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Computer Science and Engineering

UB - University at Buffalo, The State University of New York

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CSE Undergraduate Course Offerings

Entire Catalog

The CSE graduate program has offered these courses over the last five years. Many courses are offered every year, but some are offered irregularly. Click the "More »" links to see more details and histories of course offerings.

Semester

CSE 101 Computers: A General Introduction

Introduces computers and applications software. Areas of study include computers and their societal impact; history; hardware; problem solving; buying computers and software; and application packages, such as word processing, spreadsheets, and database systems. Admitted computer science and computer engineering majors should not enroll in this course.

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CSE 111 Great Ideas in Computer Science

Designed to satisfy the mathematics core requirements. Students study algorithmic problem-solving techniques and gain an appreciation for some of the most interesting and significant results of computer science, as well as its intellectual and social significance. The course has both a mathematical and a laboratory component. Topics may include algorithm design, introduction to programming, structured programming, software tools, software engineering, text manipulation, numerical computation, transistors, very large-scale integrated circuits, machine architecture, language translation, operating systems, and artificial intelligence. Admitted computer science and computer engineering majors should not enroll in this course sequence.

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CSE 113 Introduction to Computer Programming I

Introduction to computers and computer programming intended for nonmajors. Currently required for some School of Management majors and appropriate for others seeking a practical introduction to computer programming. Topics include the use of data types and variables, programming control constructs supported by modern languages, input/output, basic concepts of object-oriented programming (such as classes, objects, encapsulation, information hiding, and code reuse), as well as graphical user interfaces. No previous computer experience assumed. Not suitable for intended computer science or computer engineering majors except those who have absolutely no experience using a computer. Admitted computer science and computer engineering students should not take this course.

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CSE 115 Introduction to Computer Science for Majors I

Provides the fundamentals of the field to computer science and computer engineering majors, introducing students to algorithm design and implementation in a modern, high-level programming language. Emphasizes problem solving by abstraction. Topics include object-oriented design using a formal modeling language; fundamental object-oriented principles such as classes, objects, interfaces, inheritance and polymorphism; simple event-driven programming; data types; variables; expressions; basic imperative programming techniques, including assignment, input/output, subprograms, parameters, sequencing, selection and iteration; the use of aggregate data structures, such as arrays or more general collections; simple design patterns.

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CSE 116 Introduction to Computer Science for Majors II

Continuation of CSE 115. Heavily emphasizes abstract data types (ADTs) and object-oriented methodology, and expects students not only to understand ADTs but also to design and implement robust ADTs using a modern object-oriented programming language. Further emphasizes object-oriented techniques, which support sound software engineering, such as encapsulation, polymorphism and inheritance as well as the use of more complex design patterns. Essential topics integrated in this framework include the use of recursion; linked data structures, including lists, stacks, queues, binary trees, and other advanced data structures; and algorithms for searching and sorting; exceptions and exception handling, event-driven programming. Introduces the analysis of algorithm complexity (0-notation).

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CSE 191 Discrete Structures

Foundational material for further studies in computer science. Topics include logic, proofs, sets, functions, relations, recursion, recurrence relations, mathematical induction, graphs, trees, and some basic counting theory. CSE 191 is required for computer science and computer engineering majors.

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CSE 241 Digital Systems

A course in digital principles which includes an introduction to machine dependent programming. Topics covered include: fundamentals of digital logic, computer arithmetic & Boolean algebra, minimization techniques, basic components of digital circuits such as logic gates and flip-flops, information representation, design of combinational and sequential circuits, memory devices and programmable logic devices, CPU organization, arithmetic logic unit and control unit design, assembly language programming.

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CSE 250 Algorithms & Data Structures

Course description is currently unavailable.

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CSE 250 Data Structures

Provides a rigorous analysis of the design, implementation, and properties of advanced data structures. Topics include order notation and time-space analysis and tradeoffs in a list, tree and graph algorithms, and hashing. Surveys library implementations of basic data structures in a high-level language. Advanced data structure implementations are studied in detail. Illustrates the importance of choosing appropriate data structures when solving a problem by programming projects in a high-level language different from the language of CSE 115 and CSE 116; also covers instruction in this language. CSE 191 may also be used as a corequisite.

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CSE 305 Introduction to Programming Languages

Examines the various components of programming languages so students will understand the choices that have been made by programming language designers, and how those choices affect how procedures may be expressed and how data are conceptualized. Topics generally include the nature of variables, types, expressions, control structures, subprograms, concurrency, and exceptions; syntax and semantics. Discusses different programming paradigms, such as imperative, functional, logic, procedural and object-oriented.

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CSE 321 Real-Time and Embedded Operating Systems

Addresses some of the fundamental challenges in the design, implementation, and validation of these real-time and embedded systems. Topics include resource management, concurrency, secure coding practices, memory management, timeline design and analysis using metrics and schedulability tests, hardware interfacing, device driver programming, memory maps and boot kernels, firmware and ROM-resident system code, communications and networking, and debugging live systems. These concepts will be reinforced through C programming assignments using the RTLinux operating system.

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CSE 331 Introduction to Algorithm Analysis and Design

Introduces methods for algorithm design, paradigms such as divide and conquer, greedy, and dynamic programming, and techniques for algorithm analysis, such as asymptotic notations, estimates and recursions. Topics include sorting, searching, scheduling, string matching, graph algorithms, computational geometry, and more.

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CSE 341 Computer Organization

Basic hardware and software issues of computer organization. Topics include computer abstractions and technology, performance evaluation, instruction set architecture, arithmetic logic unit design, advanced computer arithmetic, datapath and control unit design, pipelining, memory hierarchy, input-output.

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CSE 379 Introduction to Microprocessors and Microcomputers

Microprocessor architecture, machine language programming, microprocessor assemblers, assembly language programming, software development, memory and I/O interface, interrupts, microprocessor system design and microprocessor applications.

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CSE 380 Introduction to Microprocessors and Microcomputers Lab

A microprocessor system and its application in embedded devices. This course is the laboratory component to CSE 379. Topics include: microprocessor architecture; memory organization; assembly language programming; microprocessor assemblers; software development; use of microprocessor boards; memory and I/O interfaces; programming peripherals; interrupt system programming; microprocessor system design and applications.

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CSE 396 Introduction to the Theory of Computation

Covers machine models and formal specifications of the classes of computational problems they can solve. The central concepts are the Turing machine and the classes of decidable and computably enumerable languages. The Halting Problem and other natural problems are shown to be undecidable by Turing machines, implying that they are undecidable by high-level programming languages or any other known computational model. Finite automata, which are Turing machines without external memory, are shown to correspond to the class of regular languages. The course also covers regular expressions, time and space complexity of Turing machines, reducibility between problems, and NP-completeness.

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CSE 410 Special Topics

Course description is currently unavailable.

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CSE 411 Introduction to Computer Systems Administration

Teaches how to administer a network of computer workstations using an Operating System such as UNIX. Topics include managing user accounts, system backups, installing and configuring the operating system, setting up a computer network, shell programming, and computer security.

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CSE 421 Introduction to Operating Systems

Covers the principles and techniques in the design of operating systems. Describes concepts of operating systems in terms of functions, structure, and implementation, particularly emphasizing multiprogramming. Topics include process coordination, deadlocks, memory management, device management, file systems, scheduling policies for CPU, and network and distributed operating systems. Illustrates concepts with examples from existing operating systems.

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CSE 422 Operating Systems Internals

Uses an operating system (such as UNIX) as an example to teach the internal workings of operating systems. The material presented is more practical than the other operating systems related classes. The laboratory component of this course provides programming projects involving modifications to an operating system kernel (such as UNIX) on computers dedicated to use for this course. Topics covered include building the operating system kernel, the system call interface, process management, kernel services provided for processes, the I/O system, the internal workings of the file system, device drivers, and the kernel support of Interprocess Communications.

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CSE 431 Algorithms Analysis and Design

Introduces basic elements of the design and analysis of algorithms. Topics include asymptotic notations and analysis, divide and conquer, greedy algorithms, dynamic programming, fundamental graph algorithms, NP-completeness, approximation algorithms, and network flows. For each topic, beside in-depth coverage, we discuss one or more representative problems and their algorithms. In addition to the design and analysis of algorithms, students are expected to gain substantial discrete mathematics problem solving skills essential for computer scientists and engineers.

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CSE 435 Information Retrieval

This course will focus on text-based information retrieval (IR) techniques, more popularly known as search engines. Various IR models such as the Boolean model, vector space model, probabilistic model will be studied. Efficient indexing techniques for large document collections as well as specialized collections will be examined. Various query expansion techniques such as local context analysis will be introduced. Finally, the course will also discuss search engines for the web, and the use of link analysis to determine document/page relevance. Students will work on written assignments, as well as hands-on programming projects to gain expertise in this area.

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CSE 442 Software Engineering

Examines in detail the software development process. Topics include software life-cycle models; architectural and design approaches; various techniques for systematic software testing; coding and documentation strategies; project management; customer relations; the social, ethical, and legal aspects of computing; and the impact of economic, environmental, safety, manufacturability, and sustainability factors on design. Students in this course participate in a real-world project from conception to implementation.

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CSE 443 Language Processors Intro

Course description is currently unavailable.

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CSE 452 Vlsi Testing

Course description is currently unavailable.

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CSE 453 Hardware/Software Integrated Systems Design

Software designs produced in the prerequisite CSE 442 Software Engineering course are carried here to a complete hardware realization. Bringing skills learned from previous hardware and software-oriented courses, students form multidisciplinary workgroups and are given tools, parts, goals, and constraints, all of which define the integrated design setting. These workgroups identify, formulate, and solve the hardware and software problems posed by their project, and defend their realization concepts at key intervals during the project build-out. Projects are tested, and a report analyzing the level of satisfaction of design and performance specifications submitted. Each group prepares a "rollout" presentation, which includes a demonstration of their project in operation. This is a required course for CEN majors.

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CSE 455 Introduction To Pattern Recognition

Foundations of pattern recognition algorithms and machines, including statistical and structural methods. Data structures for pattern representation, feature discovery and selection, classification vs. description, parametric and non-parametric classification, supervised and unsupervised learning, use of contextual evidence, clustering, recognition with strings, and small sample-size problems. programming projects.

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See:http://www.cse.buffalo.edu/~jcorso/t/CSE455

CSE 456 Introduction To Visualization

Course description is currently unavailable.

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CSE 462 Database Concepts

Discusses basic concepts of modern database management systems. Topics include: data models, query languages, database design, integrity constraints, indexing, query evaluation, and transaction management. Students implement small projects using modern DBMS.

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CSE 463 Knowledge Representation

Introduces the field of knowledge representation and reasoning, the branch of artificial intelligence concerned with the techniques for representing and reasoning about the information to be used by an AI program. Topics typically include: the knowledge-representation hypothesis; propositional and first-order logic; model finding; resolution; syntactic proof theory; direct and refutation methods; relevance logic; truth maintenance and belief revision; commonsense reasoning; ontologies. Other topics that may be included as time permits are: modal logics; non-monotonic, defeasible, and default logics; logics of knowledge and belief; frames; description logics; vague and uncertain beliefs; logics of actions and time.

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CSE 467 Computational Linguistics

Introduces computational models for understanding natural languages. Covers topics including, but not limited to, syntactic and semantic parsing, generation, and knowledge representation techniques. Cross-listed with LIN 467.

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CSE 473 Introduction to Computer Vision and Image Processing

Introduces those areas of artificial intelligence that relate to fundamental issues and techniques of computer vision and image processing. Emphasizes physical, mathematical, and image-processing aspects of vision. Topics include image formation, edge detection, segmentation, convolution, image-enhancement techniques, extraction of features (such as color, texture, and shape), object detection, 3-D vision, and computer system architectures and applications.

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See:http://www.cse.buffalo.edu/courses/cse573/peter/index.html

CSE 474 Introduction to Machine Learning

Involves teaching computer programs to improve their performance through guided training and unguided experience. Takes both symbolic and numerical approaches. Topics include concept learning, decision trees, neural nets, latent variable models, probabilistic inference, time series models, Bayesian learning, sampling methods, computational learning theory, support vector machines, and reinforcement learning.

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CSE 484 Philosophy of Computer Science

Introduces philosophical issues in computer science. Examines the nature of computer science (e.g., whether it is a science or a branch of engineering, whether it is the study of physical computers or abstract computing); the nature of computation, algorithms, and software, and their implementation in computer programs; the nature of computer programs (e.g., whether they are theories, models, or simulations; whether they can or should be patented or copyrighted; whether they can be verified). Also briefly explores the philosophy of artificial intelligence and issues in computer ethics. Offered irregularly. Cross listed with PHI 484.

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CSE 486 Distributed Systems

Addresses some of the fundamental challenges in the design, implementation and deployment of large-scale distributed systems. Concepts covered include concurrency, synchronization, connection establishment, event handling, inter process communication, storage management, and service registration, discovery, and lookup. Also covers issues related to distributed objects such as life cycle management, mobility, security, naming, location, evolution, and autonomy. Analyses and implements possible solutions using objects, processes, services, components and frameworks. Offered irregularly.

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CSE 487 Data Intensive Computing

Overview of information technology in large-scale commercial and scientific systems, emphasizing state of the art computing in realizing various services and the frameworks supporting these services. Concepts covered include: enterprise modeling, process modeling, process automation and streamlining, workflow management, messaging, persistent message queues, transaction monitoring, document exchange, application servers, service definition (web services, web services definition language: WSDL), connection and resource reservation protocols (TCP, grid computing), integration technologies and architectures (Java 2 Enterprise Edition: J2EE, extensible Markup Language: XML, and Globus toolkit).

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CSE 489 Modern Network Concepts

Introduces basic elements of modern computer and telecommunications networks. Discusses a hybrid five-layer reference model resembling the popular TCP/IP model. In each layer, the course introduces the state-of-the-art hardware and software technologies. These include, for example, fiber-optic and wireless/mobile/cellular communications at the physical layer, to network security in the application layer. Offered once a year.

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CSE 490 Computer Architecture

Examines system architecture with 32- and 64-bit microprocessors. Topics include the design of high-performance computer systems, such as workstations and multiprocessor systems using recent advanced microprocessor. Considers the internal architecture of recent microprocessors, followed by vector processing, memory hierarchy design, and communication subsystems for I/O and interprocessor communication.

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CSE 492 Undergrad Peer Mentoring

Course description is currently unavailable.

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CSE 493 Introduction to VLSI Electronics

Introduces VLSI electronics. VLSI is the integration of a large number of logic gates on a single semiconductor chip. Applications of VLSI include memory, microprocessors, and signal processing. Topics include digital system design; VLSI systems; CMOS circuits; use of CAD tools in the layout of full-custom and semi-custom integrated circuits. Project required. Emphasizes designing a working chip and understanding various steps in design. Typical projects: ALU, games, controllers.

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CSE 495 Supervised Teaching

Course description is currently unavailable.

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CSE 496 Internship/practicum

Course description is currently unavailable.

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CSE 498 Undergraduate Research & Creative Activities

Course description is currently unavailable.

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CSE 499 Independent Study

Course description is currently unavailable.

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