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Course Criteria
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3.00 Credits
Principles of counting. Boolean operations. Logic and methods of proof. Sets, relations, functions, strings, and languages. Students cannot get credit for both CS 2305 and CE/TE 3307. Prerequisite: MATH 1326, MATH 2413 or MATH 2417. (3-0) S
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3.00 Credits
Exceptions and number formatting. File input/output using Stream classes. Implementation of primitive data structures, including linked lists (all types), stacks, queues, and binary trees. Advanced data manipulation using core classes. Introduction to multithreading, multimedia, and networking. Includes a comprehensive programming project. Prerequisite: CS 1337. (Same as CE 2336) (3-0) S
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1.00 - 6.00 Credits
Individual study under a faculty member's direction. May be repeated for credit as topics vary (6 hours maximum). Consent of instructor required. (Same as SE 2V95) ([1-6]-0) R
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1.00 - 3.00 Credits
In this course, students will work together in small teams to solve graduated problems, similar to those used in programming contests around the world. Approaches to categorizing problems and selecting appropriate data structures and algorithms will be covered, along with types of algorithms for solving problems (brute force, greedy, divide and conquer, dynamic programming). Students will do problem solving in a competitive environment against the clock. May be repeated for credit (3 hours maximum). Prerequisites: CS 2336 and CS 3305. (1-0) Y
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1.00 - 3.00 Credits
May be repeated for credit as topics vary (4 hours maximum). Must be taken Credit/No Credit. Consent of instructor required. (Same as SE 3195) (1-0) R
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3.00 Credits
Topics in enumeration; principle of inclusion and exclusion. Partial orders and lattices. Algorithmic complexity; recurrence relations. Graph theory. Students cannot receive credit for both CS 3305 and CE/TE 3307. Prerequisite: CS 2305. (3-0) S
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3.00 Credits
Programming with basic data structures (arrays, stacks, queues, lists, and trees) and their associated algorithms. Various sorting and searching techniques. Fundamental graph algorithms. This course covers much of the same material as CS 3345 without requiring the analysis of algorithms. Computer Science majors may NOT take this course. This course may not be taken for degree credit by students who have completed CS 2336 (C/C++). Prerequisite: CS 1337 or CS 3335 or equivalent programming experience. (3-0) Y
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3.00 Credits
Numerous programming projects in both C and C++. All fundamentals of C, with special emphasis on use of pointers. Use of C++ extensions to create and extend (by inheritance) abstract data types. The use/ advantages of virtual functions (dynamic polymorphism). Prerequisite: CS 2336 or equivalent. (3-0) T
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3.00 Credits
This course introduces the concepts of computer architecture by going through multiple levels of abstraction, and the numbering systems and their basic computations. It focuses on the instruction-set architecture of the MIPS machine, including MIPS assembly programming, translation between MIPS and C, and between MIPS and machine code. General topics include performance calculation, processor datapath, pipelining, and memory hierarchy. Students who have already completed CS 2310 or CS/SE 4340 cannot receive credit for this course. Students cannot get credit for both CS/SE 3340 and CE/EE 4304. Prerequisite: CS 1337. (Same as SE 3340) (3-0) S
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3.00 Credits
Axiomatic probability theory, independence, conditional probability. Discrete and continuous random variables, special distributions of importance to CS/SE and expectation. Simulation of random variables and Monte Carlo methods. Central limit theorem. Basic statistical inference, parameter estimation, hypothesis testing, and linear regression. Introduction to stochastic processes. Illustrative examples and simulation exercises from queuing, reliability, and other CS/SE applications. Students cannot get credit for both CS/SE 3341 and CE/EE/TE 3341. Prerequisites: MATH 1326, MATH 2414 or MATH 2419, and CS 2305. (Same as SE 3341) (3-0) S
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