCE

Cat. I This course studies the problem of making computers act in ways which we call ?intelligent?. Topics include major theories, tools and applications of artificial intelligence, aspects of knowledge representation, searching and planning, and natural language understanding. Students will be expected to complete projects which express problems that require search in state spaces, and to propose appropriate methods for solving the problems. Undergraduate credit may not be earned both for this course and for CS 534. Recommended background: CS 2102, CS 2223, and CS 3133.

CS 4401. SOFTWARE SECURITY ENGINEERING

Cat. I This course provides an introduction to the pitfalls and practices of building secure software applications. Topics will include threat modeling, secure software development, defensive programming, web security and the interaction between security and usability. The course focuses on the application level with minor attention to operating-system level security; network-level security is not covered. Assignments involve designing and implementing secure software, evaluating designs and systems for security-related flaws, and presentations on security issues or tools. All students will be required to sign a pledge of responsible conduct at the start of the course. Recommended Background: CS3013 and CS3733. The course assumes nontrivial experience with C and Unix, familiarity with operating systems, filesystems, and databases, and experience with technologies for building web applications (from CS4241 or personal experience).

CS 4404. TOOLS & TECHN - COMPTR NTW SEC

This course introduces students to modern network security concepts, tools, and techniques. The course covers security threats, attacks and mitigations at the operating?system and network levels (as opposed to the software level). Topics include: authentication, authorization, confidentiality, integrity, anonymity, privacy, intrusion detection and response, and cryptographic applications. Students will become familiar with modern security protocols and tools. Assignments will involve using securitytesting software to uncover vulnerabilities, network packet analyzers, and existing security applications to create secure network implementations. The course requires enough programming and systems background to understand attacks and use systems tools, but does not involve significant programming projects. Assignments and projects will use a Linux base for implementation. Students who have credit for CS 558 may not earn subsequent credit for this course. Recommended Background: Knowledge of operating systems (CS3013 or equivalent) and computer networks (CS3516 or equivalent). Familiarity with Linux or Unix is essential.

CS 4432. DATABASE SYSTEMS II

This course concentrates on the study of the internals of database management systems. Topics include: principles and theories of physical storage management, advanced query languages, query processing and optimization, index structures for relational databases, transaction processing, concurrency control, distributed databases, and database recovery, security, client server and transaction processing systems. Students may be expected to design and implement software components that make up modern database systems. Undergraduate credit may not be earned both for this course and CS 542. Recommended background: CS 3431 and CS 3733.

CS 4445. DATA MINING AND KNOWLEDGE DISCOVERY IN DATABASES

This course provides an introduction to Knowledge Discovery in Databases (KDD) and Data Mining. KDD deals with data integration techniques and with the discovery, interpretation and visualization of patterns in large collections of data. Topics covered in this course include data warehousing and mediation techniques; data mining methods such as rule-based learning, decision trees, association rules and sequence mining; and data visualization. The work discussed originates in the fields of artificial intelligence, machine learning, statistical data analysis, data visualization, databases, and information retrieval. Several scientific and industrial applications of KDD will be studied. Recommended background: MA 2611, CS 2223, and CS 3431, or CS 3733.

CS 4513. DISTRIBUTED COMPUTING SYSTEMS

This course extends the study of the design and implementation of operating systems begun in CS 3013 to distributed and advanced computer systems. Topics include principles and theories of resource allocation, file systems, protection schemes, and performance evaluation as they relate to distributed and advanced computer systems. Students may be expected to design and implement programs that emphasize the concepts of file systems and distributed computing systems using current tools and languages. Undergraduate credit may not be earned both for this course and for CS 502. Recommended background: CS 3013, CS 3516, and system programming experience.

CS 4515. COMPUTER ARCHITECTURE

This course explores the architectural design of modern computer systems in terms of instruction sets and the organization of processors, controllers, memories, devices, and communication links. Topics include an overview of computer architectures and system components, theoretical foundations, instruction-level and thread-level pipelining, multifunction pipelines, multi-core systems, caching and memory hierarchies, and multi-core and parallel computer organization. Students may be expected to design and implement programs that simulate significant components of modern computer architectures. Recommended background: CS 2011 or ECE 2801, and CS 3013.

CS 4516. ADVANCED COMPUTER NETWORKS

This course provides an in-depth look into computer networks. While repeating some of the areas from CS 3516, the goal is to go deeper into computer networks topics. This in-depth treatment in topics such as routing, congestion control, wireless layer protocols and physical signaling considerations will require the use of basic queuing theory and probability to provide a more formal treatment of computer networks performance. Other topics covered include: LAN and WLAN technologies, mobile wireless networks, sensor networks, optical networks, network security, intrusion detection and network management. Students will be expected to do more sophisticated network programming than seen in CS 3516 and will conduct laboratory activities involving measuring the performance of modern networking applications running on both wired networks and infrastructure wireless networks. Undergraduate credit may not be earned both for this course and for CS 513. Recommended background: CS 3013, CS 3516, and knowledge of probability. The course assumes a familiarity with operating systems including Unix or Linux, and significant experience with C/C++.

CS 4533. TECHNIQUES OF PROGRAMMING LANGUAGE TRANSLATION

This course studies the compiling process for high-level languages. Topics include lexical analysis, syntax analysis, semantic analysis, symbol tables, intermediate languages, optimization, code generation and run-time systems. Students will be expected to use compiler tools to implement the front end, and to write a program to implement the back end, of a compiler for a recursive programming language. Undergraduate credit may not be earned for both this course and for CS 544. Recommended Background: CS 2102 and CS 3133.

CS 4536. PROGRAMMING LANGUAGES

This course covers the design and implementation of programming languages. Topics include data structures for representing programming languages, implementing control structures (such as functions, recursion, and exceptions), garbage collection, and type systems. Students will be expected to implement several small languages using a functional programming language. Recommended background: CS 2303, CS 3133, and experience programming in a functional language (as provided by CS 1101 or CS 1102). Undergraduate credit may not be earned for both this course and CS 536.

CS 4731. COMPUTER GRAPHICS

Cat. I This course studies the use of the computer to model and graphically render two- and three-dimensional structures. Topics include graphics devices and languages, 2- and 3-D object representations, and various aspects of rendering realistic images. Students will be expected to implement programs which span all stages of the 3-D graphics pipeline, including clipping, projection, arbitrary viewing, hidden surface removal and shading. Undergraduate credit may not be earned both for this course and for CS 543. Recommended background: CS 2223, CS 2303 and MA 2071.

CS 4732. COMPUTER ANIMATION

This course provides an in-depth examination of the algorithms, data structures, and techniques used in modeling and rendering dynamic scenes. Topics include animation hardware and software, parametric blending techniques, modeling physical and articulated objects, forward and inverse kinematics, key-frame, procedural, and behavioral animation, and free-form deformation. Students will be expected to develop programs to implement low-level animation algorithms as well as use commercial animation tools to design and produce small to moderate sized animations. Recommended background: CS 4731.

CS 4802. BIOVISUALIZATION

This course will use interactive visualization to model and analyze biological information, structures, and processes. Topics will include the fundamental principles, concepts, and techniques of visualization (both scientific and information visualization) and how visualization can be used to study bioinformatics data at the genomic, cellular, molecular, organism, and population levels. Students will be expected to write small to moderate programs to experiment with different visual mappings and data types. Recommended background: CS 2102, CS 2223, and one or more biology courses.

CS 4803. BIOLOGICAL AND BIOMEDICAL DATABASE MINING

This course will investigate computational techniques for discovering patterns in and across complex biological and biomedical sources including genomic and proteomic databases, clinical databases, digital libraries of scientific articles, and ontologies. Techniques covered will be drawn from several areas including sequence mining, statistical natural language processing and text mining, and data mining. Recommended Background: CS 2102, CS 2223, MA 2610 or MA 2611, and one or more biology courses.

 
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