CS Course Guidesheet 2022-23 | Thomas J. Watson College of Engineering and Applied Science

PRINTER-FRIENDLY VERSION OF THE GUIDESHEETStudents with AP credit for GenEd courses and a strong CS background may take CS 120 and CS 140 in the first semester. Students without prior programming experience should take CS 110 in fall and either CS 120 or CS 140 in the spring. Please consult a CS advisor before attempting CS 120 and CS 140 together.

These suggested course tracks are based on undergraduate requirements from the class entering in the 2022-23 academic year. These are only suggestions, refer to the University Bulletin for the official requirements for each major.

For archived requirements refer to the University Bulletin. Select the desired year, then click Link to Resource under the heading View Online.

For more information on graduate-level requirements go here.

Credit Requirements

To receive the BS degree in computer science, students must earn a minimum of 126 credit hours, including transfer credits, with a minimum 2.0 (C) grade-point average in computer science major courses, and a minimum cumulative grade-point average of 2.0.

Of the minimum 126 semester credits:

A minimum of 60 credits must be in liberal arts and sciences courses.
A minimum of 40 credits must be earned in Computer Science Watson College.
A minimum of 45 credits must be completed at the 300-level or above.

Area Requirements

Communications - 8 Credits

One course that meets the Binghamton Univeristy General Education Composition requirement.

AND

CS 301 - Eth Soc & Global Issues Comput

Communications course with required writing and oral presentations. Understanding the local and global implications of computing in society, including ethical, legal, security and social issues. Developing professional skills related to computing, including effective communication and productive teamwork. Fostering an appreciation for continuing professional development. Should be taken at the same time as or before any junior-level Computer Science courses. Prerequisites: Any General Education "C" course, CS 101, and CS 210, and either CS 140 or CS 210 and may be taken concurrently (All prerequisites must have a grade of C- or better). Offered every semester. 4 credits Levels: Undergraduate

Humanities/Social Science Electives - 20 Credits

Science - 8 or 10 Credits

The total of the science and free elective credits should be 22 credits.

Select one of the following sequences:

BIOL 113 - Intro to Cell & Molecular Biol

Introductory Biology: Cell and molecular Biology. Survey of cell and molecular biology: biological macromolecules, cellular organization and metabolism, cell communication, cell differentiation, coding of genetic information, inheritance, gene expression and regulation, cell replication, biotechnology, as well as cellular and molecular aspects of animal physiology. Lecture and discussion. BIOL 113 and 114 may be taken in any order. Offered regularly. 4 credits. Levels: Undergraduate
BIOL 114 - Intro to Organisms & Pops Biol

Introductory Biology: Organisms and Populations. Survey of organismal and population biology; history of life; structure and physiology of plants and animals; homeostasis, integration, growth, ecology; animal behavior; evolution. Lecture and discussion. BIOL 113 and 114 may be taken in any order. Offered regularly. 4 credits. Levels: Undergraduate
BIOL 115 - Intro Biology Lab

Introductory research-based course organized around developing novel research hypotheses and executing studies and experiments to test those hypotheses. The course covers the complete scientific process: assessing literature, learning techniques for field- and lab-based data collection, collecting and analyzing data, and writing and sharing results. Course fee applies. Refer to the Schedule of Classes. Co-requisite or prerequisite of BIOL 113 or BIOL 114. Offered regularly. Levels: Undergraduate

CHEM 104 - General Chemistry I

Fundamentals of chemistry, including atomic structure, stoichiometry, chemical reactions, kinetic theory of gases, thermochemistry, chemical bonding, molecular geometry and bonding theories, as well as properties of liquids, solids, and solutions. This material provides the foundation for CHEM 105; together, CHEM 104 and CHEM 105 provide a thorough treatment of chemical principles. This course is recommended for pre‐health students and science majors (other than Chemistry and Biochemistry majors). Not open to students who have credit for CHEM 111, CHEM107 or CHEM 108. Offered regularly. 4 Credits. Levels: Graduate, Undergraduate
CHEM 105 - General Chemistry II

Thermochemistry and thermodynamics; equilibrium; chemical kinetics; electrochemistry; nuclear chemistry; descriptive inorganic, organic and biochemistry. This course is recommended for pre‐health students and science majors (other than Chemistry and Biochemistry majors). Prerequisite: CHEM 104 or equivalent. Not open to students who have credit for CHEM 111, CHEM107 or CHEM 108. Offered regularly. 4 credits. Levels: Undergraduate
CHEM 106 - General Chemistry Laboratory

Experiments designed to teach students basic laboratory skills and provide them with an authentic research experience in chemistry through a combination of lecture and laboratory sessions. This course is recommended for pre‐health students and science majors (other than Chemistry and Biochemistry majors). Co or Prerequisite: CHEM 104. Offered regularly. 2 credits. Course fee applies. Refer to the Schedule of Classes. Levels: Undergraduate

PHYS 131 - Gen. Physics I(Calculus Based)

A calculus based introduction to the basic concepts underlying physical phenomena, including kinematics, dynamics, energy, momentum, forces found in nature, rotational motion, angular momentum, simple harmonic motion, fluids, thermodynamics and kinetic theory. Lectures, discussion, demonstration, and laboratory. Pre or Co-requisites: high school trigonometry and algebra; AP calculus or MATH 224/225. Offered spring semester. 4 credits. Levels: Undergraduate
PHYS 132 - Gen. Physics II(Calculus Based

Mathematics - 20 Credits

MATH 224 - Differential Calculus
MATH 225 - Integral Calculus
MATH 226 - Integration Tech & Application

This is a 2-credit course covering the calculus of transcendental & inverse functions, L’Hospital’s Rule, integral techniques, improper integrals, calculus of parametric curves, and polar coordinates. Prerequisites: Math 225 with a grade of at least a C- or consent of instructor. 2 credits. Levels: Undergraduate
MATH 227 - Infinite Series

MATH 314 - Discrete Mathematics

MATH 330 - Number Systems

Careful discussion of the real numbers, the rational numbers and the integers, including a thorough study of induction and recursion. Countable and uncountable sets. The methodology of mathematics: basic logic, the use of quantifiers, equivalence relations, sets and functions. Methods of proof in mathematics. Training in how to discover and write proofs. Prerequisites: C or better in MATH 227 or MATH 230, or consent of instructor. Every semester. 4 credits. Levels: Undergraduate

AND

MATH 327 - Probability with Stat Methods

Development of probabilistic concepts in discrete and absolutely continuous cases. Classical combinatorial methods, independence, random variables, distributions, moments, transformations, conditioning, confidence intervals, estimation. Open to Watson School students only. Does not serve as a prerequisite for MATH 448 or for any actuarial science courses. Prerequisites: C- or better in MATH 227 or MATH 230, or consent of instructor. Every semester. 4 credits. Levels: Undergraduate

MATH 448 - Mathematical Statistics

Estimation, confidence intervals and hypothesis testing. Introduction to linear models, categorical data and nonparametric statistics. Students who obtain B- or better in this course can apply for the VEE Mathematical Statistics credits from Society of Actuaries. Prerequisites: C or better in MATH 447 and either MATH 314 or MATH 330, or consent of instructor. Every semester. 4 credits. Levels: Undergraduate

As well as one elective chosen from the following list.

MATH 304 - Linear Algebra
MATH 371 - Ordinary Diff. Equations

Ordinary differential equations from quantitative and qualitative point of view including existence and uniqueness theory, first and second order equations and higher order equations, systems of first order equations, Laplace transforms, series solutions methods. MATH 371 contains the topics of MATH 324 and includes additional topics of the theory of existence and uniqueness, and systems of linear equations. The topics are studied from a more advanced mathematical viewpoint than in MATH 324. Only one of Math 324 and Math 371 can be counted towards math minor. Prerquisites: C or better in both MATH 304 and MATH 330, or consent of instructor. Every semester. 4 credits. Levels: Undergraduate
MATH 381 - Graph Theory

Directed and undirected graphs, trees, connectivity, Eulerian and Hamiltonian graphs, planar graphs, coloring of graphs, graph parameters, optimization and graph algorithms. Prerequisites: C or better in both MATH 304 and either MATH 314 or MATH 330, or consent of instructor. Spring only. 4 credits. Levels: Undergraduate
MATH 386 - Combinatorics

Topics from among counting techniques, generating function and recurrence relations, pigeonhole principle, Ramsey's Theorem, Latin squares, combinatorial designs. Prerequisites: C or better in both MATH 304 and either MATH 314 or MATH 330, or consent of instructor. Fall only. 4 credits. Levels: Undergraduate
MATH 407 - Intro to the Theory of Numbers

Mathematics or Science Elective - 4 Credits

MATH 323 - Calculus III

Or a scince elective chosen from the courses that meet the General Education Labrotory Science requirement.

Free Electives - 12 or 14 Credits

The total of the science and free elective credits should be 22 credits.

At least four credits must be in liberal arts and science. At most one free elective in liberal arts and science may be taken pass/fail instead of a letter grade. At most 2 credits of activity/wellness may be used as free elective credit.

Computer Science - 52 Credits

CS 101 - Prof Skills Ethics & CS Trends

Introduction to and discussion of topics of interest to computer science majors: social, ethical and professional issues; university, school and department resources; current developments in computer science. Prerequisite: none. Offered in the Fall semester. 1 credit Levels: Undergraduate
CS 120 - Prog & Hardware Fundamentals

Introduction to the C programming language, including local and global variables, basic control structures, function calls, pointers and the stack; use of command-line C development environments and development tools such as gdb and make; assembly language connection to higher-level C; building blocks of the Von Neumann machine (ALU, registers, control unit, RAM, decoders, program counters) and the underlying basic logic elements; simple non-pipelined processor architectures. Supervised laboratory work involves programming in C and low-level languages, interfacing with hardware, and the design and simulation of small circuits and simplified microprocessors. Prerequisite MATH 225 that may be taken concurrently. CS 110, CS Majors may request a waiver from the Undergraduate Director based on prior programming experience (All prerequisites must have a grade of C- or better) Offered every semester. 4 credits Levels: Undergraduate
CS 140 - Prog with Obj & Data Struct

Assumes a foundation in procedural programming as covered in CS 110. Provides the foundations of software development using Java and the data structures provided by Java. Problem solving using object-oriented programming techniques is emphasized. Topics include primitive and reference data types, variables, expressions, assignment, functions/methods, parameters, selection, iteration, recursion, exception handling, generic linear data structures and maps, file types, file I/O, simple GUIs, programming to an interface, use of inheritance, javadoc documentation, and introduction to Java threads. Required laboratory provides supervised problem solving, programming using the command line as well as Eclipse or Netbeans development environments, code backup in a version control repository, debugging and JUnit testing techniques. Prerequisite: CS 110,CS Majors may request a waiver from the Undergraduate Director based on prior programming experience. Math 225 (All prerequisites must have a grade of C- or better). Offered every semester. 4 credits Levels: Undergraduate
CS 220 - Arch from a Prog Perspective

The architecture and programming of computer systems. Data representation and computer arithmetic. Processor and memory organization. Assembly and machine language programming. Advanced C programming language constructs and their implementation in assembly language. Introduction to system software (assemblers, linkers, loaders, compilers). Supervised laboratory work involves programming and debugging using machine language, assembly language and C. Prerequisite: CS 120 and CS 140 (All prerequisites must have a grade of C- or better). Offered every semester. 4 credits Levels: Undergraduate
CS 240 - Data Struct & Algorithms

Analysis of the design, implementation, and properties of basic and advanced data structures, including lists, stacks, queues, hash tables, trees, heaps, and graphs. Design and time-space analysis of basic and advanced algorithms, including searching, sorting, insert/delete, hash table collision resolution techniques, recursive functions, balanced tree maintenance, and graph algorithms. Weekly required laboratory programming and three or more additional programming projects in C++. Practical programming techniques including C++ templates and the Standard Template Library (STL), operator overloading, C++ stream I/O, separate compilation using makefiles, debugging tools and techniques, dynamic memory management. Prerequisites: CS 120 and CS 140, and either MATH 226 (may be taken concurrently) OR MATH 230 (All prerequisites must have a grade of C- or better). Offered every semester. 4 credits Levels: Undergraduate
CS 320 - Advanced Computer Architecture

Performance metrics and analysis; instruction set architecture and its implications; high-performance computer arithmetic; instruction pipelines and pipelined datapath implementation; out-of-order execution, register renaming, branch prediction and superscalar processors; caches and memory systems; memory hierarchy; the I/O subsystem; reliable storage systems; introduction to multicore and multithreaded architectures; hardware and architectural support for security. Required lab includes programming projects. Prerequisite: CS 220 (All prerequisites must have a grade of C- or better). Offered every semester. Credits 4 Levels: Undergraduate
CS 350 - Operating Systems

Introduction to the design and implementation of operating systems: hardware/software interface; processes and threads; CPU scheduling; virtual memory; memory management; concurrency, race conditions, deadlocks, and synchronization; file and storage systems; input/output; protection and security; virtualization and hypervisors; multi-processor operating systems. Required lab includes programming exercises and presentations. Prerequisites: CS 220 and either CS 240 (All prerequisites must have a grade of C- or better). Prerequisite (May be taken concurrently.): CS 301. Offered every semester. 4 credits. Levels: Undergraduate
CS 373 - Automata Theory & Formal Lg.

Theory and application of automata and the languages they recognize. Regular languages, deterministic and non-deterministic finite automata, regular expressions, context-free languages, context-free grammars, pushdown automata, normal forms, context-sensitive languages, linear bounded automata, Turing recognizable languages, Turing decidable languages, Turing machines, computability, decidability, reducibility. Students will utilize an automata simulator to program finite automata, pushdown automata, and Turing machines. Application of concepts. Required activity includes student presentations. Prerequisites: CS 140 and either MATH 314 or MATH 330 (All prerequisites must have a grade of C- or better). Offered every semester 4 credits Levels: Undergraduate
CS 375 - Design & Analysis of Algorithm

Analysis of common algorithms for processing strings, trees, graphs and networks. Comparison of sorting and searching algorithms. Algorithm design strategies: divide and conquer, dynamic, greedy, back tracking, branch and bound. Introduction to NP-completeness. Required activity includes student presentations. Prerequisites: CS 240, MATH 227 and MATH 314 or MATH 330, CS 301 (may be taken concurrently). (All prerequisites must have a grade of C- or better). Offered every semester. 4 credits Levels: Undergraduate
CS 471 - Programming Languages

Introduction to the design and implementation of programming languages: linguistic features for expressing algorithms; formal syntax specification; introduction to language semantics and parsing; declarative programming (functional and goal-driven); scripting languages; imperative programming (procedural and object-oriented); comparative design and implementation issues across languages and paradigms. Assignments emphasize languages such as Prolog, Haskell, Python, and Ruby. Required lab includes student presentations. Prerequisites: CS 373 and 375 (All prerequisites must have a grade of C- or better). Offered every semester. 4 credits Levels: Undergraduate

At least 15 credits of Computer Science electivesmust be chosen, and at least one course must be chosen from each of the areas A, B, and C. Courses in multipl areas count as meeting all the areas indicated. Courses from D and E are optional. At most, one course can be taken from E.

A: Networking and Communications

CS 426 - Internet of Things

This course covers the applied area of Internet of Things (IoT). IoT are pervasive computing systems consisting of smart sensors embedded in physical environments with many promising applications. IoT challenge many classical approaches to computing and networking. Students will learn about key techniques in IoT through this course. A substantial part of the material will cover wireless sensor networks, embedded operating systems, and network protocols. A variety of different IoT applications will be introduced, including clinical monitoring, structural health monitoring, and industrial process automation. In this course, students will also have an opportunity to obtain hands-on experience on programming embedded devices to sense and communicate. Prerequisite: Either CS 320 Advanced Computer Architecture or CS350 Operating Systems (All prerequisites must have a grade of C- or better) Term offered varies. 4 credits. Levels: Undergraduate
CS 427 - Mobile Systems Security

This course discusses cybersecurity issues in various aspects of mobile systems, including mobile networks, mobile communications, mobile OSes, mobile applications, and mobile devices. It presents technical details of how mobile systems work and explains their vulnerabilities with potential security risks. The course uses a combination of real-world mobile devices and high-fidelity emulation testbeds to demonstrate common types of attacks in mobile systems as well as how to defend against these attacks. In this course, students are expected to gain hands-on experiences with mobile systems and learn basic techniques to tackle their cybersecurity problems. Prerequisite: CS 350 Operating Systems, or equivalents, CS 375 Design and Analysis of Algorithms. Term offered varies. 4 credits. Levels: Undergraduate
CS 428 - Computer Networks

Communication protocols and layering, hardware-software infrastructures for networking, MAC protocols, data link protocols, switching, inter- and intra-domain routing, the TCP/IP protocol suite, transport protocols, application layer protocols, local and system area networks, wireless and sensor networks, overlay and virtual networks, client-server and peer-to-peer models, network programming with sockets, protocol design and implementation issues, network security. Prerequisite: CS 350 (All prerequisites must have a grade of C- or better). Term offered varies. 4 credits. Levels: Undergraduate
CS 440 - Adv Topics - Obj Oriented Prog

Object-oriented programming and its concomitant design patterns provide rich abstractions for program development. These programs will eventually execute on real hardware, however. This course will investigate advanced object-oriented techniques and how they interact with hardware and operating system issues. We will ground our topics in C++, but the goal of the course will be to develop understanding that can be applied across languages. We will examine different design techniques for things such as memory management, and explore how and why they differ in performance and robustness. We will also cover idioms such as ""Resource Acquisition Is Initialization"" (RAII) and how they can be used to provide robust resource management for exceptions (exception safety). We will also devote time to covering generic programming and related topics such as expression templates. This is a growing area that seeks to decouple algorithms and data structures through the use of templates and other meta-programming techniques. These techniques exploit the fact that the C++ template mechanism is a language-within-a-language that is executed at compile-time rather than run-time. Additional topics include dynamic linking for techniques such as ""plug-ins"", template instantiation mechanisms, template specialization, idioms for memory management, thread-safety issues, thread-safety, C++ reflection. Prerequisites: CS 240 and CS 350. Term offered varies. 4 credits. Levels: Undergraduate
CS 442 - Design Patterns

Patterns for program design including examples of patterns used in existing software libraries. Exercises in programming with design patterns and communicating designs to other programmers using the language of patterns. Use of an object-oriented programming language to implement patterns and principles for common design problems. Design patterns are applied to problems involving features including concurrency, sockets, streams, reflection, and dynamic proxies. The course also discusses automating software build processes with build tools. Prerequisites: CS 140 or CS 210 and CS 375 (All prerequisites must have a grade of C- or better). Term offered varies. 4 credits Levels: Undergraduate
CS 444 - Programming for the Web

An in-depth understanding of programming for the World Wide Web: detailed coverage of widely used language(s) for web programming, asynchronous programming, principles of web architecture, web protocols, web design patterns, client-side programming, templating, server-side programming, a technical history of the web, web security. Students are expected to have experience with a modern programming language and will be assigned programming projects using current state-of- the-art web technologies. Prerequisite: either CS 140 or CS 210 and, CS 320 or CS 350 or CS 375. (All prerequisites must have a grade of C- or better) Term offered varies. 4 credits Levels: Undergraduate
CS 447 - High Performance Computing

This course covers the applied area of high performance computing for machine learning, big data, and scientific computing. Students will learn about techniques for programs where the amount of computation is substantial enough that performance is a major concern. A substantial part of the material will cover parallel computation, including message-passing, multicore, and vectorization. A variety of different algorithms and applications will be considered, including machine learning, big data, and more traditional scientific computing. Prerequisite: CS 220, CS 240, either CS 320 or CS350 (All prerequisites must have a grade of C- or better). Term offered varies. 4 Credits Levels: Undergraduate
CS 451 - Systems Programming

A detailed study of the application program interface of a modern operating system. File operations, concurrency, processes, threads, inter-process communication, synchronization, client-server programming, multi-tier programming. Prerequisite: CS 350 (All prerequisites must have a grade of C- or better). Term offered varies. 4 credits Levels: Undergraduate
CS 452 - Intro to Cloud Computing

This course will provide students with topics in cloud computing with coverage of core cloud components such as virtualization techniques, distributed systems, cloud service models, and representative cloud computing systems. It will not only include the in-depth study of the fundamental enabling techniques such as server, network, and data storage virtualization, but also provide the demonstration of how these techniques work inside today’s widely-used cloud-based systems such as MapReduce, key-value stores, and Openstack. The course will include weekly assignments in the form of homework, labs, and projects. Prerequisite: CS 350. Term offered varies. 4 credits. Levels: Undergraduate
CS 457 - Intro To Distributed Systems

Fundamental issues in distributed systems. Distributed synchronization and concurrency control. Distributed process management (scheduling, remote invocation, task forces, load balancing). Protection and security. Robust distributed systems. Case studies. Prerequisites: CS 350 (All prerequisites must have a grade of C- or better). Term offered varies. 4 credits Levels: Undergraduate
CS 458 - Intro to Computer Security

The course provides an introduction to the principles and practices of network, computer, and information security. Topics include authentication and cryptographic techniques, intrusion detection, access control, security policies, and program/policy analysis techniques. Prerequisites: CS 350 and CS 375 (All prerequisites must have a grade of C- or better). Term offered varies. 4 credits Levels: Undergraduate

B: Large Software Development

CS 428 - Computer Networks

Communication protocols and layering, hardware-software infrastructures for networking, MAC protocols, data link protocols, switching, inter- and intra-domain routing, the TCP/IP protocol suite, transport protocols, application layer protocols, local and system area networks, wireless and sensor networks, overlay and virtual networks, client-server and peer-to-peer models, network programming with sockets, protocol design and implementation issues, network security. Prerequisite: CS 350 (All prerequisites must have a grade of C- or better). Term offered varies. 4 credits. Levels: Undergraduate
CS 432 - Database Systems

Associations between data elements and data models: entity-relationship, relational and object-oriented. Relational database design techniques. Formal and commercial query languages. Introduction to query processing, transaction management and concurrency control. Prerequisite: CS 375 (All prerequisites must have a grade of C- or better). Term offered varies. 4 credits Levels: Undergraduate
CS 433 - Information Retrieval

Indexing and data structures for storing and searching the index. Boolean, statistical, inference nets and knowledge-based models. Thesaurus construction. Query expansion. Natural language and linguistic techniques. Evaluation. Distributed information retrieval. Information integration and fusion. Dissemination of information. Summaries, themes and reading tours. Hypertext. Internet tools. Intelligent agents. Digital libraries. Prerequisite: CS 375 (All prerequisites must have a grade of C- or better). Term offered varies. 4 credits Levels: Undergraduate
CS 440 - Adv Topics - Obj Oriented Prog

Object-oriented programming and its concomitant design patterns provide rich abstractions for program development. These programs will eventually execute on real hardware, however. This course will investigate advanced object-oriented techniques and how they interact with hardware and operating system issues. We will ground our topics in C++, but the goal of the course will be to develop understanding that can be applied across languages. We will examine different design techniques for things such as memory management, and explore how and why they differ in performance and robustness. We will also cover idioms such as ""Resource Acquisition Is Initialization"" (RAII) and how they can be used to provide robust resource management for exceptions (exception safety). We will also devote time to covering generic programming and related topics such as expression templates. This is a growing area that seeks to decouple algorithms and data structures through the use of templates and other meta-programming techniques. These techniques exploit the fact that the C++ template mechanism is a language-within-a-language that is executed at compile-time rather than run-time. Additional topics include dynamic linking for techniques such as ""plug-ins"", template instantiation mechanisms, template specialization, idioms for memory management, thread-safety issues, thread-safety, C++ reflection. Prerequisites: CS 240 and CS 350. Term offered varies. 4 credits. Levels: Undergraduate
CS 442 - Design Patterns

Patterns for program design including examples of patterns used in existing software libraries. Exercises in programming with design patterns and communicating designs to other programmers using the language of patterns. Use of an object-oriented programming language to implement patterns and principles for common design problems. Design patterns are applied to problems involving features including concurrency, sockets, streams, reflection, and dynamic proxies. The course also discusses automating software build processes with build tools. Prerequisites: CS 140 or CS 210 and CS 375 (All prerequisites must have a grade of C- or better). Term offered varies. 4 credits Levels: Undergraduate
CS 444 - Programming for the Web

An in-depth understanding of programming for the World Wide Web: detailed coverage of widely used language(s) for web programming, asynchronous programming, principles of web architecture, web protocols, web design patterns, client-side programming, templating, server-side programming, a technical history of the web, web security. Students are expected to have experience with a modern programming language and will be assigned programming projects using current state-of- the-art web technologies. Prerequisite: either CS 140 or CS 210 and, CS 320 or CS 350 or CS 375. (All prerequisites must have a grade of C- or better) Term offered varies. 4 credits Levels: Undergraduate
CS 447 - High Performance Computing

This course covers the applied area of high performance computing for machine learning, big data, and scientific computing. Students will learn about techniques for programs where the amount of computation is substantial enough that performance is a major concern. A substantial part of the material will cover parallel computation, including message-passing, multicore, and vectorization. A variety of different algorithms and applications will be considered, including machine learning, big data, and more traditional scientific computing. Prerequisite: CS 220, CS 240, either CS 320 or CS350 (All prerequisites must have a grade of C- or better). Term offered varies. 4 Credits Levels: Undergraduate
CS 451 - Systems Programming

A detailed study of the application program interface of a modern operating system. File operations, concurrency, processes, threads, inter-process communication, synchronization, client-server programming, multi-tier programming. Prerequisite: CS 350 (All prerequisites must have a grade of C- or better). Term offered varies. 4 credits Levels: Undergraduate
CS 455 - Intro to Visual Info Processin

The course focuses on fundamental topics, including visual information acquisition, representation, description, enhancement, restoration, transformations and compressions, and reconstruction from projections. The second focus is on Computer Science applications, including algorithms developed in applications such as statistical and syntactic pattern recognition, robotic vision, multimedia indexing, visual data mining, and bio-informatics. Prerequisite: CS 375 (All prerequisites must have a grade of C- or better). Term offered varies. 4 credits Levels: Undergraduate
CS 457 - Intro To Distributed Systems

Fundamental issues in distributed systems. Distributed synchronization and concurrency control. Distributed process management (scheduling, remote invocation, task forces, load balancing). Protection and security. Robust distributed systems. Case studies. Prerequisites: CS 350 (All prerequisites must have a grade of C- or better). Term offered varies. 4 credits Levels: Undergraduate
CS 460 - Computer Graphics

Concepts, structure, techniques and algorithms for use of modern interactive computer graphics systems. Graphics hardware, software system structure. Techniques and algorithms for basic graphics input/output functions. Matrix techniques for transformations and projections. Techniques for two- and three-dimensional modeling, rendering, animation and visualization. Prerequisite: CS 375 (All prerequisites must have a grade of C- or better). Prerequisite or Corequisite: MATH 304. Term offered varies. 4 credits Levels: Undergraduate
CS 472 - Compiler Design

Fundamentals of programming language translation. Compiler design concepts. General aspects of lexical analysis and parsing of context-free languages. Grammars and parsing techniques. Syntax-directed translation. Declarations and symbol management. Semantic processing and code generation. Principles, methods and examples of code optimization. Prerequisite: CS 373 and CS 375 (All prerequisites must have a grade of C- or better). Term offered varies. 4 credits Levels: Undergraduate

C: Data and Information Management

CS 415 - Social Media Data Sci Pipeline

The focus of this course is on applying data science techniques to large-scale social media. The topics covered include large-scale data collection and management, exploratory analysis and measurement techniques, hypothesis testing and statistical modeling, and predictive, real time analytics. Students will build an end-to-end analysis pipeline and use it to answer questions about online events as they occur. The goal of the class is to provide students with a methodological toolbox, the technical skills to make use of these tools, and the experience of using them on real world data. Prerequisite: CS 350 Operating Systems, CS 375 Design & Analysis Algorithm, MATH 327 Probability with Stat Methods or equivalent. (All prerequisites must have a grade of C- or better) Term offered varies. 4 credits. Levels: Undergraduate
CS 432 - Database Systems

Associations between data elements and data models: entity-relationship, relational and object-oriented. Relational database design techniques. Formal and commercial query languages. Introduction to query processing, transaction management and concurrency control. Prerequisite: CS 375 (All prerequisites must have a grade of C- or better). Term offered varies. 4 credits Levels: Undergraduate
CS 433 - Information Retrieval

Indexing and data structures for storing and searching the index. Boolean, statistical, inference nets and knowledge-based models. Thesaurus construction. Query expansion. Natural language and linguistic techniques. Evaluation. Distributed information retrieval. Information integration and fusion. Dissemination of information. Summaries, themes and reading tours. Hypertext. Internet tools. Intelligent agents. Digital libraries. Prerequisite: CS 375 (All prerequisites must have a grade of C- or better). Term offered varies. 4 credits Levels: Undergraduate
CS 435 - Introduction To Data Mining

Basic topics of data mining, including data preprocessing, mining association rules, classification rules, clustering rules, post processing and mining in unstructured data. Prerequisites: CS 375, MATH 304 and MATH 327 or MATH 448 (All prerequisites must have a grade of C- or better). Term offered varies. 4 credits Levels: Undergraduate
CS 436 - Intro to Machine Learning

This course provides a broad introduction to machine learning and its applications. Major topics include: supervised learning (generative/discriminative learning, parametric/non-parametric learning, support vector machines); computational learning theory (bias/variance tradeoffs, VC theory, large margins); unsupervised learning; semi-supervised learning; reinforcement learning. The course will give students the basic ideas and intuition behind different techniques as well as a more formal understanding of how and why they work. The course will also discuss recent applications of machine learning, such as to data mining, bioinformatics, and information retrieval. Prerequisites: CS 375 and MATH 327 or MATH 448 (All prerequisites must have a grade of C- or better). Term offered varies. 4 credits Levels: Undergraduate
CS 455 - Intro to Visual Info Processin

The course focuses on fundamental topics, including visual information acquisition, representation, description, enhancement, restoration, transformations and compressions, and reconstruction from projections. The second focus is on Computer Science applications, including algorithms developed in applications such as statistical and syntactic pattern recognition, robotic vision, multimedia indexing, visual data mining, and bio-informatics. Prerequisite: CS 375 (All prerequisites must have a grade of C- or better). Term offered varies. 4 credits Levels: Undergraduate
CS 465 - Intro to Artificial Intelligen

This course will cover the basic ideas and techniques underlying the design of artificial intelligence (AI) agents. Topics include search, knowledge representation (and reasoning), planning, reasoning under uncertainty, machine learning (including reinforcement learning), and applications (natural language processing, vision, robotics, etc). Prerequisite: CS 375 (All prerequisites must have a grade of C- or better) Term offered varies. 4 credits. Levels: Undergraduate

D: Other Courses

CS 424 - Intelligent Mobile Robotics

The focus of this course is on intelligent mobile robots that can autonomously operate in indoor environments with limited human guidance. The topics covered in this course include mapping, localization, navigation, planning, reasoning, and human-robot interaction (language-based and vision-based). The students will learn to develop software in Robot Operating System (ROS) on real mobile robots. The goal of this course is to help students learn entry level algorithms and programming skills that are required to conduct research in the area of intelligent mobile robotics. Prerequisite: CS 350, CS 375. (All prerequisites must have a grade of C- or better) Term offered varies. 4 credits. Levels: Undergraduate Restrictions: Must be enrolled in one of the following Majors: Computer Science
CS 441 - Game Dev For Mobile Platforms

This course focuses software development for mobile computing platforms, such as smartphones and tables, with an emphasis on games. Students will develop interactive applications, and utilize the wide variety of sensors and networking features available on the platform, along with basic elements of graphics programming and animation. The course also covers the mechanics of distributing software for mobile computing platforms. Both iOS and Android operating systems will be covered. The course will feature a mix of individual and team projects. Prerequisite: CS 140 , CS 375. (All prerequisites must have a grade of C- or better). Term offered varies. 4 credits. Levels: Undergraduate
CS 445 - Software Engineering

Software engineering practice applied to the life cycle of software applications and engineering projects. Software project planning and management: risk management, estimation, scheduling, trade studies, CM and SQA. Software development: process model selection, domain analysis, requirements gathering, analysis and design modeling, user interface design, architectural and detailed design, documentation, testing strategies/methods, test plan generation, and reuse. Advanced topics include formal methods and cleanroom software engineering. Requires a major team project. Prerequisites: CS 350 or CS 375 (All prerequisites must have a grade of C- or better). Term offered varies. 4 credits Levels: Undergraduate
CS 453 - Software Security

This hands-on course covers offensive and defensive technologies in the area of software security. Particularly, students will learn about various vulnerabilities that lead to software compromise, attacks that exploit such vulnerabilities, and defenses that defend against such attacks. Topics covered include simple control-flow corruption attacks, slightly harder buffer overflow and return-to-libc attacks, and advanced ROP attacks. Students are expected to not only learn the concepts behind each attack, but also execute them in a controlled environment. Prerequisite: CS350 Operating Systems (All prerequisites must have a grade of C- or better) Term offered varies. 4 credits Levels: Undergraduate
CS 456 - Intro to Computer Vision

Course has two parts. Part one focuses on an introduction to the fundamental topics of computer vision, including low-level vision, intermediate-level vision, high-level vision, vision systems, visual knowledge representation, motion analysis, shape from shading and 3D reconstruction, as well as image retrieval. Part two introduces the applications of the fundamental computer vision techniques. Examples include robotic vision, pattern recognition and medical imaging. Pre req CS 375 (All prerequisites must have a grade of C- or better). 4 credits Levels: Undergraduate
CS 459 - Science of Cyber Security

This course focuses on techniques that approach cyber security problems in a principled manner using concepts from data mining, game theory, graph theory, and psychology. The intent of this course is to permit students to bridge the divide between real-world cyber threats and formal, scientific foundations of solutions that address such threats. Real-world cyber security issues, such as spamming, phishing attacks, malware, sybil attacks in social networks, and DDoS attacks, are used to illustrate how cyber threats can be modeled with abstract representations that are amenable to rigorous analysis and formal reasoning. The course also emphasizes the development of cyber defense mechanisms that are rooted in scientific foundations. Prerequisite: CS 350 and CS 375 (All prerequisites must have a grade of C- or better). Term offered varies. 4 credits. Levels: Undergraduate

CS-480 any approved topics course, prequisites will vary by course.

Any future approved CS 400-level course will count as area D and other areas as is appropriate.

E: Internship, Co-op, Research

To count as a CS elective, courses in this area must be taken for a total of 3 credits.

CS 395. Computer Science Internship. Prerequisites: CS 220, 240, junior or senior standing and CS Department approval
CS 396. Computer Science Co-op. Prerequisites: CS 220, 240, junior or senior standing and CS Department approval
CS 499. Undergraduate Research. Prerequisites vary by research area. Requires junior or senior standing, supervision by a Computer Science faculty
member, and completion of CS Department approval form.

General Education Requirements

Students must fulfill the General Education Requirements for Computer Science. Students normally complete these requirements within the 126-credit program described above.

Supplemental information regarding the BSCS Degree Requirements

The following information supplements that provided in the University Bulletin. It applies to students who matriculated Fall 2016 or after.

All required Computer Science courses, except CS 101, are offered every semester. The minimum grade in a required Computer Science course must be at least a C- to be allowed to take any Computer Science course, for which it is a prerequisite.

Calculus Topics are broken down as follows:

MATH 224 - Differential Calculus
MATH 225 - Integral Calculus
MATH 226 - Integration Tech & Application

This is a 2-credit course covering the calculus of transcendental & inverse functions, L’Hospital’s Rule, integral techniques, improper integrals, calculus of parametric curves, and polar coordinates. Prerequisites: Math 225 with a grade of at least a C- or consent of instructor. 2 credits. Levels: Undergraduate
MATH 227 - Infinite Series

Humanities/Social Science – May be filled by courses offered by the Division of Humanities, the Division of Social Sciences, the Psychology Department and HDEV courses offered by the College of Community and Public Affairs. Many of the courses taken to meet the General Education requirements will fulfill the Humanities/Social Science requirement.

Mathematics - Students who are strong in math are encouraged to take MATH 330 (Number Systems) instead of MATH 314 (Discrete Mathematics). Students with a strong math background may take MATH 381 (Graph Theory) as their Math elective. The following Binghamton University course can be substituted for MATH 327: MATH 448 (Mathematical Statistics), which has a prerequisite of MATH 323 and MATH 447.

Free Electives – May be filled by extra courses from any of the areas listed above, SOM courses, or additional Computer Science courses. A maximum of 2 HWS credits may be counted as Free Elective credits. At least four free elective credits must be in Liberal Arts and Science in order to ensure the 60 credits needed for a BS degree. CS 110 counts as a free elective.

Prerequisites for Computer Science Courses

The MATH and CS pre-requisites must have a grade of at least C-.

CS 101: None
CS 110: MATH 225
CS 120: CS 110, MATH 225
CS 140: CS 110, MATH 225
CS 220: CS 120, 140
CS 240: CS 120, 140, MATH 226
CS 301: CS 101, Gen Ed C/J course, CS 220 or 240
CS 320: CS 220
CS 350: CS 220, 240, 301
CS 373: CS 140, MATH 314 or 330
CS 375: CS 240, MATH 227, 314 or 330, CS 301
CS 402: CS 220, 240
CS 415: CS 350, 375, MATH 327 or 448
CS 424: CS 350, 375
CS 426: CS 320 or 350
CS 428: CS 350
CS 432: CS 375
CS 433: CS 375
CS 435: CS 375, MATH 304, 327 or 448
CS 436: CS 375, MATH 327 or 448
CS 440: CS 240, 350
CS 441: CS 140, 375
CS 442: CS 140, 375
CS 444: CS 320 or 350 or 375
CS 445: CS 350 or 375
CS 447: CS 22, 240, 320 or 350
CS 451: CS 350
CS 452: CS 350
CS 453: CS350
CS 455: CS 375
CS 456:
CS 457: CS 350
CS 458: CS 350, 375
CS 459: CS 375, MATH 327 or 448
CS 460: CS 375
CS 465: CS 375
CS 471: CS 373, 375
CS 472: CS 373, 375
CS 476: CS 140, 320, 350