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Penn - Prerequisite(s): CSE 120, 121, 260, 262 . How do you optimally encode a text file? How do you find shortest paths in a map? How do you desgin a communication network? How do you route data in a network? What are the limits of efficient computation? Thi s course gives a comprehensive introduction to design and analysis of algorithms, and answers along the way to thes e and many other interesting computational questions. You will learn about problem-solving; advanced data structure s such as universal hashing and red-black trees; advanced design and analysis techniques such as dynamic programmin g and amortized analysis; graph algorithms such as minimum spanning trees and network flos; NP-completeness theory ; and approximation algorithms .

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Penn - Prerequisite(s): CSE 121 and 260 . Introduction to database management systems and principles of design. The Entity-Relationship model as a modelin g tool. The relational model: formal languages, the industry standard SQL, relational design theory, query optimization . Storing and querying XML data. Datalog and recursive queries. Views and data integration. Overview of system leve l issues: physical data organization, indexing techniques, and transactions. Connecting databases to the Web. Cours e work requires programming in several different query languages, several written homeworks and a team project .

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Penn - Prerequisite(s): CSE 320 . Can you check if two large documents are identical by examining a small number of bits? Can you verify that a program has correctly computed a function without ever computing the function? Can students compute the averag e score on an exam without ever revealing their scores to each other? Can you be convinced of the correctness of a n assertion without ever seeing the proof? The answer to all these questions is in the affirmative provided we allow th e use of randomization. Over the past few decades, randomization has emerged as a powerful resource in algorith m desgin. This course would focus on powerful general techniques for designing randomized algorithms as well a s specific representative applications in various domains, including approximation algorithms, cryptography and numbe r theory, data structure design, online algorithms, and parallel and distributed computation . 340. Problem Solving and Programming. (M) Prerequisite(s): CSE 120, 121 . This course is about the principles of programmng languages. It studies programming language concepts b y implementing a sequence of interpreters, compilers, and type checkers, each one introducing a new language concept . The goal of this course is threefold: By studying the concepts and abstractions of high-level programming languages , students should be able to use them more effectively. Second, by learning how the features of high-level programmin g languages are implemented, students should be able to program more expressively in low-level languages. Finally, b y understanding the principles behind programming language design, students should be able to create, evaluate an d compare programming languages .

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Penn - Prerequisite(s): Two semesters of programming courses, e.g., CSE 120-121 , and CSE 240 . You know how to program, but do you know how to write programs that understand and generate other programs ? This is the focus of CSE 341. In addition to traditinal programming language implementation topics (such as lexing , parsing, grammars, symbol tables, code generation, optimization, garbage collection, and object-oriente d implementation), this course also explores the more general problem of reasoning about computation (e.g., fo r detecting bugs or security constraint violations). CSE 341 includes a substantial and rewarding Java programmin g project to develop a fully operational compiler for a Java-like object oriented programming language .

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Penn - Prerequisite(s): CSE 240 . Large systems versus small programs. Problems of scale. Software life-cycle: design phase, implementation phase , testing, maintenance. Software re-use. Tools/Toolkits/Libraries. Programming as a group activity. Support tools, e.g. , SCCS and RCS. Standards. Software readability and structure. Reading code. Style sheets. Software Testing: role i n process, test cases, testers. Documentation. Embedded documentation and external documentation . 371. Computer Organization and Design Lab. (B) Prerequisite(s): CIS 240 . This is the second computer oganization course and focuses on computer hardware design. Topics covered are: (1 ) basic digital system design including finite state machines, (2) instruction set design and simple RISC assembl y programming, (3) quantitative evaluation of computer performance, (4) circuits for integer and floating-poin t arithmatic, (5) datapath and control, (6) micro-programming, (7) pipeling, (8) storage hierarchy and virtual memory, (9 ) input/output, (10) different forms of parallelism including instruction level parallelism, data-level parallelism usin g both vectors and message-passing multi-processors, and thread-level parallelism using shared memory multiprocessors . Basic cache coherence and synchronization .

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Penn - Corequisite(s): CSE 371 . Laboratory for CSE 371. In this laboratory section, students gain experience with digital design techniques b y designing and implementing actual circuits using Verilog HDL and FPGAs. Five assignments culminate in the desig n and simulation of a complete 16-bit integer pipelined CPU .

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Penn - Prerequisite(s): CSE 240 or EE 300 . This course surveys methods and algorithms used in modern operating systems. Concurrent distributed operation i s emphasized. The main topics covered are as follows: process synchronization; interprocess communication ; concurrent/distributed programming languages; resource allocation and deadlock; virtual memory; protection an d security; distributed operation; distributed data; performance evalaution .

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Penn - Corequisite(s): CSE 380. This course is a semester long project to design and implement your own operating system. Typical components include a process management system, a commond interpreter, and a file management system.

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Penn - Prerequisite(s): MATH 240, PHYS 150 or MEAM 110/147 . The rapidly evolving field of robotics includes systems designed to replace, assist, or even entertain humans in a wid e variety of tasks. Recent examples include planetary rovers, robotic pets, medical surgical-assistive devices, and semi autonomous search-and-rescue vehicles. This introductory-level course presents the fundamental kinematic, dynamic , and computational principles underlying most modern robotic systems. The main topics of the course include : coordinate transformations, manipulator kinematics, mobile-robot kinematics, actuation and sensing, feedback control , vision, motion planning, and learning. The material is reinforced with hands-on lab exercises including basic robot - arm control and the programming of vision-guided mobile robots .

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Penn - Prerequisite(s): CSE 121 and CSE 262; CSE 341 strongl y recommended . Artificial Intelligence is considered from the point of view of a resource--limited knowledge-based agent who mus t reason and act in the world. Topics include logic, automatic theorem proving, search, knowledge representation an d reasoning, natural language processing, probabilistic reasoning, and machine learning. Programming assignments i n Prolog and C++ or Java .

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Penn - Prerequisite(s): CSE 260, 262 and Math 240 . The purpose of this course is to introduce undergraduate students in computer computer science and engineering t o quantum computers (QC) and quantum information science (QIS). This course is meant primarly for juniors an d seniors in CSE. No prior knowledge of quantum mechanics (QM) is assumed. Enrollment is by permission of th e instructor . 400. Senior Project. (A) Prerequisite(s): Senior standing or permission of instructor . The goal of the senior design coruse is to provide students with an opportunity to define, design and execute a significant project. Project subjects may revolve around software, hardware or computational theory. Students mus t have an abstract of their Senior Project, which is approved and signed by a Project Advisor early in the Fall semester . The project is expected to span two semesters; students must enroll in CSE 401 during the second semester. At the en d of the first semester, students are required to submit an intermediate report and give a presentation describing thei r project and progress. Grades are based on technical writing skills (as per submited report) presentation skills and progress on the project. These are evaluated by the Project Adviser and the Course Instructor.

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Penn - Prerequisite(s): CSE 400, senior standing or permission of instructor. Continuation of CSE 400. Design and implementation of a significant piece of work: software, hardware or theory. Students are required to submit a final written report and give a final presentation and demonstration of their project. Grades are based on the report, the presentation and the satisfactory completion of the project. These are evaluated b y the Project Adviser and the Course Instructor .

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Penn - The course introduces mathematical and algorithmic techniques for geometric modeling with applications to computer graphics and computer animation. The course covers implicit and parametric curves; implicit and parametric surfaces; polygonal surfaces; polygonal surface simplification, decomposition, and parametrization; and surface reconstruction from point sets.

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Penn - Prerequisite(s): CIS 121. Automatic summarization can help alleviate the information overload problem caused by the unprecedented amount of online textual information. The building of a summarization system requires good understanding of the properties of human language and the use of various natural language tools. In this course we will build several summarization systems of increasing complexity and sophistication. In the process we will learn about various natural language processing tools and resources such as part of speech tagging, chunking, parsing, Wordnet, and machine learning toolkits. We will also cover probability and statistics concepts used in summarization, but also applicable to a wide range of other language-related tasks.

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Penn - This course is a pragmatic introduction to parallel and distributed programming. It targets science and engineering students with basic programming skills, and prepares them for parallelizing existing sequential programs or optimizing the perfomrance of existing parallel codes. The course teaches how to program with widely used parallel programming interfaces such as Pthread, MPI, OpenMP, HPFaand RMI. In addition, the course covers enough information on common parallel architectures, so that the students can optimize the programs for different platforms.

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Penn - Prerequisite(s): CIS 330, CIS 380 recommended. This course focuses on Internet and Web technologies and the underlying principles of distributed systems, information retrieval, and data management. The material covered will include web and application server architecturs, SML and semistructured data, schema mediation, document indexing and retrieval, peer-to-peer systems, distributed transactions and remote procedure calls. The course has a substantial group implementation project.

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Penn - Prerequisite(s): One year programming experience (C, JAVA, C++). A thorough introduction to computer graphics techniques, covering primarily 3D modeling and image synthesis. Topics cover: geometric transformations, geometric algorithms, software systems (OpenGL), 3D object models (surface and volume), visible surface algorithms, image synthesis, shading and mapping, ray tracing, radiosity, global illumination, photon mapping, anti-aliasing and compositing.

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Penn - Prerequisite(s): CSE 120, 121 or equivalent experience and concurrent or past enrollment in CSE 460/560. This project-based course is designed to provide a comprehensive introduction to the application of computer graphics in a laboratory setting. Course materials and labs will facilitate understanding issues and trends in 3D computer graphics. Students will develop a facility with fundamental 3-D models and modeling software through a series of projects. The course will offer students a technical understanding of Polygonal and Spline based modeling, alternative and standard methods of 3-D model import and export, and model conversion. It will also cover procedural and scripting methods, techniques, and conventions for creating models and shaders that will function properly for rendering and animation. Practical application of topics covered in CSE 460/560 include; geometric transformations, hierarchies, articulation, modeling, blend shaps, vertex weighting, and animation. Experiments with various animation methods inlcude: dynamics, forward and inverse kinematics, surface deformations, keyframe interpolation, motion capture, procedural animation, and facial animation. The course will be laboratory based and will use industry standard software.

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Penn - Prerequisite(s): Previous exposure to major concepts in linear algebra (i.e. vector matrix math), curves and surfaces, dynamical systems (e.g. 2nd order mass-spring-damper systems) and 3D computer graphics has also been assumed in the preparation of the course materials. This course covers core subject matter common to the fields of robotics, character animation and embodied intelligent agents. The intent of the course is to provide the student with a solid technical foundation for developing, animating and controlling articulated systems used in interactive computer games, virtual reality simulations and high-end animation applications. The course balances theory with practice by "looking under the hood" of current animation systems and authoring tools and examines the technolgies and techniques used from both a computer science and engineering perspective. Topics covered include: geometric coordinate systems and transformations; quaternions; parametric curves and surfaces; forward and inverse kinematics; dynamic systems and control; computer simulation; keyframe, motion capture and procedural animation; behavior-based animation and control; facial animation; smart characters and intelligent agents.

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Penn - Prerequisite(s): PHIL 006 or instructor's permission . Basic concepts of set theory, relations and functions, properties of relations. Basic concepts of algebra. Grammars , languages, and automata- finite state grammars, regular expressions, context-free and context-sensitive grammars , unrestricted grammars, finite automata, pushdown automata and other related automata, Turing machines, Syntax an d semantics of grammar formalisms. Strong generative capacity of grammars, Grammers as deductive systems, parsin g as deduction. Relevance of formal gammars to modeling biological sequences. The course will deal with these topic s in a very basic and introductory manner--ideas of proofs and not detailed proofs, and more importantly with plenty o f linguistic examples to bring out the linguistic relevance of these topics . The course will deal with these topics in a very basic and introductory manner--ideas of proofs and not detailed proofs, and more importantly with plenty of linguistic examples to bring out the linguistic relevance of these topics.

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Penn - Prerequisite(s): CIS 380, some network programming experience is desirable. Ever increasing availability of inexpensive processors connected by a communication network has motivated the development of numerous concepts and paradigms for distributed real-time embedded systems. The primary objectives of this course are to study the principles and concepts of real-time embedded computing and to provide students hands-on experience in developing embedded applications. This course covers the concepts and theory necessary to understand and program embedded real-time systems. This includes concepts and theory for real-time system design, analysis, and certification; programming and operating systems for embedded systems; and concepts, technologies, and protocols for distributed embedded real-time systems. The course will cover a variety of existing systems and technologies, e.g., real- machines, architectural description anguage, formal meth and logical-time programming paradigms, and certification The course requires active student participation in-group projects. Each group will be responsible for the design and implementation of a life-critical embedded system such as a pacemaker. The group projects are intended to complement the learning of principles and concepts through the application of theory in practice and the development of experimental skills in building embedded applications.

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Penn - Prerequisite(s): CSE 260. Logic has been called the calculus of computer science as it plays a fundamental role in computer science, similar to that played by calculus in the physical sciences and traditional engineerng disciplines. Indeed, logic is useful in areas of computer science as disparate as architecture (logic gates), software engineerng (specification and verification), programming languages (semantics, logic programming), databases (relational algebra and SQL), artificial intelligence (automatic theorem proving), algorithms (complexity and expressiveness), and theory of computation (general notions of computability). CSE 482 provides the students with a thorough introduction to mathematical logic, covering in depth the topics of syntax, semantics, decision procedures, formal proof systems, and soundness and completeness for both propositional and first-order logic. The material is taught froma computer science perspective, with an emphasis on algorithms, computational complexity, and tools. Projects will focus on problems in circuit design, specification and analysis and protocols, and query evaluation in databases. COMPUTER & INFORMATION SCIENCE (CIS) Graduate Courses

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Penn - Prerequisite(s): Undergraduate-level course in programming languages or compilers; significant programming experience. This course introduces basic concepts and techniques in the foundational study of programming languages. The central theme is the view of individual programs and whole languages as mathematical objects about which precise claims may be made and proved. Particular topics include operational techniques for formal definition of language features, type systems and type safety properties, polymorphism and subtyping, foundations of object-oriented programming, and mechanisms supporting information hiding and programming in the large. L/R

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Penn - Prerequisite(s): Knowledge of computer organizaiton and basic programming skills. This course is an introductory graduate course on computer architecture with an emphasis on a quantitative approach to cost/performance design tradeoffs. The course covers the fundamentals of classical and modern uniprocessor design: performance and cost issues, instruction sets, pipelining, superscalar, out-of-order, and speculative execution mechanisms, caches, physical memory, virtual memory, and I/O. Other topics include: static scheduling, VLIW and EPIC, software speculation, long (SIMD) and short (multimedia) vector execution, multithreading, and an introduction to shared memory multiprocessors.

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Penn - Prerequisite(s): CIT 594 or equivalent . An investigation of several major algorithms and their uses in areas including list manipulation, sorting, searching , selection and graph manipulation. Efficiency and complexity of algorithms. Compexity Classes .

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