
Term I  Course #  Course Name  Lecture  Lab  Study  Credit 

CS 115  Introduction to Computer ScienceThis is an introduction to computer science with an emphasis on programming. The topics include: design; algorithmic thinking; recursion; objectoriented programming; ethics in computer science; and some basics about computer systems: machine language, interpreters, compilers, and data representation. Close  3  2  8  4   Science I  3  0  3  3  CS 146  Introduction to Web Programming and Project DevelopmentThis course introduces students to the infrastructure underlying the Web, including protocols and markup languages. It also addresses the question of how one presents large volumes of information to people who need to find out what they are looking for quickly. The scope of the course ranges from mechanics to aesthetics. Social and ethical issues are also discussed, including the concept of information ecologies for social acceptance. Networks and protocols; pervasive computing; Web protocols; markup languages and XML; defining information architecture; understanding information needs and informationseeking behaviors; organizing Web sites and intranets; navigation systems; search systems; thesauri; from research to design: strategies for information architecture; enterprise information architecture; ethics on the Web; and information ecologies. Close  3  0  6  3  MA 121  Differential CalculusLimits, the derivatives of functions of one variable, differentiation rules, applications of the derivative. This is a seven week course. Prerequisites:MA 120Introduction to Calculus (400)
(LectureLabStudy Hours)
The first part of the course reviews algebra and precalculus skills. The second part of the course introduces students to topics from differential calculus, including limits, rates of change and differentiation rules. This is a seven week course. Close 
Close  4  0  8  2  MA 122  Integral CalculusDefinite integrals of functions of one variable, antiderivatives, the Fundamental Theorem, integration techniques, improper integrals, applications. This is a seven week course. Prerequisites:MA 121Differential Calculus (408)
(LectureLabStudy Hours)
Limits, the derivatives of functions of one variable, differentiation rules, applications of the derivative. This is a seven week course. Close 
Close  4  0  8  2  CAL 103 OR CAL 105  Writing And Communications ColloquiumThis course empowers students with the written and oral communications skills essential for both universitylevel academic discourse as well as success outside Stevens in the professional world. Tailored to the Stevens student, styles of writing and communications include technical writing, business proposals and reports, scientific reports, expository writing, promotional documents and advertising, PowerPoint presentations, and team presentations. The course covers the strategies for formulating effective arguments and conveying them to a wider audience. Special attention is given to the skills necessary for professional document structure, successful presentation techniques and grammatical/style considerations. Close OR CAL Colloquium: Knowledge, Nature, CultureThis course introduces students to all the humanistic disciplines offered by the College of Arts and Letters: history, literature, philosophy, the social sciences, art, and music. By studying seminal works and engaging in discussions and debates regarding the themes and ideas presented in them, students learn how to examine evidence in formulating ideas, how to subject opinions, both their own, as well those of others, to rational evaluation, and in the end, how to appreciate and respect a wide diversity of opinions and points of view. Close  3  0  6  3  PE 200  Physical Education I  0  0  0  0   Total  20  2  39  17 
 Term II  Course #  Course Name  Lecture  Lab  Study  Credit 

CS 284  Data StructuresThis is a course on standard data structures, including sorting and searching and using the Java language. The topics include: stages of software development; testing; UML diagrams; elementary data structures (lists, stacks, queues, and maps); use of elementary data structures in application frameworks; searching; sorting; and introduction to asymptotic complexity analysis. Corequisites:CS 135Discrete Structures (328)(LectureLabStudy Hours) The aim of this course is to integrate knowledge of basic mathematics with the problems involving specification, design, and computation. By the end of the course, the student should be able to: use sets, functions, lists, and relations in the specification and design of problems; use properties of arithmetic, modular arithmetic (sum, product, exponentiation), prime numbers, greatest common divisor, factoring, Fermat?s little theorem; use binary, decimal, and baseb notation systems and translation methods; use induction to design and verify recursive programs; and implement in Scheme all algorithms considered during the course. Close 
Prerequisites:CS 115Introduction to Computer Science (328)
(LectureLabStudy Hours)
This is an introduction to computer science with an emphasis on programming. The topics include: design; algorithmic thinking; recursion; objectoriented programming; ethics in computer science; and some basics about computer systems: machine language, interpreters, compilers, and data representation. Close 
Close  2  2  8  4   Science II  3  0  3  3   Science Lab  0  3  0  1  CS 135  Discrete StructuresThe aim of this course is to integrate knowledge of basic mathematics with the problems involving specification, design, and computation. By the end of the course, the student should be able to: use sets, functions, lists, and relations in the specification and design of problems; use properties of arithmetic, modular arithmetic (sum, product, exponentiation), prime numbers, greatest common divisor, factoring, Fermat?s little theorem; use binary, decimal, and baseb notation systems and translation methods; use induction to design and verify recursive programs; and implement in Scheme all algorithms considered during the course. Close  3  2  8  4  MA 123  Series, Vectors, Functions, and SurfacesTaylor polynomials and series, functions of two and three variables, linear functions, implicit functions, vectors in two and three dimensions. This is a seven week course. Prerequisites:MA 122 or Integral Calculus (408)
(LectureLabStudy Hours)
Definite integrals of functions of one variable, antiderivatives, the Fundamental Theorem, integration techniques, improper integrals, applications. This is a seven week course. Close 
MA 115Calculus I (000)
(LectureLabStudy Hours)
An introduction to differential and integral calculus for functions of one variable. Begins with limits and continuity, and ends with integration techniques and applications of the definite integral. As of Fall 2012, MA 115 is replaced by the sequence MA 121 and MA 122. Close 
Close  4  0  8  2  MA 124  Calculus of Two VariablesPartial derivatives, the tangent plane and linear approximation, the gradient and directional derivatives, the chain rule, implicit differentiation, extreme values, application to optimization, double integrals in rectangular coordinates. This is a seven week course. Prerequisites:MA 123Series, Vectors, Functions, and Surfaces (408)
(LectureLabStudy Hours)
Taylor polynomials and series, functions of two and three variables, linear functions, implicit functions, vectors in two and three dimensions. This is a seven week course. Close 
Close  4  0  8  2  CAL 105 OR CAL 103  CAL Colloquium: Knowledge, Nature, CultureThis course introduces students to all the humanistic disciplines offered by the College of Arts and Letters: history, literature, philosophy, the social sciences, art, and music. By studying seminal works and engaging in discussions and debates regarding the themes and ideas presented in them, students learn how to examine evidence in formulating ideas, how to subject opinions, both their own, as well those of others, to rational evaluation, and in the end, how to appreciate and respect a wide diversity of opinions and points of view. Close OR Writing And Communications ColloquiumThis course empowers students with the written and oral communications skills essential for both universitylevel academic discourse as well as success outside Stevens in the professional world. Tailored to the Stevens student, styles of writing and communications include technical writing, business proposals and reports, scientific reports, expository writing, promotional documents and advertising, PowerPoint presentations, and team presentations. The course covers the strategies for formulating effective arguments and conveying them to a wider audience. Special attention is given to the skills necessary for professional document structure, successful presentation techniques and grammatical/style considerations. Close  3  0  6  3  PE 200  Physical Education II  0  0  0  0   Total  19  7  41  19 
 Term III  Course #  Course Name  Lecture  Lab  Study  Credit 

CS 334  Automata and ComputationIntroduction to recursive functional programming and equational reasoning; lists as inductive types and list induction; introduction to formal languages, automata, and the theory of computation; regular expressions, finite state machines, and pumping lemma; context free grammars and push down automata; turing machines, recursive enumerability, and unsolvable problems; and complexity and intractability. A number of models of computation are considered, as well as their relation to various problem classes (e.g. solvable problems and polynomial time solvable problems). Some experiments are performed that involve writing small Scheme programs. Prerequisites:CS 115, and Introduction to Computer Science (328)
(LectureLabStudy Hours)
This is an introduction to computer science with an emphasis on programming. The topics include: design; algorithmic thinking; recursion; objectoriented programming; ethics in computer science; and some basics about computer systems: machine language, interpreters, compilers, and data representation. Close 
CS 135Discrete Structures (328)
(LectureLabStudy Hours) The aim of this course is to integrate knowledge of basic mathematics with the problems involving specification, design, and computation. By the end of the course, the student should be able to: use sets, functions, lists, and relations in the specification and design of problems; use properties of arithmetic, modular arithmetic (sum, product, exponentiation), prime numbers, greatest common divisor, factoring, Fermat?s little theorem; use binary, decimal, and baseb notation systems and translation methods; use induction to design and verify recursive programs; and implement in Scheme all algorithms considered during the course. Close 
Close  3  0  0  3  CS 383  Computer Organization and ProgrammingThe main aspects of computers: data (data types and formats, number bases), hardware (stored program computer concept, addressing methods and program sequencing, instruction sets and their implementation, the CPU and microprogrammed control, input/output organization, peripherals and interfacing, and main memory), communication (network protocols), software (operating systems, dispatching algorithms), and assembly language programming. Corequisites:CS 181 or Introduction to Computer Science Honors I (320)(LectureLabStudy Hours) Getting acquainted with C++: data types, input and output, functions, writing simple C++ programs, flow control, Boolean expressions, decision statements, if/then, and switch/case. Loop operations, while, do/while, and for loops. Arrays and pointers. Defining structs and classes, constructors and destructors, and operator overloading using an example String class. Templates. Abstract data types: vectors, lists, stacks, queues, and priority trees with applications. Trees and simple sorting with searching algorithms. By invitation only. Students who complete this class are exempt from CS 115 and CS 284. Close 
CS 284Data Structures (228)(LectureLabStudy Hours) This is a course on standard data structures, including sorting and searching and using the Java language. The topics include: stages of software development; testing; UML diagrams; elementary data structures (lists, stacks, queues, and maps); use of elementary data structures in application frameworks; searching; sorting; and introduction to asymptotic complexity analysis. Close 
Prerequisites:CS 115Introduction to Computer Science (328)
(LectureLabStudy Hours)
This is an introduction to computer science with an emphasis on programming. The topics include: design; algorithmic thinking; recursion; objectoriented programming; ethics in computer science; and some basics about computer systems: machine language, interpreters, compilers, and data representation. Close 
Close  3  0  0  3  CS 385  AlgorithmsThis is a course on more complex data structures, and algorithm design and analysis, using the C language. Topics include: advanced and/or balanced search trees; hashing; further asymptotic complexity analysis; standard algorithm design techniques; graph algorithms; complex sort algorithms; and other "classic" algorithms that serve as examples of design techniques. Prerequisites:CS 181 or Introduction to Computer Science Honors I (320)
(LectureLabStudy Hours) Getting acquainted with C++: data types, input and output, functions, writing simple C++ programs, flow control, Boolean expressions, decision statements, if/then, and switch/case. Loop operations, while, do/while, and for loops. Arrays and pointers. Defining structs and classes, constructors and destructors, and operator overloading using an example String class. Templates. Abstract data types: vectors, lists, stacks, queues, and priority trees with applications. Trees and simple sorting with searching algorithms. By invitation only. Students who complete this class are exempt from CS 115 and CS 284. Close 
CS 284Data Structures (228)
(LectureLabStudy Hours) This is a course on standard data structures, including sorting and searching and using the Java language. The topics include: stages of software development; testing; UML diagrams; elementary data structures (lists, stacks, queues, and maps); use of elementary data structures in application frameworks; searching; sorting; and introduction to asymptotic complexity analysis. Close 
Close  4  0  8  4  CS 306  Intro to IT Security The course provides a basic introduction to the key concepts in security. It covers basic concepts such as authentication, confidentiality, integrity, and nonrepudiation as well as important techniques and applications. Topics include access control, security economics, ethics, privacy, software/operating system security, and security policies Close  3  0  0  3  HSS 371 OR HPL 455  Computers and SocietyAn introduction to arguments about the relationship between computing and society, the impact of computing activities on social relationships, and the evolution of institutions to regulate computermediated activities. Close OR Ethical Issues in Science and TechnologyConsideration of such issues as the ethical responsibility of scientists and technologists for the uses of their knowledge, the ethics of scientific research, and truth and fraud in science and engineering. We will study such contemporary moral questions as those concerning the uses and abuses of nuclear energy, environmental pollution and the preservation of natural resources, and the impact of new technologies on the right to privacy. Close  3  0  6  3  PE 200  Physical Education III  0  2  0  0   Total  16  2  14  16 
 Term IV  Course #  Course Name  Lecture  Lab  Study  Credit 

CS 392  Systems ProgrammingIntroduction to systems programming in C on UNIX. Students will be introduced to tools for compilation, dynamic linking, debugging, editing, automatic rebuilding, and version control. Some aspects of the UNIX system call interface will be studied, drawn from this list: process creation, signals, terminal I/O, file I/O, interprocess communication, threads, network protocol stacks, programming with sockets, and introduction to RPC. Style issues to be covered include: naming, layout, commenting, portability, design for robustness and debugability, and language pitfalls. X programming and GUI design will be covered, if time allows. Prerequisites:CS 182 or Introduction to Computer Science Honors II (400)
(LectureLabStudy Hours) Advanced programming concepts covering classical data structures and objectoriented programming. Emphasis will be on building a collection of reusable software components that will form the basis of future programming efforts. The data structures covered include lists, stacks, queues, trees, binary search trees, and balanced search trees. The objectoriented features of Java covered include classes, templates, inheritance, polymorphism and runtime binding. Also included is a discussion of the analysis of asymptotic running times of algorithms. Close 
CS 385Algorithms (408)
(LectureLabStudy Hours) This is a course on more complex data structures, and algorithm design and analysis, using the C language. Topics include: advanced and/or balanced search trees; hashing; further asymptotic complexity analysis; standard algorithm design techniques; graph algorithms; complex sort algorithms; and other "classic" algorithms that serve as examples of design techniques. Close 
Close  3  0  0  3  CS 496  Principles of Programming LanguagesAn introduction to programming language design and implementation, with an emphasis on the abstractions provided by programming languages. Assignments involve problemsolving issues in principles of programming languages such as Scheme and ML; recursive types and recursive functions; structural induction; abstract data types; abstract syntax; implementing languages with interpreters; static vs. dynamic scoping, closures, state; exceptions; types: typechecking, type inference, static vs. dynamic typing; objectoriented languages: classes and interfaces, inheritance and subtyping; polymorphism and genericity; and design patterns and the visitor pattern. Corequisites:CS 182 or Introduction to Computer Science Honors II (400)(LectureLabStudy Hours) Advanced programming concepts covering classical data structures and objectoriented programming. Emphasis will be on building a collection of reusable software components that will form the basis of future programming efforts. The data structures covered include lists, stacks, queues, trees, binary search trees, and balanced search trees. The objectoriented features of Java covered include classes, templates, inheritance, polymorphism and runtime binding. Also included is a discussion of the analysis of asymptotic running times of algorithms. Close 
CS 385Algorithms (408)(LectureLabStudy Hours) This is a course on more complex data structures, and algorithm design and analysis, using the C language. Topics include: advanced and/or balanced search trees; hashing; further asymptotic complexity analysis; standard algorithm design techniques; graph algorithms; complex sort algorithms; and other "classic" algorithms that serve as examples of design techniques. Close 
Prerequisites:CS 334Automata and Computation (300)
(LectureLabStudy Hours) Introduction to recursive functional programming and equational reasoning; lists as inductive types and list induction; introduction to formal languages, automata, and the theory of computation; regular expressions, finite state machines, and pumping lemma; context free grammars and push down automata; turing machines, recursive enumerability, and unsolvable problems; and complexity and intractability. A number of models of computation are considered, as well as their relation to various problem classes (e.g. solvable problems and polynomial time solvable problems). Some experiments are performed that involve writing small Scheme programs. Close 
Close  3  0  0  3  CS 347  Software Development ProcessThis course provides a general introduction to the essentials of the software development process, that series of activities that facilitate developing better software in less time. The course introduces software development and deployment life cycles, requirements acquisition and analysis, software architecture and design, and resource management and scheduling in the implementation phase. Students gain experience with tools and methodologies for configuration management and project management. Security engineering is considered as an essential part of the software development process, particularly from the standpoint of applied risk management. Prerequisites:CS 181 or Introduction to Computer Science Honors I (320)
(LectureLabStudy Hours) Getting acquainted with C++: data types, input and output, functions, writing simple C++ programs, flow control, Boolean expressions, decision statements, if/then, and switch/case. Loop operations, while, do/while, and for loops. Arrays and pointers. Defining structs and classes, constructors and destructors, and operator overloading using an example String class. Templates. Abstract data types: vectors, lists, stacks, queues, and priority trees with applications. Trees and simple sorting with searching algorithms. By invitation only. Students who complete this class are exempt from CS 115 and CS 284. Close 
CS 284, Data Structures (228)
(LectureLabStudy Hours) This is a course on standard data structures, including sorting and searching and using the Java language. The topics include: stages of software development; testing; UML diagrams; elementary data structures (lists, stacks, queues, and maps); use of elementary data structures in application frameworks; searching; sorting; and introduction to asymptotic complexity analysis. Close 
CS 135Discrete Structures (328)
(LectureLabStudy Hours) The aim of this course is to integrate knowledge of basic mathematics with the problems involving specification, design, and computation. By the end of the course, the student should be able to: use sets, functions, lists, and relations in the specification and design of problems; use properties of arithmetic, modular arithmetic (sum, product, exponentiation), prime numbers, greatest common divisor, factoring, Fermat?s little theorem; use binary, decimal, and baseb notation systems and translation methods; use induction to design and verify recursive programs; and implement in Scheme all algorithms considered during the course. Close 
Close  3  0  0  3  MA 222  Probability and StatisticsIntroduces the essentials of probability theory and elementary statistics. Lectures and assignments greatly stress the manifold applications of probability and statistics to computer science, production management, quality control, and reliability. Contents include: descriptive statistics, pictorial and tabular methods, and measures of location and of variability; sample space and events, probability axioms, and counting techniques; conditional probability and independence, and Bayes' formula; discrete random variables, distribution functions and moments, and binomial and Poisson distributions; continuous random variables, densities and moments, normal, gamma, and exponential and Weibull distributions unions; distribution of the sum and average of random samples; the Central Limit Theorem; confidence intervals for the mean and the variance; hypothesis testing and pvalues, and applications for the mean; simple linear regression, and estimation of and inference about the parameters; and correlation and prediction in a regression model. Prerequisites:MA 116 or Calculus II (408)
(LectureLabStudy Hours) Continues from MA 115 with improper integrals, infinite series, Taylor series, and Taylor polynomials. Vectors operations in 3space, mathematical descriptions of lines and planes, and singlevariable calculus for parametric curves. Introduction to calculus for functions of two or more variables including graphical representations, partial derivatives, the gradient vector, directional derivatives, applications to optimization, and double integrals in rectangular and polar coordinates. Close 
MA 124Calculus of Two Variables (408)
(LectureLabStudy Hours)
Partial derivatives, the tangent plane and linear approximation, the gradient and directional derivatives, the chain rule, implicit differentiation, extreme values, application to optimization, double integrals in rectangular coordinates. This is a seven week course. Close 
Close  3  0  6  3  HUM  Humanities 200 Level  3  0  6  3  PE 200  Physical Education IV  0  2  0  0   Total  15  2  12  15 
 Term V  Course #  Course Name  Lecture  Lab  Study  Credit 

CS 503  Discrete Mathematics for CryptographyTopics include basic discrete probability, including urn models and random mappings; a brief introduction to information theory; elements of number theory, including the prime number theorem, the Euler phi function, the Euclidean algorithm, and the Chinese remainder theorem; and elements of abstract algebra and finite fields including basic fundamentals of groups, rings, polynomial rings, vector spaces, and finite fields. Carries credit toward the Applied Mathematics degree only when followed by CS 579. Recommended for highlevel undergraduate students. Prerequisites:MA 502 or Mathematical Foundations of Computer Science (300)
(LectureLabStudy Hours) This course provides the necessary mathematical prerequisites for the computer science master’s program and also serves as a foundation for further study in mathematics. The topics covered include prepositional calculus: predicates and quantifiers; elementary number theory and methods of proof; mathematical induction; elementary set theory; combinatorics; functions and relations; countability; recursion and Onotation. Applications to computer science are stressed. Close 
CS 135Discrete Structures (328)
(LectureLabStudy Hours) The aim of this course is to integrate knowledge of basic mathematics with the problems involving specification, design, and computation. By the end of the course, the student should be able to: use sets, functions, lists, and relations in the specification and design of problems; use properties of arithmetic, modular arithmetic (sum, product, exponentiation), prime numbers, greatest common divisor, factoring, Fermat?s little theorem; use binary, decimal, and baseb notation systems and translation methods; use induction to design and verify recursive programs; and implement in Scheme all algorithms considered during the course. Close 
Close  3  0  0  3  CS 442  Database Management SystemsIntroduction to the design and querying of relational databases. Topics include: relational schemas; keys and foreign key references; relational algebra (as an introduction to SQL); SQL in depth; EntityRelationship (ER) database design; translating from ER models to relational schemas and from relational schemas to ER models; functional dependencies; and normalization. Prerequisites:CS 182 or Introduction to Computer Science Honors II (400)
(LectureLabStudy Hours) Advanced programming concepts covering classical data structures and objectoriented programming. Emphasis will be on building a collection of reusable software components that will form the basis of future programming efforts. The data structures covered include lists, stacks, queues, trees, binary search trees, and balanced search trees. The objectoriented features of Java covered include classes, templates, inheritance, polymorphism and runtime binding. Also included is a discussion of the analysis of asymptotic running times of algorithms. Close 
CS 385Algorithms (408)
(LectureLabStudy Hours) This is a course on more complex data structures, and algorithm design and analysis, using the C language. Topics include: advanced and/or balanced search trees; hashing; further asymptotic complexity analysis; standard algorithm design techniques; graph algorithms; complex sort algorithms; and other "classic" algorithms that serve as examples of design techniques. Close 
Close  3  0  6  3  CS 443  Database PracticumIn this course students use skills developed in earlier courses to work in teams with clients on the development of software to be used by the clients or by the organizations for which they work. Potential clients include Stevens faculty, Stevens departments that provide services to students, notforprofit organizations, government agencies, and, on occasion, forprofit companies. Teams work with clients to iteratively develop GUIbased prototypes of software that will satisfy the clients’ needs (requirements engineering); they perform the analysis and design required before implementation begins, and, finally, they implement the software, and deploy it to the client’s site together with documentation required by the software’s users and maintainers. Prerequisites:CS 385, and Algorithms (408)
(LectureLabStudy Hours) This is a course on more complex data structures, and algorithm design and analysis, using the C language. Topics include: advanced and/or balanced search trees; hashing; further asymptotic complexity analysis; standard algorithm design techniques; graph algorithms; complex sort algorithms; and other "classic" algorithms that serve as examples of design techniques. Close 
CS 442Database Management Systems (306)
(LectureLabStudy Hours) Introduction to the design and querying of relational databases. Topics include: relational schemas; keys and foreign key references; relational algebra (as an introduction to SQL); SQL in depth; EntityRelationship (ER) database design; translating from ER models to relational schemas and from relational schemas to ER models; functional dependencies; and normalization.
Close 
Close  3  0  6  3  CS 576  Secure SystemsAttacks on computer systems have become part of everyday life. It is the goal of this class to teach a basic understanding of the possible security failures, as well as the protection mechanism. The class will cover an introduction to network and host security concepts and mechanisms; basic cryptographic algorithms and protocols; authentication and authorization protocols; access control models; common network (wired and wireless) attacks; typical protection approaches, including firewalls and intrustion detection systems; and operating systems and application vulnerabilites, exploits, and countermeasures. The class is designed for undergraduate, master's, and Ph.D. students. Those who take the class are expected to be able to program in C, have some basic knowledge of assembly language, and be familiar with network programming, as well as Unixlike operating systems. Corequisites:CS 577Cybersecurity Laboratory (300)(LectureLabStudy Hours) Cybersecurity Laboratory Theoretical foundations in cryptographic algorithms, cryptographic protocols, access control models, formal methods, security policy, etc. provide the necessary background to understand the realworld implications of cryptography and network security. This laboratory course is designed to provide students with a handson experience based on the theoretical knowledge they have acquired by taking other securityoriented courses. This handson experience is of great importance for future jobs in industry. The course will accomplish its goals through a number of inlab programming exercises. Topics covered include: basic cryptographic algorithms and protocols; authentication and authorization protocols; access control models; common network (wired and wireless) attacks; typical protection approaches including firewalls and intrustion detection systems; and operating systems and application vulnerabilites, exploits, and countermeasures. Close 
Prerequisites:CS 506, and Introduction to IT Security (300)
(LectureLabStudy Hours) This course provides a basic introduction to the key concepts in security. It covers basic concepts such as authentication, confidentiality, integrity, and nonrepudiation as well as important techniques and applications. Topics include access control, security economics, ethics, privacy, software/operating system security, and security policies. Close 
CS 182 or Introduction to Computer Science Honors II (400)
(LectureLabStudy Hours) Advanced programming concepts covering classical data structures and objectoriented programming. Emphasis will be on building a collection of reusable software components that will form the basis of future programming efforts. The data structures covered include lists, stacks, queues, trees, binary search trees, and balanced search trees. The objectoriented features of Java covered include classes, templates, inheritance, polymorphism and runtime binding. Also included is a discussion of the analysis of asymptotic running times of algorithms. Close 
CS 385 or Algorithms (408)
(LectureLabStudy Hours) This is a course on more complex data structures, and algorithm design and analysis, using the C language. Topics include: advanced and/or balanced search trees; hashing; further asymptotic complexity analysis; standard algorithm design techniques; graph algorithms; complex sort algorithms; and other "classic" algorithms that serve as examples of design techniques. Close 
CS 570 or Introduction to Programming, Data Structures, and Algorithms (300)
(LectureLabStudy Hours)
Introduction to programming, data structures, and algorithm design, using one or more modern imperative language9s), as chosen by the instructor. Students will learn: basic programming constructs, data types, advanced and/or balanced search trees; hashing; asymptotic complexity analysis; standard algorithm design techniques; graph algorithms; sort algorithms; and other "classic' algorithms that serve as examples of design techniques. Students will be given regular programming assignments. Close 
CS 590Algorithms (300)
(LectureLabStudy Hours) This is a course on more complex data structures, and algorithm design and analysis, using one or more modern imperative language(s), as chosen by the instructor. Topics include: advanced and/or balanced search trees; hashing; further asymptotic complexity analysis; standard algorithm design techniques; graph algorithms; complex sort algorithms; and other "classic" algorithms that serve as examples of design techniques. Close 
Close  3  0  0  3  CS 577  Cybersecurity LaboratoryCybersecurity Laboratory Theoretical foundations in cryptographic algorithms, cryptographic protocols, access control models, formal methods, security policy, etc. provide the necessary background to understand the realworld implications of cryptography and network security. This laboratory course is designed to provide students with a handson experience based on the theoretical knowledge they have acquired by taking other securityoriented courses. This handson experience is of great importance for future jobs in industry. The course will accomplish its goals through a number of inlab programming exercises. Topics covered include: basic cryptographic algorithms and protocols; authentication and authorization protocols; access control models; common network (wired and wireless) attacks; typical protection approaches including firewalls and intrustion detection systems; and operating systems and application vulnerabilites, exploits, and countermeasures.Corequisites:CS 576Secure Systems (300)(LectureLabStudy Hours)
Attacks on computer systems have become part of everyday life. It is the goal of this class to teach a basic understanding of the possible security failures, as well as the protection mechanism. The class will cover an introduction to network and host security concepts and mechanisms; basic cryptographic algorithms and protocols; authentication and authorization protocols; access control models; common network (wired and wireless) attacks; typical protection approaches, including firewalls and intrustion detection systems; and operating systems and application vulnerabilites, exploits, and countermeasures. The class is designed for undergraduate, master's, and Ph.D. students. Those who take the class are expected to be able to program in C, have some basic knowledge of assembly language, and be familiar with network programming, as well as Unixlike operating systems. Close 
Prerequisites:CS 506, and Introduction to IT Security (300)
(LectureLabStudy Hours) This course provides a basic introduction to the key concepts in security. It covers basic concepts such as authentication, confidentiality, integrity, and nonrepudiation as well as important techniques and applications. Topics include access control, security economics, ethics, privacy, software/operating system security, and security policies. Close 
CS 182 or Introduction to Computer Science Honors II (400)
(LectureLabStudy Hours) Advanced programming concepts covering classical data structures and objectoriented programming. Emphasis will be on building a collection of reusable software components that will form the basis of future programming efforts. The data structures covered include lists, stacks, queues, trees, binary search trees, and balanced search trees. The objectoriented features of Java covered include classes, templates, inheritance, polymorphism and runtime binding. Also included is a discussion of the analysis of asymptotic running times of algorithms. Close 
CS 385 or Algorithms (408)
(LectureLabStudy Hours) This is a course on more complex data structures, and algorithm design and analysis, using the C language. Topics include: advanced and/or balanced search trees; hashing; further asymptotic complexity analysis; standard algorithm design techniques; graph algorithms; complex sort algorithms; and other "classic" algorithms that serve as examples of design techniques. Close 
CS 570 or Introduction to Programming, Data Structures, and Algorithms (300)
(LectureLabStudy Hours)
Introduction to programming, data structures, and algorithm design, using one or more modern imperative language9s), as chosen by the instructor. Students will learn: basic programming constructs, data types, advanced and/or balanced search trees; hashing; asymptotic complexity analysis; standard algorithm design techniques; graph algorithms; sort algorithms; and other "classic' algorithms that serve as examples of design techniques. Students will be given regular programming assignments. Close 
CS 590Algorithms (300)
(LectureLabStudy Hours) This is a course on more complex data structures, and algorithm design and analysis, using one or more modern imperative language(s), as chosen by the instructor. Topics include: advanced and/or balanced search trees; hashing; further asymptotic complexity analysis; standard algorithm design techniques; graph algorithms; complex sort algorithms; and other "classic" algorithms that serve as examples of design techniques. Close 
Close  3  0  0  3   Total  15  0  12  15 
 Term VI  Course #  Course Name  Lecture  Lab  Study  Credit 

CS 488  Computer ArchitectureAn introduction to the functional level structure of modern pipelined processors and the empirical and analytic evaluation of their performance. Topics include: empirical and analytic techniques for measuring performance (use of various means, Amdahl's Law, and benchmarks); tradeoff analysis; principles of instruction set design and evaluation (memory addressing, operations, types and sizes of operands, instruction set encoding, CISC vs. RISC, and related compilation issues); pipelining (basics, data hazards, and control hazards); and memory systems. Corequisites:MA 222Probability and Statistics (306)(LectureLabStudy Hours) Introduces the essentials of probability theory and elementary statistics. Lectures and assignments greatly stress the manifold applications of probability and statistics to computer science, production management, quality control, and reliability. Contents include: descriptive statistics, pictorial and tabular methods, and measures of location and of variability; sample space and events, probability axioms, and counting techniques; conditional probability and independence, and Bayes' formula; discrete random variables, distribution functions and moments, and binomial and Poisson distributions; continuous random variables, densities and moments, normal, gamma, and exponential and Weibull distributions unions; distribution of the sum and average of random samples; the Central Limit Theorem; confidence intervals for the mean and the variance; hypothesis testing and pvalues, and applications for the mean; simple linear regression, and estimation of and inference about the parameters; and correlation and prediction in a regression model. Close 
Prerequisites:CS 383Computer Organization and Programming (300)
(LectureLabStudy Hours) The main aspects of computers: data (data types and formats, number bases), hardware (stored program computer concept, addressing methods and program sequencing, instruction sets and their implementation, the CPU and microprogrammed control, input/output organization, peripherals and interfacing, and main memory), communication (network protocols), software (operating systems, dispatching algorithms), and assembly language programming. Close 
Close  3  0  0  3  CS 492  Operating SystemsThe use and internals of modern operating systems. Lectures focus on internals whereas programming assignments focus on use of the operating system interface. Major topics include: the process concept; concurrency and how to program with threads; memory management techniques, including virtual memory and shared libraries; file system data structures; and I/O. Prerequisites:CS 383, Computer Organization and Programming (300)
(LectureLabStudy Hours) The main aspects of computers: data (data types and formats, number bases), hardware (stored program computer concept, addressing methods and program sequencing, instruction sets and their implementation, the CPU and microprogrammed control, input/output organization, peripherals and interfacing, and main memory), communication (network protocols), software (operating systems, dispatching algorithms), and assembly language programming. Close 
CS 392Systems Programming (300)
(LectureLabStudy Hours) Introduction to systems programming in C on UNIX. Students will be introduced to tools for compilation, dynamic linking, debugging, editing, automatic rebuilding, and version control. Some aspects of the UNIX system call interface will be studied, drawn from this list: process creation, signals, terminal I/O, file I/O, interprocess communication, threads, network protocol stacks, programming with sockets, and introduction to RPC. Style issues to be covered include: naming, layout, commenting, portability, design for robustness and debugability, and language pitfalls. X programming and GUI design will be covered, if time allows. Close 
Close  3  0  0  3  CS 578  Privacy in a Networked WorldIncreasing use of computers and networks in business, government, recreation, and almost all aspects of daily life has led to a proliferation of online sensitive data that, if used improperly, can harm the data subjects. As a result, concern about the ownership, control, privacy, and accuracy of these data has become a top priority. This course focuses on both the technical challenges of handling sensitive data and the policy and legal issues facing data subjects, data owners, and data users. This course is suitable for advanced undergraduate computer science majors, graduate students in computer science, and students in technology management or other majors with some computer science background. Course readings draw on a variety of sources, including both technical materials and the popular press.Prerequisites:CS 579 or Foundations of Cryptography (300)
(LectureLabStudy Hours) This course provides a broad introduction to cornerstones of security (authenticity, confidentiality, message integrity, and nonrepudiation) and the mechanisms to achieve them as well as the underlying mathematical basics. Topics include: block and stream ciphers, publickey systems, key management, certificates, publickey infrastructure (PKI), digital signature, nonrepudiation, and message authentication. Various security standards and protocols such as DES, AES, PGP, and Kerberos, are studied. Close 
CS 594 or Enterprise Security and Information Assurance (300)
(LectureLabStudy Hours) This course addresses the security of ebusiness and cyber environments from an endtoend perspective, including data center security and access security. The information security phases of inspection, protection, detection, reaction, and reflection are emphasized. Topics also include: server and application security, virtual local area networks (VLANs), secure access and financial transaction techniques, and backup and disaster recovery techniques. The course also reviews financial Electronic Data Interchange (EDI) and smart card security in banking applications, and describes how the business and financial risks associated with security are estimated and managed. The course includes a project and related lab experiments. Close 
CS 306 or Introduction to IT Security (310)
(LectureLabStudy Hours) This course provides a basic introduction to the key concepts in security. It covers basic concepts such as authentication, confidentiality, integrity, and nonrepudiation as well as important techniques and applications. Topics include access control, security economics, ethics, privacy, software/operating system security, and security policies.
Close 
CS 506Introduction to IT Security (300)
(LectureLabStudy Hours) This course provides a basic introduction to the key concepts in security. It covers basic concepts such as authentication, confidentiality, integrity, and nonrepudiation as well as important techniques and applications. Topics include access control, security economics, ethics, privacy, software/operating system security, and security policies. Close 
Close  3  0  0  3  CS 579  Foundations of CryptographyThis course provides a broad introduction to cornerstones of security (authenticity, confidentiality, message integrity, and nonrepudiation) and the mechanisms to achieve them as well as the underlying mathematical basics. Topics include: block and stream ciphers, publickey systems, key management, certificates, publickey infrastructure (PKI), digital signature, nonrepudiation, and message authentication. Various security standards and protocols such as DES, AES, PGP, and Kerberos, are studied.Prerequisites:CS 503, and Discrete Mathematics for Cryptography (300)
(LectureLabStudy Hours) Topics include basic discrete probability, including urn models and random mappings; a brief introduction to information theory; elements of number theory, including the prime number theorem, the Euler phi function, the Euclidean algorithm, and the Chinese remainder theorem; and elements of abstract algebra and finite fields including basic fundamentals of groups, rings, polynomial rings, vector spaces, and finite fields. Carries credit toward the Applied Mathematics degree only when followed by CS 579. Recommended for highlevel undergraduate students. Close 
CS 182 or Introduction to Computer Science Honors II (400)
(LectureLabStudy Hours) Advanced programming concepts covering classical data structures and objectoriented programming. Emphasis will be on building a collection of reusable software components that will form the basis of future programming efforts. The data structures covered include lists, stacks, queues, trees, binary search trees, and balanced search trees. The objectoriented features of Java covered include classes, templates, inheritance, polymorphism and runtime binding. Also included is a discussion of the analysis of asymptotic running times of algorithms. Close 
CS 385 or Algorithms (408)
(LectureLabStudy Hours) This is a course on more complex data structures, and algorithm design and analysis, using the C language. Topics include: advanced and/or balanced search trees; hashing; further asymptotic complexity analysis; standard algorithm design techniques; graph algorithms; complex sort algorithms; and other "classic" algorithms that serve as examples of design techniques. Close 
CS 570 or Introduction to Programming, Data Structures, and Algorithms (300)
(LectureLabStudy Hours)
Introduction to programming, data structures, and algorithm design, using one or more modern imperative language9s), as chosen by the instructor. Students will learn: basic programming constructs, data types, advanced and/or balanced search trees; hashing; asymptotic complexity analysis; standard algorithm design techniques; graph algorithms; sort algorithms; and other "classic' algorithms that serve as examples of design techniques. Students will be given regular programming assignments. Close 
CS 590Algorithms (300)
(LectureLabStudy Hours) This is a course on more complex data structures, and algorithm design and analysis, using one or more modern imperative language(s), as chosen by the instructor. Topics include: advanced and/or balanced search trees; hashing; further asymptotic complexity analysis; standard algorithm design techniques; graph algorithms; complex sort algorithms; and other "classic" algorithms that serve as examples of design techniques. Close 
Close  3  0  0  3  HUM  Humanities 300 Level  3  0  6  3   Total  15  0  6  15 
 Term VII  Course #  Course Name  Lecture  Lab  Study  Credit 

CS 425  Cybersecurity Capstone IUnder the guidance of a cybersecurity faculty member of the department, students will participate in a yearlong cybersecurity project. The project may be conducted in a number of ways, including as a cybersecurityonly project, as a project where the cybersecurity student is integrated into the senior capstone project of another discipline like CS, QF, ECE, or as a project where the cybersecurity student interacts in a consultant role with one or more senior capstone teams of another discipline. Prerequisites:CS 576, and Secure Systems (300)
(LectureLabStudy Hours)
Attacks on computer systems have become part of everyday life. It is the goal of this class to teach a basic understanding of the possible security failures, as well as the protection mechanism. The class will cover an introduction to network and host security concepts and mechanisms; basic cryptographic algorithms and protocols; authentication and authorization protocols; access control models; common network (wired and wireless) attacks; typical protection approaches, including firewalls and intrustion detection systems; and operating systems and application vulnerabilites, exploits, and countermeasures. The class is designed for undergraduate, master's, and Ph.D. students. Those who take the class are expected to be able to program in C, have some basic knowledge of assembly language, and be familiar with network programming, as well as Unixlike operating systems. Close 
CS 577Cybersecurity Laboratory (300)
(LectureLabStudy Hours) Cybersecurity Laboratory Theoretical foundations in cryptographic algorithms, cryptographic protocols, access control models, formal methods, security policy, etc. provide the necessary background to understand the realworld implications of cryptography and network security. This laboratory course is designed to provide students with a handson experience based on the theoretical knowledge they have acquired by taking other securityoriented courses. This handson experience is of great importance for future jobs in industry. The course will accomplish its goals through a number of inlab programming exercises. Topics covered include: basic cryptographic algorithms and protocols; authentication and authorization protocols; access control models; common network (wired and wireless) attacks; typical protection approaches including firewalls and intrustion detection systems; and operating systems and application vulnerabilites, exploits, and countermeasures. Close 
Close  3  0  0  3  CS 595  Information Security and the LawThis course examines every major aspect of the relationship between information security and the law, at a level suitable for information security specialists and senior managers who supervise information security operations. In the first phase, the course explores substantive legal principles relating to information security, with regard to both private and government interests. The second phase of the course explores information security operations as the repository of information that may be at issue in legal proceedings. Finally, the course concludes with a discussion of the balancing process required to promote information security in a system of ordered liberties, that is, with due respect for civil rights. Close  3  0  0  3  CS  Security Elective  3  0  3  3  CS  CS Elective  3  0  3  3  CS 511  Concurrent ProgrammingThe study of concurrency as it appears at all levels and in different types of computing systems. Topics include: models of concurrency; languages for expressing concurrency; formal systems for reasoning about concurrency; the challenges of concurrent programming; race conditions; deadlock; livelock and nondeterministic behavior; prototypical synchronization problems, such as readerswriters and dining philosophers; mechanisms for solution of these problems, such as semaphores, monitors, and conditional critical regions; important libraries for concurrent programming; message passing, both synchronous and asynchronous; and applications of multithreaded concurrent programming and parallel algorithms. Substantial programming required. Prerequisites:CS 590 or Algorithms (300)
(LectureLabStudy Hours) This is a course on more complex data structures, and algorithm design and analysis, using one or more modern imperative language(s), as chosen by the instructor. Topics include: advanced and/or balanced search trees; hashing; further asymptotic complexity analysis; standard algorithm design techniques; graph algorithms; complex sort algorithms; and other "classic" algorithms that serve as examples of design techniques. Close 
CS 385Algorithms (408)
(LectureLabStudy Hours) This is a course on more complex data structures, and algorithm design and analysis, using the C language. Topics include: advanced and/or balanced search trees; hashing; further asymptotic complexity analysis; standard algorithm design techniques; graph algorithms; complex sort algorithms; and other "classic" algorithms that serve as examples of design techniques. Close 
Close  3  0  6  3  CS 485  Societal Impact of Information TechnologiesStudents explore tradeoffs posed by modern information technologies such as the Internet, mining of personal data, web tracking, and surveillance systems. Also covered are major debates about how IT technologies should be harnessed to serve the greater good, such as: Internet governance, privacy vs. openness, and laws regarding intellectual property. Students will learn how actions undertaken in their daily lives as IT professionals may have broad consequences, both planned and unplanned. Students will learn how to identify and analyze these consequences and who may be affected by them. Student must be a senior computer science or cybersecurity major. Close  1  0  0  1   Total  16  0  12  16 
 Term VIII  Course #  Course Name  Lecture  Lab  Study  Credit 

CS 426  Cybersecurity Capstone IIContinuation of CS425. Prerequisites:CS 425Cybersecurity Capstone I (300)
(LectureLabStudy Hours) Under the guidance of a cybersecurity faculty member of the department, students will participate in a yearlong cybersecurity project. The project may be conducted in a number of ways, including as a cybersecurityonly project, as a project where the cybersecurity student is integrated into the senior capstone project of another discipline like CS, QF, ECE, or as a project where the cybersecurity student interacts in a consultant role with one or more senior capstone teams of another discipline. Close 
Close  3  0  0  3  CS  Security Elective  3  0  3  3   Free Elective  3  0  6  3  CS 521  TCP/IP NetworkingIntroduction to IP networking. Examination of all layers of the OSI stack. Detailed examination of the IP, ICMP, UDP, and TCP protocols. Basic concepts of network design: endtoend principle, routing, encapsulation, flow control, congestion control, and security. Detailed coverage of TCP. Some treatment of important Internet applications and services. Emphasis on network layer and above. Assignments focus on protocols and software. Prerequisites:CS 520 or Introduction to Operating Systems (300)
(LectureLabStudy Hours) The use and internals of modern operating systems. Lectures focus on internals, whereas programming assignments focus on use of the operating system interface. Major topics include: the process concept; concurrency and how to program with threads; memory management techniques, including virtual memory and shared libraries; file system data structures; and I/O. Close 
CS 492Operating Systems (300)
(LectureLabStudy Hours) The use and internals of modern operating systems. Lectures focus on internals whereas programming assignments focus on use of the operating system interface. Major topics include: the process concept; concurrency and how to program with threads; memory management techniques, including virtual memory and shared libraries; file system data structures; and I/O. Close 
Close  3  0  0  3   Humanities (1)  3  0  6  3   Total  15  0  15  15 
 