CIT 101/L. CIT Fundamentals (2/1)
Corequisite: CIT 101L. The course provides an introduction to the computer hardware and software skills needed to help meet the growing demand for information technology (IT) professionals. The lecture portion of the course introduces the fundamentals of computer hardware and software management, and introduces key IT concepts including security, networking, and professional responsibilities. The lab portion of the course provides hands-on practice in the management of computing systems and the troubleshooting of technical problems. Two hour lecture and three hour laboratory per week.
CIT 160/L. Internet Technologies (2/1)
Corequisite: CIT 160L. Architecture of the Internet; Internet protocols, including http, ftp, telnet; browser technologies; current developments in Internet technologies and usage characteristics; Hypertext; self descriptive text; webpage design; website design; ADA compliance; commercialization of the Internet; role of the Internet in CIT. Lab: 3 hours per week.
CIT 210/L. Deployment and Management of Operating Systems (3/1)
Prerequisites: CIT 101/L, COMP 122/L; Lower division writing requirement. Corequisite: CIT 210L. Introduction to the basic components of CIT systems, including networking, web systems, databases, scripting, system administration and maintenance, and system integration. A deeper study of operating system principles, network architecture and resource management, including shared resources.
CIT 270/L. Integrative Programming (3/1)
Prerequisites: CIT 160/L; COMP 182/L; MATH 103, MATH 150A or MATH 255A. Corequisite: CIT 270L. Role of integrative programming in information technology: operating systems, system management, application reuse. Tools and techniques for integrative programming, such as Perl, TCL/tk, VBscript and Python. Script programming development environments. Role of scripting in system installation and management. Client-server architecture. Interface management, wrappers, facades, brokers and proxies. XML and XML-related technologies, with emphasis on data exchange for application/system integration. Integration technologies, such as web services, Ruby on Rails, CORBA and DCOM. Integration platforms, such as .net and J2EE. Lab: 3 hours per week.
CIT 360/L. CIT System Management and Lab (2/1)
Prerequisites: CIT 210/L, CIT 270/L. Corequisites: CIT 360 and CIT 360L are corequisites of each other. Overview of enterprise system architecture, principles and practices of systems administration and system management including firewalls and proxy servers; networked file systems; user account management; resources allocation, installation and configuration of operating systems, startup and shutdown, booting, performance monitoring, storage backup and restore; system administration tools; system maintenance, user support issues, web administration; integration of network, storage, system resources to meet user needs and enterprise goals and objectives, roles and responsibilities of a system administrator. Lab portion of the course will provide hands-on implementation and troubleshooting exercises. Two hour lecture and three hour laboratory per week.
CIT 384/L. Web Development and Hosting and Lab (2/1)
Prerequisites: CIT 270/L, CIT 360/L. High-level understanding of TCP/IP protocol stack as it exists in practice, including example protocols. Packet capture and traffic analysis. System and software architectures for web applications, including hosting and horizontal scaling of web and database servers. Principles of website design at front-end, back-end and database tiers. Web service technology using AJAX and JSON. Security, privacy and reliability issues. Two hours of lecture and three hours of laboratory per week. Credit not allowed for both CIT 384/L and COMP 484/L.
CIT 425/L. Information and Systems Security and Lab (2/1)
Prerequisites: CIT 360/L and IS 435; Attempted Upper Division Writing Proficiency Exam. This course will provide a comprehensive introduction and study into a broad selection of contemporary information systems security issues, concepts and policies, including the survey of state-of-the art technology used to address security problems. Topics of study include the basic principles of information systems security, including cryptography, identifications and authentications, access control models and mechanisms, multilevel database security, Internet security, planning and administering security, risk analysis, social issues such as individual privacy, and the role of public policy. The students will gain an understanding of the threats to information resources and learn about counter measurements and their limitations. Two hours of lecture and three hours of laboratory per week. Credit not allowed for both CIT 425/L and COMP 424.
CIT 480/L. CIT System Design and Implementation I (2/1)
Prerequisites: IS 451; Upper Division Writing Proficiency Exam. Corequisites: CIT 480L. CIT senior project first semester includes project proposal, methods and processes, feasibility studies, teamwork, CASE tools, work breakdown structure, estimating and budgeting, schedule planning, peer reviews and inspections, and technical presentation. Professional communication. Teamwork concepts and issues. Organizational context. Professional and ethical issues, roles and responsibilities. Two hour lecture and three hour laboratory per week.
CIT 481/L. CIT System Design and Implementation II (2/1)
Prerequisites: CIT 480/L. Corequisite: CIT 481L. CIT senior project second semester includes system/software design, functional and non-functional testing, system and acceptance testing, schedule management and tracking, delivery and deployment planning, social contexts of computing, standards and certification issues such as ISO, CMMI, technical presentation, technical documentation, legal Issues in computing, intellectual property. Lab: 3 hours per week.
COMP 100. Computers: Their Impact and Use (3)
Not open to Computer Science majors. Introduction to the uses, concepts, techniques and terminology of computing. Places the possibilities and problems of computer use in historical, economic and social contexts. Shows how computers can assist in a wide range of personal, commercial and organizational activities. Typical computer applications, including word processing, spreadsheets and databases. (Available for General Education, E Lifelong Learning.) (IC)
COMP 102/L. Programming for Data Applications and Lab (2/1)
Prerequisite: Multiple Measures Placement in GE-level Mathematics, or credit in MATH 093 or MATH 196QR or MATH 196S or equivalent. Corequisite: COMP 102L. Programming, using the Python programming language, with a focus on data manipulation and processing in contexts outside of traditional computing. No prior programming experience is required. Lab: three hours per week. (Available for General Education, B4 Mathematics and Quantitative Reasoning or E Lifelong Learning.)
COMP 105BAS. Computer Programming in BASIC (1)
Prerequisite: COMP 101, COMP 110/L or COMP 106/L. Instruction and practice in computer programming in BASIC. 3 hours of lab per week.
COMP 108. Orientation to Computer Science (3)
Prerequisite: Multiple Measures Placement in GE-level Mathematics, or credit in MATH 093 or MATH 196QR or MATH 196S or equivalent. Not a required course in the major. Recommended for incoming Computer Science majors with limited computing experience as well as those considering a major in Computer Science. Introduction to the Computer Science major and profession. Main focus on developing problem solving, algorithm development and programming skills, and acquiring critical thinking abilities, especially when applied to computer science. Additional emphasis on orientation to the university, campus resources, study skills, motivation and career awareness.
COMP 110/L. Introduction to Algorithms and Programming and Lab (3/1)
Prerequisite: Grade of “C” or better in MATH 102, MATH 103, MATH 104, MATH 105, MATH 150A or MATH 255A, or a passing score on the Mathematics Placement Test (MPT) that satisfies prerequisites for MATH 150A or MATH 255A. Corequisite: COMP 110L. Introduction to algorithms, their representation, design, structuring, analysis and optimization. Implementation of algorithms as structured programs in a high level language. Lab: 3 hours per week. (Available for General Education, E Lifelong Learning if required by student’s major.)
COMP 122/L. Computer Architecture and Assembly Language (1/1)
Prerequisites: Grade of “C” or better in COMP 110/L; Grade of “C” or better in MATH 103, MATH 104, MATH 105, MATH 150A or MATH 255A, or a passing score on the Mathematics Placement Test (MPT) that satisfies prerequisites for MATH 150A or 255A; Lower division writing requirement. Corequisite: COMP 122L. Introduction to computer architecture, assembly language programming, system software and computer applications. Number systems and data representation. Internal organization of a computer. Primitive instructions and operations. Assembly language. Integrated lecture/lab environment. Lab: 3 hours per week.
COMP 182/L. Data Structures and Program Design and Lab (3/1)
Prerequisites: Grade of “C” or better in COMP 110/L; Grade of “C” or better in MATH 103, MATH 104, MATH 105, MATH 150A or MATH 255A, or a passing score on the Mathematics Placement Test (MPT) that satisfies prerequisites for MATH 150A or 255A; Lower division writing requirement. Corequisite: COMP 182L. Introduction to data structures and the algorithms that use them. Review of composite data types, such as arrays, records, strings and sets. Role of the abstract data type in program design. Definition, implementation and application of data structures, such as stacks, queues, linked lists, trees and graphs. Recursion. Use of time complexity expressions in evaluating algorithms. Comparative study of sorting and searching algorithms. Lab: 3 hours per week.
COMP 196A-Z. Experimental Topics Courses in Computer Science (1-4)
Course content to be determined.
COMP 222. Computer Organization (3)
Prerequisites: Grade of “C” or better in COMP 122/L and COMP 182/L. Extension of basic addressing concepts to more advanced addressability, such as base register and self-relative addressing. Comparative computer architecture focusing on such organizations as multiple register processors and stack machines. Basics of virtual memory input-output. Introduction to the concept of microprogrammable systems. Low-level language translation process associated with assemblers. System functions such as relocatable loading and memory management. Application of data structure and hashing techniques to the above. Other related topics.
COMP 256/L. Discrete Structures for Computer Science and Lab (3/1)
Prerequisites: COMP 182/L; MATH 150A; PHIL 230. Study of discrete mathematical structures and proof techniques as used in computer science. Discrete structures, such as functions, relations, sets, graphs and trees. Proof techniques, such as proof by induction, proof by contradiction and proof by cases. Counting techniques. Lab: 3 hours per week.
COMP 282. Advanced Data Structures (3)
Prerequisites: Grade of “C” or better in COMP 182/L and MATH 150A. Introduction to advanced data structures (particularly persistent structures) using object-oriented design. Main memory structures, hash tables and trees. Architectural foundations for files. Large-scale sorting. Hash-based persistent structures. Indexed files. Introduction to databases.
COMP 296A-Z. Experimental Topics Courses in Computer Science (1-4)
Course content to be determined.
COMP 300. Computer Fluency (3)
Prerequisite: Completion of the lower division writing requirement. Does not provide credit toward Computer Science major. Study of fundamental computing concepts related to: information technology, data and its digital representation, technological power, computing limitations and social impact. Survey of essential and advanced applications designed to process different forms of information other than text. Promote such computing skills as basic algorithmic thinking, debugging, logical reasoning and critical use of information. Develop capabilities for applying the technology. (Available for General Education, E Lifelong Learning.)
COMP 310. Automata, Languages and Computation (3)
Prerequisite: COMP 256/L or MATH 326. Study of the relation of languages (defined as sets of strings) and machines for processing these languages, with emphasis on classes of languages and corresponding classes of machines. Phrase structure languages and grammar. Types of grammar and classes of languages. Regular languages and finite state automata. Context-free languages and pushdown automata. Unrestricted languages and Turing Machines. Computability models of Turing, Church, Markov and McCarthy. Applications to programming languages, compiler design, and program design and testing.
COMP 322/L. Introduction to Operating Systems and System Architecture and Lab (3/1)
Prerequisite: COMP 222, or ECE 422 and ECE 425/L. Corequisite: COMP 322L. Recommended Prerequisite: COMP 105C or knowledge of “C” Language. Examination of the principal types of systems, including batch, multi-programming and time-sharing. Discusses networked system. Considers the salient problems associated with implementing systems, including interrupt of event driven systems, multitasking, storage and database management and input-output. Emphasizes some of the simple algorithms used to solve common problems encountered, such as deadlocks, queue service and multiple access to data. Projects are implemented to reinforce the lectures. One 3-hour lab per week.
COMP 333. Concepts of Programming Languages (3)
Prerequisite: COMP 282. Discussion of issues in the design, implementation and use of high-level programming languages through a historical framework, including how languages reflect different design philosophies and use requirements and the technical issues in the design of main abstraction constructs of programming languages. Other approaches to imperative or object-oriented programming, functional programming, logical programming and parallel programming.
COMP 380/L. Introduction to Software Engineering (2/1)
Prerequisites: COMP 270/L or COMP 282; PHIL 230; and Oral Communication GE Basic Skills Section A.4. Corequisite: COMP 380L. Concepts and techniques for systems engineering, requirements analysis, design, implementation and testing of large-scale computer systems. Principles of software engineering for production of reliable, maintainable and portable software products. Emphasis on object-oriented analysis and design techniques. Topics include unit, integration and systems testing, configuration management, software quality assurance practices and an introduction to Computer Aided Software Engineering (CASE). This is a lecture portion of a course in software engineering involving the design and partial implementation of a software system as a group project. Lab: 3 hours per week.
COMP 396A-Z. Experimental Topics Courses in Computer Science (1-4)
Course content to be determined.
COMP 410. Logic Programming (3)
Prerequisites: COMP 333, COMP 282, COMP 310; Attempted Upper Division Writing Proficiency Exam. Programming techniques in the logic programming language PROLOG. Prenex conjunctive normal form and grammatical algorithms. Tableaux, sequenzen, resolution and other semi-decision procedures. Closures of relations, fixed point theory, control mechanisms, relationship to functional programming. Available for graduate credit.
COMP 424. Computer System Security (3)
Prerequisites: COMP 322/L and COMP 380/L, or CIT 360/L and IS 435; Attempted Upper Division Writing Proficiency Exam. Analysis of the need for computer system security and the security techniques in operating systems, databases and computer networks. Supporting techniques, such as auditing, risk analysis and cost-benefit tradeoffs, are discussed. Available for graduate credit.
COMP 429. Computer Network Software (3)
Prerequisites: COMP 322/L; Attempted Upper Division Writing Proficiency Exam. Basic software design and analysis considerations in networking computers into coherent, cooperating systems capable of processing computational tasks in a distributed manner. Network topology, routing procedures, message multiplexing and process scheduling techniques. Available for graduate credit.
COMP 430. Language Design and Compilers (3)
Prerequisites: COMP 310, COMP 380/L; Attempted Upper Division Writing Proficiency Exam. Examination of the issues involved in the design and subsequent implementation of programming languages. Considerations of implementation difficulties, including various features in a programming language. Tools and techniques to facilitate both the processing of programming languages and the building of programming processors. Available for graduate credit.
COMP 440. Database Design (3)
Prerequisites: COMP 380/L; Attempted Upper Division Writing Proficiency Exam. Database structure, including: structure definition, data models, semantics of relations and operation on data models. Database schemas, including element definition and use and manipulation of the schema. Elements of implementation. Algebra of relations on a database. Hierarchical databases. Discussion of information retrieval, reliability, protection and integrity of databases. Available for graduate credit.
COMP 442. Machine Learning Principles (3)
Prerequisites: COMP 182/L and MATH 445; or COMP 380/L and MATH 340; or COMP 380/L and MATH 341. A study of the concepts, principles, techniques, and applications of machine learning. Topics include concept-based learning, information-based learning (decision trees and ID3 algorithms), rule-based learning (association rules, learning ordered rules, learning unordered rules, and descriptive rule learning), distance-based learning (nearest neighbor algorithms), probability-based learning (Bayesian classifiers and networks), and error-based learning (perceptron, multivariable linear regression with gradient descent, nonlinear and multidimensional models, artificial neural networks, and support vector machines). Model ensembles learning and reinforcement learning are also discussed. Available for graduate credit. Graduate students will be required to complete advanced projects.
COMP 465/L. Computer Graphic Systems and Design and Lab (2/1)
Prerequisites: MATH 262; Attempted Upper Division Writing Proficiency Exam. Corequisite: COMP 465L. Fundamental concepts of computer graphics. Graphics devices; graphics languages; interactive systems. Applications to art, science, engineering and business. Trade-offs between hardware devices and software support. Lab: 3 hours per week. Available for graduate credit.
COMP 467. Multimedia Systems Design (3)
Prerequisites: COMP 380/L; Attempted Upper Division Writing Proficiency Exam. Study of fundamentals of multimedia storage, processing, communication, presentation and display by digital means with emphasis on audio, still images and video media. Includes sampling theory, compression techniques and synchronization. Discussion of hypermedia and methodology issues. Multimedia programming; software tools for authoring multimedia applications and interfaces. Available for graduate credit.
COMP 469. Introduction to Artificial Intelligence (3)
Prerequisites: COMP 310, COMP 380/L, COMP 410; Attempted Upper Division Writing Proficiency Exam. Exploration of the use of computers to perform computations normally associated with intelligence. These include game playing, theorem proving, problem solving, question answering and visual perception. Topics include languages, system architectures and heuristic strategies for advanced, high-level computations. Covers computational models for knowledge representation, natural language and vision. Available for graduate credit.
COMP 482. Algorithm Design and Analysis (3)
Prerequisites: COMP 282; COMP 256/L or MATH 320 or MATH 326. The analysis of algorithms, in terms of time and space complexity for best/average/worst case execution using asymptotic notation; the application of standard algorithmic approaches, including greedy, divide and conquer, and dynamic programming, to algorithm design; and a review of classical algorithms, including sorting, searching, and graph algorithms.
COMP 484/L. Web Engineering I and Lab (2/1)
Prerequisites: COMP 322/L or COMP 380/L or CIT 360; Attempted Upper Division Writing Proficiency Exam. Corequisite: COMP 484L. Internet infrastructure and the underlying networking technologies. Study of system and software architectures for web applications, e-business and e-commerce systems. Principles of website design. Advances in web-engineering technologies. Principles of web-based based transaction processing. XML and the associated technologies. Web service technology. Security and privacy issues. Study of the emerging Internet technologies. Available for graduate credit. Two hour lecture and three hour lab per week.
COMP 485. Human-Computer Interaction (3)
Prerequisites: COMP 380/L or CIT 360; Attempted Upper Division Writing Proficiency Exam. Examines the information exchange between humans and computer systems. Discusses aspects of input/output devices, software engineering and human factors with respect to human-computer interactions. Topics include text and graphic display; user modeling; program design, debugging, complexity and comprehension; and current research studies and methodologies. Available for graduate credit.
COMP 490/L. Senior Design Project (3/1)
Prerequisites: COMP 380/L; Upper Division Writing Proficiency Exam. Corequisite: COMP 490L. Project-oriented course to allow students to apply their knowledge of software engineering to the design and implementation of a system to solve a real-world problem. Students select and specify a suitable problem, investigate design alternatives and select an appropriate one, implement a solution and verify and validate the result, all as part of a team effort. The role of digital computers in modern society are investigated, including the dangers of computer misuse, as well as the proper and intelligent use of computers. Ethical concerns of software professionals are studied. Lab: 3 hours per week.
COMP 491L. Senior Project Lab (1)
Prerequisites: COMP 490/L. Project-oriented lab to allow students to complete the design, implementation and testing of the team-based software engineering project started in COMP 490/L. Lab: 3 hours per week.
COMP 492. Projects in Data Science (3)
Prerequisites: COMP 442 and MATH 445. Students will gain practical experience in the field of data science by applying their knowledge of software engineering and statistical data analysis to one or more real datasets. Students select and specify a suitable data analysis problem, investigate questions and hypotheses that arise from the real dataset(s), and use programming, system implementation, and statistical analysis to find answers to those hypotheses. The projects are conducted in groups and each group is required to produce a written project report at the end of the semester as well as an oral presentation to the departments and/or their peers. This course synthesizes concepts introduced in both Computer Science and Math prerequisite courses.
COMP 494A-C. Academic Internship (1-3)
Prerequisites: Junior standing or above in major; Upper Division Writing Proficiency Exam; Prior approval of the department; Good standing as a matriculated student. Academic internship training program. Supervised off-campus professional computing experience for selected computer science students. Academic internship units do not count toward General Education units or major requirements. Maximum of 6 units of enrollment is allowed. Only one enrollment per semester permitted. (Credit/No Credit only)
COMP 496A-Z. Experimental Topics Courses in Computer Science (1-4)
Course content to be determined.
COMP 499A-C. Independent Study (1-3)
COMP 522. Embedded Applications (3)
Prerequisites: COMP 322/L or instructor’s consent. Embedded systems present cost effective, challenging and flexible computational platforms. Instruction in the unique aspects of embedded systems including architectures, instruction sets, development environments, concurrent programming, networking, applications of embedded platforms, data acquisition from sensors and interaction with surrounding environment.
COMP 528/L. Mobile Computing and Lab (2/1)
Prerequisites: COMP 322/L, COMP 380/L. Corequisite: COMP 528L. Issues related to the design, development, networking, and deployment of mobile computing system for pervasive and mobile applications. Two hours of lecture and three hours of laboratory per week.
COMP 529/L. Advanced Network Topics and Lab (2/1)
Prerequisites: COMP 429 or instructor consent; MATH 340 or MATH 341. Corequisite: COMP 529L. Architectural principles: naming, addressing, routing; congestion control, traffic management, QoS; wireless networks; overlay networks and virtualization; queueing theory; measurements; network security; switching and routing; content distribution; and proposals for future Internet structures.
COMP 539. Network Infrastructure (3)
Prerequisite: COMP 424 or COMP 429 or instructor’s consent. Topics regarding the implementation and administration of network and information infrastructure components will be presented. Issues covered include security administration, packet filtering, proxy services and virus protection. Fundamentals of administering information services such as SMTP, DNS, LDAP and HTTP will be investigated. Internet infrastructure administration and routing protocols such as RIP, BGP and link redundancy will also be explored.
COMP 541. Data Mining (3)
Prerequisites: COMP 380/L. A study of the concepts, principles, techniques and applications of data mining. Topics include data preprocessing, the ChiMerge algorithm, data warehousing, OLAP technology, the Apriori algorithm for mining frequent patterns, classification methods (such as decision tree induction, Bayesian classification, neural networks, support vector machines and genetic algorithms), clustering methods (such as k-means algorithm, hierarchical clustering methods and self-organizing feature map)and data mining applications (such as Web, finance, telecommunication, biology, medicine, science and engineering). Privacy protection and information security in data mining are also discussed.
COMP 542. Machine Learning (3)
Prerequisites: COMP 380/L and MATH 340 or MATH 341; or graduate standing. A study of the concepts, principles, techniques, and applications of machine learning. Topics include concept-based learning, information-based learning (decision trees and ID3 algorithms), rule-based learning (association rules, learning ordered rules, learning unordered rules, and descriptive rule learning), distance-based learning (nearest neighbor algorithms), probability-based learning (Bayesian classifiers and networks), and error-based learning (perceptron, multivariable linear regression with gradient descent, nonlinear and multidimensional models, artificial neural networks, and support vector machines). Model ensembles learning and reinforcement learning are also discussed.
COMP 560. Expert Systems (3)
Prerequisite: COMP 469. Extensive introduction to the concepts and techniques of expert systems. Rationale for such systems, including evaluation of prospective domains. Explores existing systems, those under development and likely future areas. Basic architecture is demonstrated using both example and rule-based systems. Commercial tools for building expert systems are surveyed and evaluated. Knowledge acquisition methods. Guidelines given for planning and managing development projects.
COMP 565. Advanced Computer Graphics (3)
Prerequisites: COMP 322/L. This course will cover the theory, design, implementation and application of advanced computer graphics environments. Accelerated 3D graphics APIs; the modeling and simulation of light, sound, physical objects, motion and collisions; and user interaction in single- and multi-user virtual environments will be studied. The application domain for this class is interactive 3D computer games, scientific visualization and virtual reality.
COMP 581. Open Source Software Engineering (3)
Prerequisites: COMP 380/L. Introduction to open source software engineering concepts, principles and applications. Topics include history of open source software, open source software engineering models, open source products and software quality, strategies and business models, government policies toward open source software, work organization of open source software development, software and intellectual property rights, organizations of the open source community, and case studies. Different open source software products for various applications are also discussed and used for group projects.
COMP 582. Software Requirements Analysis and Specification (3)
Prerequisites: COMP 380/L. An in-depth study of the early phases of the software development life cycle commonly called software requirements analysis and specification. Topics include the gathering of both functional and nonfunctional requirements, customer communication, requirements prototyping, requirements modeling, requirements validation, the documentation of requirements in terms of a formal software requirements specification, and the management of software requirements.
COMP 583. Software Engineering Management (3)
Prerequisites: COMP 380/L; Upper Division Writing Proficiency Exam. Provides a framework for understanding software engineering management models, technologies, trends, tools and planning processes. Emphasizes the development of an individualized approach to managing software teams, projects and systems. The role of management as an increasingly critical factor in software engineering is examined.
COMP 584. Advanced Web Engineering (3)
Prerequisites: COMP 380/L. A study of the concepts, principles, techniques and methods of Web engineering. Topics include requirements engineering, modeling and architectures, design and technologies, testing, operation and maintenance, Web project management, application development process, usability, and performance and security of Web applications. Technologies, business models and strategies and societal issues of Web 2.0 and Semantic Web also are discussed.
COMP 585. Graphical User Interfaces (3)
Prerequisites: COMP 322/L, COMP 380/L. The design, development and analysis of programs requiring graphical, direct manipulation and user interfaces (GUIs) will be examined. The majority of modern software includes a GUI. The development tools, environments and style guides for common GUIs will be used in course assignments and discussed in lecture. The course involves the design and development of several GUI programs. The aesthetic and human computer interaction aspects and future trends in GUIs design and development also will be reviewed.
COMP 586. Object-Oriented Software Development (3)
Prerequisites: COMP 322/L, COMP 380/L. Review of object-oriented concepts. Comparison with functional methods. Benefits and pitfalls of object orientation. Fundamentals of object-oriented modeling—associations, links and states. Survey of object-oriented development methods. In-depth study of a current object-oriented method. Object-oriented software requirements analysis and modeling. Object-oriented preliminary design. Designing concurrent and multiprocessor systems. Object-oriented detailed design. Object-oriented and object-based implementations. Object-oriented testing.
COMP 587. Software Verification and Validation (3)
Prerequisites: COMP 380/L; Passing score on the Upper Division Writing Proficiency Exam. An-in depth study of verification and validation strategies and techniques as they apply to the development of quality software. Topics include test planning and management, testing tools, technical reviews, formal methods and the economics of software testing. The relationship of testing to other quality assurance activities as well as the integration of verification and validation into the overall software development process are also discussed.
COMP 589. Software Metrics (3)
Prerequisites: COMP 380/L; MATH 340 or MATH 341; Passing score on the Upper Division Writing Proficiency Exam. The role of metrics and quantitative models in software development. Product metrics, process metrics, measurement models and techniques for empirical validation. Measurement and analysis. Implementation of a metrics program. Measuring software size, complexity and functionality at different stages of software development. Use of measures to predict effort and schedule required for software projects. Measures of software quality. Analyzing defect data to predict software reliability. Performance measures. Management applications for metrics. Tools that support metrics collection, analysis, summary and presentation.
COMP 595A-Z. Experimental Topics Courses (3)
Course content to be determined.
COMP 598A-Z. Advanced Selected Topics (1-4)
Prerequisite: Instructor consent.
COMP 610. Data Structures and Algorithms (3)
Prerequisites: COMP 310; MATH 482. Topics include design strategies for data structures and algorithms, theoretical limits to space and time requirements time/space trade offs, and open problems in the field.
COMP 615. Advanced Topics in Computation Theory (3)
Prerequisites: COMP 310; MATH 482. Languages and the theory of computation are studied in depth. Covers advanced material concerning regular and context free languages. Study of deterministic context-free languages, context sensitive languages, recursive and recursively enumerable sets. Investigation of current areas of interest.
COMP 620. Computer System Architecture (3)
Prerequisites: COMP 322/L, COMP 380/L. Analysis and evaluation of individual computers, networks of computers and the programs that support their operation and use. Emphasis on comparison of architectures and the risks and benefits associated with various approaches and configurations.
COMP 680. Advanced Topics in Software Engineering (3)
Prerequisites: COMP 322/L, COMP 380/L. New and emerging software engineering technologies and practices covering: principles, concepts, methods, notations, formalisms, techniques, and tools. Study of these technologies and practices from a practical as well as from a theoretical perspective. Explore current problems underlying the development of large software systems and approaches for dealing with them.
COMP 684. Software Architecture and Design (3)
Prerequisites: COMP 380/L, COMP 582. Techniques, methods and tools for designing, building, analyzing and evaluating the structural, architectural and behavioral properties of software systems. It includes the study of the fundamental concepts and principles of software architectural design, structured design, object-oriented design, component-level design and design for reuse.
COMP 695A-Z. Experimental Topics Courses (3)
Course content to be determined.
COMP 696A,C. Directed Graduate Research (1,3)
Prerequisite: Permission of project/thesis committee chair. (Credit/No Credit only)
COMP 698A,C. Thesis (1,3)
COMP 699A-C. Independent Study (1-3)