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

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.

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.

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.

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.

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).

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.

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.

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.

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.

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.

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.

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.

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.

This course introduces students to algorithm design and implementation in a modern, high-level, programming language (currently, Java). It emphasizes problem-solving by abstraction. There will also be a brief coverage of the social and ethical aspects of computing. Topics include data types, variables, expressions, basic imperative programming techniques including assignment, input/output, subprograms, parameters, selection, iteration, Boolean type, and expressions, and the use of aggregate data structures including arrays and records. Students will also have an introduction to the basics of abstract data types and object-oriented design, as well as the mathematics of computer science such as Boolean algebra, basic number theory, etc.

May not be counted toward the 30 hours for the M.S. or the 72 hours for the Ph.D.

This course is a continuation of CSE 503, in which heavy emphasis is placed on abstract data types (ADTs) and object-oriented methodology, where the student will be expected not only to understand ADTs, but also to design and implement robust ADTs using a modern, object-oriented, programming language. Topics such as encapsulation, polymorphism, templates, and inheritance will be emphasized. Essential topics to be integrated in this framework include the use of recursion; pointers; dynamic memory management; linked structures including linked lists, binary trees, stacks, queues, and other advanced data structures; and algorithms, including advanced searching and sorting algorithms. The analysis of algorithm complexity ("big O" notation) will be introduced.

May not be counted toward the 30 hours for the M.S. or the 72 hours for the Ph.D.

This course 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.