Course Descriptions

CS 100 Computer Science Freshman Seminar
Credit Hours: 1+0
Fulfils: CS Major Requirement
Prerequisite: None
​Provides a broad overview of the theory and practice of Computer Science.

CS 101 Programming Fundamentals
Credit Hours: 2+1
Prerequisite: None
Fulfils: CS Foundation, Formal Reasoning
Motivates computer programming as a means to solve problems; introduces the basic components of
problem solving: repetition, decision making, data storage and manipulation, input/output, modularity,
top-down design; develops expertise in the corresponding constructs – variables, data types, iteration,
conditionals, functions, file and console I/O, and recursion – in a high level programming language.

CS 102 Data Structure and Algorithms
Credit Hours: 3+1
Prerequisite: CS 101
Fulfils: CS Foundation
Motivates the design of algorithms by exploring various algorithms for a single task: linear search and binary search, bubble sort, insertion sort, selection sort, merge sort, quick sort; introduces techniques to reason about and compare algorithms: asymptotic analysis and notation, Master theorem; introduces frequently used data structures: list, tree, graph, stack, queue; discusses and analyzes basic operations on the data structures: infix, postfix, and prefix traversal, breadth-first and depth-first search, computation of graph properties.

CS 113 Discrete Mathematics
Credit Hours: 3+0
Prerequisite: None
Fulfils: CS Foundation, Formal Reasoning
Equips students with essential mathematical tools that will be encountered in future Computer Science courses; develops a capacity for formal mathematical manipulation and abstract thought; topics include: propositional logic, predicate and quantifiers, sets, functions, sequences, summations, relations, partial orderings, proofs, mathematical induction, pigeonhole principle, permutations and combinations, graphs, graph isomorphism, Euler and Hamiltonian paths, trees.

CS 201 Data Structures II
Credit Hours: 3+0
Prerequisite: CS 102 and CS 113
Fulfils: CS Kernel
Imparts proficiency in the use of commonly used data structures; introduces a few higher level data structures; develops critical judgment regarding the choice of data structures for a given situation; topics include: abstract data type, complexity, stack, queue, list, amortized analysis, array-list, linked list and skip list, hashing, binary tree, binary search tree (BST), randomized BST and treap, self-balancing in trees, AVL tree, B-tree, red-black tree, binary heap and meldable heap, Fibonacci heap, graphs and their representations, graph algorithms, trie, inverted index.

CS 212 Nature of Computation
Credit Hours: 3+0
Prerequisite: CS 113
Fulfils: CS Kernel
Develops the foundations for theoretical computer science; investigates fundamental challenges at the frontiers of theoretical computer science; provides opportunities to develop rigorous mathematical arguments; engages with classical ideas from theoretical computer science; topics include: proofs, languages, finite automata, grammars and push down automata, Turing machines and the halting problem, oracles and computability, Gödel’s completeness and incompleteness theorems, circuit complexity, polynomial time and its justification, reduction, P, NP, and NP-completeness, Cook-Levin theorem, hardness of the P versus NP problem, randomness, P versus BPP, interactive proofs, zeroknowledge proofs, quantum computing, DNA computing, biological computing, physical limits of computation.

CS 224 Object Oriented Programming and Design Methodologies
Credit Hours: 3+1
Fulfils: CS Kernel
Prerequisite: CS 102
Introduces object oriented and related memory concepts; motivates C++ as the language of choice; topics include: pointers and structs, objects, heap allocation, data encapsulation, classes, namespaces, constructors and destructors, virtual functions and destructors, operator overloading and standard input/output, inheritance and polymorphism, templates, standard library containers, and software design using UML 2.0.

CS 232 Operating Systems
Credit Hours: 3+1
Fulfils: CS Kernel
Prerequisite: CS 102
The student will be taught principles of modern operating systems. In particular, the course will cover details of concurrent processes, multi-threads, CPU scheduling, memory management, file system, storage subsystem, and input/output management. This will be accomplished by integrating theory and practice through coordinated lecture and lab hours.

CS 330 Computer Architecture
Credit Hours: 3+1
Prerequisite: CS 130
Fulfils: CS Systems Elective
Studies the architecture of RISC-V processor that enables general purpose computing; develops hands-on expertise in developing complex logical components; topics include: instruction set architecture, addressing modes, processor design and computer arithmetic, pipelining, memory systems, fetchexecution cycle, processor implementation on FPGA using Verilog HDL.

CS 353 Software Engineering
Credit Hours: 3+0
Prerequisite: CS 224 and CS 355
Fulfils: CS Kernel
Approaches software engineering as the study and practice of a collection of concepts, techniques and tools which enable programmers to design, build, and maintain large software systems in a reliable and cost effective way; develops skills and understanding that function as the basis for many of the more advanced analysis and design practices encountered in the industry; topics include: systems development process, stakeholders and their roles, systems development project needs, software process methodologies, spiral and RUP, software analysis and requirement discovery, data modelling, SAD and
OOAD, UML, use case diagrams, software project management, project scope, network diagrams and CPM, agile methodologies, XP, Scrum and FDD, class diagrams, realization of use cases, object oriented design, sequence diagrams, activity diagrams, state transition diagrams, user interface design, software testing, software construction and maintenance.

CS 355 Database Systems
Credit Hours: 3+1
Prerequisite: CS 102
Fulfils: CS Kernel
Explores in detail the theoretical and practical aspects of Relational Database Management Systems(RDBMS); develops an understanding of database modeling, relational algebra, structured query language (SQL), components of Database Management System (DBMS), transaction management and concurrency
control, database fine-tuning via indexing and partitioning, and database connectivity with front-end applications; discusses administrative aspects of database systems including database security, database management vs data warehousing vs data mining, and big data and its challenges.

CS 412 Algorithms: Design and Analysis
Credit Hours: 3+0
Prerequisite: CS 201 and MATH 310
Fulfils: CS Kernel
Develops tools and techniques that aid in designing correct, efficient algorithms for computational problems and analyzing their correctness and running time; some of the discussed techniques are: greedy method, divide-and-conquer, dynamic programming, hashing, randomization, network flows, linear programming, Fast Fourier Transform, and techniques for thinking about solving problems in parallel; analysis tools include: recurrences, probabilistic analysis, amortized analysis, and potential functions.

CS 491 Kaavish I
Credit Hours: 0+3
Prerequisite: CS 353
Fulfils: Capstone Project
Self-directed final year project carried out under the supervision of a faculty member; emphasizes solving a real-world problem; integrates knowledge and skills accumulated over the entirety of the degree; first of a 2-part sequence.

CS 492 Kaavish II (0+3)
Credit Hours: 0+3
Prerequisite: CS 491
Fulfils: Capstone Project
Self-directed final year project carried out under the supervision of a faculty member; emphasizes solving a real-world problem; integrates knowledge and skills accumulated over the entirety of the degree; second of a 2-part sequence.