Courses
Courses primarily for undergraduates:
Cr. R. F.S.
Introduction to the procedures and policies of Iowa State University and the Department of Computer Science, test-outs, honorary societies, etc. Issues relevant to student adjustment to college life will also be discussed.
Offered on a satisfactory-fail basis only.
Cr. 4. F.S.SS.
Introduction to computer literacy and applications. Applications: Windows, Internet browser/HTML, word processing, spreadsheets, database management and presentation software. Literacy: history of computing, structure of computers, telecommunications, computer ethics, computer crime, and history of programming languages. No prior computer experience necessary. Course is offered online only. Students must attend an orientation session the first week of class.
(1.5-1) Cr. 2. F.S.
Offered first 8 weeks and last 8 weeks. Use of personal computer and workstation operating systems and beginning programming. Project-oriented approach to computer operation and programming, including use of tools to aid in programming. Topics from computer history, using basic Windows and Unix tools, program structure, expression, variables, decision and logic, and iteration. No prior computer experience necessary.
Cr. 2. F.S.
Prereq: COM S 104
8-week course in programming, including instruction in syntax and semantics, of the following current programming languages.
(1-2) Cr. 2. F.S.
Prereq: COM S 104
8-week course in programming using Perl.
(2-0) Cr. 2. F.S.
Prereq: COM S 104
8-week course in programming using MATLAB.
(3-0) Cr. 3. S.
Introduction to Web programming basics. Fundamentals of developing Web pages using a comprehensive Web development life cycle. In-depth experience with current Web design techniques such as HTML5 and cascading style sheets. Programming strategies for accessibility, usability and search engine optimization.
(3-0) Cr. 3. F.S.
Introduction to computer programming for non-majors using a language such as the Visual Basic language. Basics of good programming and algorithm development. Graphical user interfaces.
(3-0) Cr. 3. F.S.
Prereq: COM S 107 or equivalent
Advanced programming applications in Visual Basic for non-majors. Emphasis on programming projects including sorting, file processing, database processing, web programming, and graphics and animation. Students will learn problem solving techniques and advanced programming skills to build real-world applications.
(2-2) Cr. 3. F.S.SS.
Using Microsoft Excel spreadsheets and Microsoft Access databases to input, store, process, manipulate, query, and analyze data for business and industrial applications.
Credit in Com S 113 may not be applied toward graduation in the COM S, S E, and CPR E majors. Only one of COM S 103 and COM S 113 may count toward graduation.
(3-0) Cr. 3. SS.
Computer programming in COBOL. Emphasis on the design, writing, debugging, and testing of business applications programs in a transaction-oriented environment.
Cr. R. F.S.
Computer science as a profession. Introduction to career fields open to computer science majors. Relationship of coursework to careers. Presentations by computer science professionals.
Offered on a satisfactory-fail basis only.
(Cross-listed with MIS). (3-1) Cr. 3. F.S.
Prereq: MATH 150 or placement into MATH 140/MATH 141/MATH 142 or higher
An introduction to computer programming using an object-oriented programming language. Emphasis on the basics of good programming techniques and style. Extensive practice in designing, implementing, and debugging small programs. Use of abstract data types. Interactive and file I/O. Exceptions/error-handling. This course is not designed for computer science, software engineering, and computer engineering majors.
Credit may not be applied toward graduation for both Com S 207/MIS 207 and Com S 227.
(3-1) Cr. 3. S.
Prereq: MIS/COM S 207, credit or enrollment in MATH 151, MATH 160, or MATH 165
Intermediate-level programming techniques. Emphasis on designing, writing, testing, debugging, and documenting medium-sized programs. Data structures and their uses. Dynamic memory usage. Inheritance and polymorphism. Algorithm design and efficiency: recursion, searching, and sorting. Event-driven and GUI programming. The software development process. This course is not designed for computer science, software engineering and computer engineering majors.
Credit may not be applied toward the major in computer science, software engineering, or computer engineering.
(3-2) Cr. 4. F.S.
Prereq: Placement into MATH 143, 165, or higher; recommended: a previous high school or college course in programming or equivalent experience.
Introduction to object-oriented design and programming techniques. Symbolic and numerical computation, recursion and iteration, modularity procedural and data abstraction, and specifications and subtyping. Object-oriented techniques including encapsulation, inheritance and polymorphism. Imperative programming. Emphasis on principles of programming and object-oriented design through extensive practice in design, writing, running, debugging, and reasoning. Course intended for Com S majors.
Credit may not be applied toward graduation for both Com S 207 and 227.
(3-1) Cr. 3. F.S.
Prereq: Minimum of C- in 227, credit or enrollment in MATH 165
An object-oriented approach to data structures and algorithms. Object-oriented analysis, design, and programming, with emphasis on data abstraction, inheritance and subtype polymorphism. Abstract data type specification and correctness. Collections and associated algorithms, such as stacks, queues, lists, trees. Searching and sorting algorithms. Graphs. Data on secondary storage. Analysis of algoritms. Emphasis on object-oriented design, writing and documenting medium-sized programs. This course is designed for majors.
(3-0) Cr. 3. F.
Prereq: COM S 107 or COM S 207 or COM S 227
Introduction to installation, utilization, and administration of Linux systems. Topics include open-source software, package installation and management, shell programming and command-line utilities, process and service management, account management, network configuration, file sharing, interoperation with other computers and operating systems, automation, and system security.
Cr. arr. F.S.
Prereq: Permission of instructor
Offered on a satisfactory-fail basis only.
Cr. arr. F.S.
Prereq: Permission of instructor
Offered on a satisfactory-fail basis only.
(3-1) Cr. 3. F.S.
Prereq: Minimum of C- in COM S 228
A practical introduction to methods for managing software development. Process models, requirements analysis, structured and object-oriented design, coding, testing, maintenance, cost and schedule estimation, metrics. Programming projects.
(3-1) Cr. 3. F.S.
Prereq: Minimum of C- in COM S 228; MATH 166, ENGL 150, and COM S 230 or CPR E 310
Basic techniques for design and analysis of efficient algorithms. Sorting, searching, graph algorithms, computational geometry, string processing and NP-completeness. Design techniques such as dynamic programming and the greedy method. Asymptotic, worst-case, average-case and amortized analyses. Data structures including heaps, hash tables, binary search trees and red-black trees. Programming projects.
(Cross-listed with S E). (3-0) Cr. 3. F.
Prereq: COM S 228
Basic theory of grammars, parsing. Language paradigms. State transition and table-based software design. Review of principles of object orientation, object oriented analysis using UML. Frameworks and APIs. User interface architecture, evaluation of user interface. Design of windows, menus, and commands. Introduction to formal specification and model-based software design. Introduction to domain-specific software engineering.
(3-0) Cr. 3. F.S.
Prereq: COM S 228, credit or enrollment in MATH 166.
Object-oriented programming experience using a language suitable for exploring advanced topics in programming. Topics include memory management, parameter passing, inheritance, compiling, debugging, and maintaining programs. Significant programming projects.
(Cross-listed with LING). (3-1) Cr. 3. F.S.
Prereq: Minimum of C- in COM S 228, MATH 166, and in COM S 230 or CPR E 310; ENGL 250
Models of computation: finite state automata, pushdown automata and Turing machines. Study of grammars and their relation to automata. Limits of digital computation, unsolvability and Church-Turing thesis. Chomsky hierarchy and relations between classes of languages.
(3-0) Cr. 3. F.
Prereq: COM S 327, CoReq MATH 207 or MATH 317
Basic algorithms, design, and programming of interactive computer graphics systems and hardware. Topics include 2D and 3D transformations, 3D viewing, visible surface algorithms, collision detection, illumination models, shading, ray tracing, shadows, transparency and texture mapping.
(Cross-listed with S E). (3-1) Cr. 3. F.S.
Prereq: Minimum of C- in COM S 228, COM S 230 or CPR E 310
Study of concepts in programming languages and major programming paradigms, especially functional programming. Special emphasis on design tradeoffs that enable students to make sound choices of programming languages for a given software development task. Programming projects.
(3-1) Cr. 3. F.S.
Prereq: COM S 321, and COM S 327; ENGL 250
Survey of operating system issues. Introduction to hardware and software components including: processors, peripherals, interrupts, management of processes, threads and memory, deadlocks, file systems, protection, virtual machines and system organization, and introduction to distributed operating systems. Programming projects.
(3-0) Cr. 3. F.S.
Prereq: Minimum of C- in COM S 228; ENGL 250
Relational, object-oriented, and semistructured data models and query languages. SQL, ODMG, and XML standards. Database design using entity-relationship model, data dependencies and object definition language. Application development in SQL-like languages and general purpose host languages with application program interfaces. Information integration using data warehouses, mediators and wrappers. Programming Projects.
Cr. R.
Prereq: Permission of department chair
Required of all cooperative students. Students must register for this course prior to commencing each work period.
Cr. 2-3. Repeatable. F.S.
Students work as individuals and teams to complete the planning, design, and implementation of a significant project in the topic area. Oral and written reports.
(0-4) Cr. 2. Repeatable. F.S.
Prereq: COM S 402A
Students implement, test, and present a completed production computer game. Students in this class will work with students in ARTIS 409. Oral and written reports.
(0-6) Cr. 3. Repeatable. F.
Students work as individuals and teams to complete the planning, design, and implementation of a significant project in the topic area. Oral and written reports.
(Dual-listed with COM S 509). (Cross-listed with S E). (3-0) Cr. 3. F.
Prereq: COM S 309
The requirements engineering process including identification of stakeholders requirements elicitation techniques such as interviews and prototyping, analysis fundamentals, requirements specification, and validation. Use of Models: State-oriented, Function-oriented, and Object-oriented. Documentation for Software Requirements. Informal, semi-formal, and formal representations. Structural, informational, and behavioral requirements. Non-functional requirements. Use of requirements repositories to manage and track requirements through the life cycle. Case studies, software projects, written reports, and oral presentations will be required.
(Dual-listed with COM S 510). (3-0) Cr. 3. F.
Prereq: COMS 228, COMS 309, COMS 327
Team with students at foreign universities to develop a software application. Importance of distributed development. Design for distributed development, effective processes for distributed development, and cultural issues in distributed development, organizing for distributed development, communication techniques and skills for distributed development,including oral presentations. Graduate credit requires in-depth study of concepts.
(Dual-listed with COM S 512). (Cross-listed with CPR E, S E). (3-0) Cr. 3. S.
Prereq: COM S 230 or CPR E 310; COM S 311, STAT 330
A study of formal techniques for model-based specification and verification of software systems. Topics include logics, formalisms, graph theory, numerical computations, algorithms and tools for automatic analysis of systems. Graduate credit requires in-depth study of concepts.
(Dual-listed with COM S 514). (3-0) Cr. 3. F.
Prereq: COM S 227 or (COM S 207 or GERON 377 or ARTGR 271) or equivalent.
An interdisciplinary course designed for students who are interested in assistive technology, pervasive computing, mobile computing and principles of universal and inclusive design for end users, in particular, the elderly population. Students will work in semester-long projects as interdisciplinary teams to apply knowledge obtained from lectures and mutual presentations. For graduate credit students are required to submit a research report and give an oral presentation.
(Dual-listed with COM S 515). (3-0) Cr. 3. S.
Prereq: COM S 309 or COM S 311, COM S 342
An introduction to the analysis, design, and testing of software for safety-critical and high-integrity systems. Analysis techniques, formal verification, fault identification and recovery, model checking, and certification issues. Emphasizes a case-based and systematic approach to software's role in safe systems.
(Cross-listed with S E). (3-0) Cr. 3. S.
Prereq: COM S 309; COM S 230 or CPR E 310; ENGL 250, SP CM 212
Comprehensive study of software testing, principles, methodologies, management strategies and techniques. Test models, test design techniques (black box and white box testing techniques), test adequacy criteria,integration, regression, system testing methods, and software testing tools.
(Dual-listed with COM S 518). (3-0) Cr. 3. Alt. S., offered odd-numbered years.
Prereq: COM S 311 or permission of instructor
Introduction to data structures, algorithms, and analysis techniques for computational problems that involve geometry. Line segment intersection, polygon triangulation, 2D linear programming, range queries, point location, arrangements and duality, Voronoi diagrams and Delaunay triangulation, convex hulls, robot motion planning, visibility graphs. Other selected topics. Programming assignments.
(Cross-listed with MATH). (3-0) Cr. 3. S.
Prereq: MATH 301 or MATH 207 or MATH 317 or COM S 230
Propositional and predicate logic. Topics selected from Horn logic, equational logic, resolution and unification, foundations of logic programming, reasoning about programs, program specification and verification, model checking and binary decision diagrams, temporal logic and modal logic.
(Cross-listed with CPR E). (3-1) Cr. 3. S.
Prereq: COM S 311, COM S 230, ENGL 250, SP CM 212
Introduction to high performance computing platforms including parallel computers and workstation clusters. Discussion of parallel architectures, performance, programming models, and software development issues. Sample applications from science and engineering. Practical issues in high performance computing will be emphasized via a number of programming projects using a variety of programming models and case studies. Oral and written reports.
(Dual-listed with COM S 526). (Cross-listed with CPR E). (3-2) Cr. 4. F.
Prereq: CPR E 308 or COM S 321, CPR E 315 or COM S 311
Models of parallel computation, performance measures, basic parallel constructs and communication primitives, parallel programming using MPI, parallel algorithms for selected problems including sorting, matrix, tree and graph problems, fast Fourier transforms.
(3-1) Cr. 3. S.
Prereq: COM S 311, COM S 362 or COM S 363, ENGL 250, SP CM 212
Topics in advanced programming techniques and tools widely used by industry (e.g., event-driven programming and graphical user interfaces, standard libraries, client/server architectures and techniques for distributed applications). Emphasis on programming projects in a modern integrated development environment. Oral and written reports.
(Dual-listed with COM S 533). (3-0) Cr. 3. S.
Prereq: Minimum of C- in COM S 331 or consent of the instructor
Modeling and analysis of natural and engineered systems that spontaneously assemble themselves from small components. Topics include biomolecular self-assembly, tile assembly models, computation via self-assembly, distributed folding, origami models, and self-repair. Emphasis on mathematical methods of describing, simulating, programming, and verifying the behaviors of self-assembling systems. Graduate credit requires a written or oral report on current research.
(3-0) Cr. 3. S.
Prereq: COM S 228, COM S 230 or CPR E 310, COM S 311 or equivalent
Challenges involved in solving computational problems on massive data sets. Discussion of computational problems that arise in the context of web search, social network analysis, recommendation systems, and online advertising etc. Theoretical aspects include modeling the computational problems using graphs, study of similarity measures and hash functions, and design of efficient algorithms for graphs. Practical aspects include implementation and performance evaluation of the algorithms on real world data sets. Graduate credit requires a written report on current research.
(3-0) Cr. 3. S.
Prereq: COM S 336 or permission of instructor
Students will learn video game programming using current game engine interfaces with real hardware. Particular attention is paid to the console architecture, development environment, tool chains, 2D graphics, 3D graphics, controllers, memory management, and audio systems. Students will complete the course by writing a simple game that runs on console hardware.
(Dual-listed with COM S 540). (3-1) Cr. 3. Alt. S., offered odd-numbered years.
Prereq: COM S 331, COM S 342, ENGL 250, SP CM 212
Theory of compiling and implementation issues of programming languages. Programming projects leading to the construction of a compiler. Projects with different difficulty levels will be given for 440 and 540. Topics: lexical, syntax and semantic analyses, syntax-directed translation, runtime environment and library support. Written reports.
(Cross-listed with BCB, BCBIO, BIOL, CPR E, GEN). (4-0) Cr. 4. F.
Prereq: MATH 165 or STAT 401 or equivalent.
Broad overview of bioinformatics with a significant problem-solving component, including hands-on practice using computational tools to solve a variety of biological problems. Topics include: bioinformatic data processing, Perl programming, genome assembly, database search, sequence alignment, gene prediction, next-generation sequencing, comparative and functional genomics, and systems biology.
(Dual-listed with COM S 554). (Cross-listed with CPR E). (3-1) Cr. 3. S.
Prereq: COM S 311, COM S 352
(3-1) Cr. 3. Theoretical and practical issues of design and implementation of distributed systems. The client server paradigm, inter-process communications, synchronization and concurrency control, naming, consistency and replication, fault tolerance, and distributed file systems. Graduate credit requires additional in-depth study of concepts. Programming projects and written reports.
(Dual-listed with COM S 555). (3-0) Cr. 3. Alt. F., offered even-numbered years.
Prereq: COM S 311 and COM S 230, STAT 330, ENGL 150, SP CM 212
Introduction to discrete-event simulation with a focus on computer science applications, including performance evaluation of networks and distributed systems. Overview of algorithms and data structures necessary to implement simulation software. Discrete and continuous stochastic models, random number generation, elementary statistics, simulation of queuing and inventory systems, Monte Carlo simulation, point and interval parameter estimation. Graduate credit requires additional in-depth study of concepts. Oral and written reports.
(Dual-listed with COM S 561). (3-1) Cr. 3. F.
Prereq: COM S 311, ENGL 250, SP CM 212.
Models for structured and semistructured data. Algebraic, first order, and user-oriented query languages. Database schema design. Physical storage, access methods, and query processing. Transaction management, concurrency control, and crash recovery. Database security. Information integration using data warehouses, mediators, wrappers, and data mining. Parallel and distributed databases, and special purpose databases. Students enrolling in COM S 561 will require additional study of advanced concepts in database systems.
(Dual-listed with COM S 572). (3-1) Cr. 3. F.
Prereq: COM S 311, COM S 230 or CPR E 310, STAT 330, ENGL 250, SP CM 212, COM S 342 or comparable programming experience
Specification, design, implementation, and selected applications of intelligent software agents and multi-agent systems. Computational models of intelligent behavior, including problem solving, knowledge representation, reasoning, planning, decision making, learning, perception, action, communication and interaction. Reactive, deliberative, rational, adaptive, learning and communicative agents and multiagent systems. Artificial intelligence programming. A research project and a written report is required for students enrolled in COM S 572.
(3-1) Cr. 3. Alt. S., offered odd-numbered years.
Prereq: COM S 311, COM S 230 or CPR E 310, STAT 330, MATH 165, ENGL 250, SP CM 212, COM S 342 or comparable programming experience
Basic principles, techniques, and applications of Machine Learning. Design, analysis, implementation, and applications of learning algorithms. Topics include: statistical learning, pattern classification, function approximation, Bayesian learning, linear models, artificial neural networks, support vector machines, decision trees, instance based learning, probabilistic graphical models, unsupervised learning, selected applications in automated knowledge acquisition, pattern recognition, and data mining.
(Dual-listed with COM S 577). (3-0) Cr. 3. Alt. F., offered even-numbered years.
Prereq: COM S 228; COM S 230 or CPR E 310, MATH 166, MATH 207 or MATH 317, or consent of the instructor
Selected topics in applied mathematics and modern heuristics that have found applications in areas such as geometric modeling, graphics, robotics, vision, human machine interface, speech recognition, computer animation, etc. Homogeneous coordinates and transformations, perspective projection, quaternions and rotations, polynomial interpolation, roots of polynomials, resultants, solution of linear and nonlinear equations, approximation, data fitting, Fourier series and fast Fourier transform, linear programming, nonlinear optimization, Lagrange multipliers, parametric and algebraic curves, curvature, Frenet formulas, Bezier curves. Programming components. A scholarly report is required for graduate credit.
(Cross-listed with MATH). (3-0) Cr. 3. S.
Prereq: MATH 265 and either MATH 266 or MATH 267; knowledge of a programming language
First order Euler method, high order Runge-Kutta method, and multistep method for solving ordinary differential equations. Finite difference and finite element methods for solving partial differential equations. Local truncation error, stability, and convergence for finite difference method. Numerical solution space, polynomial approximation, and error estimate for finite element method.
(3-0) Cr. 3. S.
Prereq: COM S 352
An introduction to fundamental concepts in the design and implementation of computer communication in both the wired and wireless networks, their protocols, and applications. Layered network architecture in the Internet, applications, transport, Socket APIs, network, and data link layers and their protocols, multimedia networking, and network security.
(Dual-listed with COM S 587). (3-0) Cr. 3. S.
Prereq: COM S 352 or CPR E 489 or equivalent.
Programming paradigms for building distributed and networking applications, including multithreaded client-server programming, socket programming, distributed object frameworks and programming suites, and web computing and security. Introduction to some on-going research issues in distributed and networking applications, including peer-to-peer computing, multimedia communications, and mobile computing and networking. A written report and an oral presentation is required for students enrolling in COM S 587.
Cr. arr. Repeatable, maximum of 9 credits. F.S.
Prereq: 6 credits in computer science, permission of instructor
Offered on a satisfactory-fail basis only. No more than 9 credits of Com S 490 may be counted toward graduation.
Cr. arr. Repeatable, maximum of 9 credits. F.S.
Prereq: 6 credits in computer science, permission of instructor
Offered on a satisfactory-fail basis only. No more than 9 credits of Com S 490 may be counted toward graduation.
Courses primarily for graduate students, open to qualified undergraduates:
(Cross-listed with CAS). (1-0) Cr. 1. F.S.
Prereq: Admission to CAS minor
Understanding core techniques in artificial life is based on basic readings in complex adaptive systems. Techniques of complex system analysis methods including: evolutionary computation, neural nets, agent based simulations (agent based computational economics). Large-scale simulations are to be emphasized, e.g. power grids, whole ecosystems.
(Cross-listed with CAS). (3-0) Cr. 3. S.
Prereq: Admission to CAS minor or related field
Survey of complex systems and their analysis. Examples are drawn from engineering, computer science, biology, economics and physics.
(Dual-listed with COM S 409). (3-0) Cr. 3. F.
Prereq: COM S 309
The requirements engineering process including identification of stakeholders requirements elicitation techniques such as interviews and prototyping, analysis fundamentals, requirements specification, and validation. Use of Models: State-oriented, Function-oriented, and Object-oriented. Documentation for Software Requirements. Informal, semi-formal, and formal representations. Structural, informational, and behavioral requirements. Non-functional requirements. Use of requirements repositories to manage and track requirements through the life cycle. Case studies, software projects, written reports, and oral presentations will be required.
(Dual-listed with COM S 410). (3-0) Cr. 3. F.
Prereq: COMS 228, COMS 309, COMS 327
Team with students at foreign universities to develop a software application. Importance of distributed development. Design for distributed development, effective processes for distributed development, and cultural issues in distributed development, organizing for distributed development, communication techniques and skills for distributed development,including oral presentations. Graduate credit requires in-depth study of concepts.
(Cross-listed with CPR E). (3-0) Cr. 3. F.
Prereq: COM S 311
A study of basic algorithm design and analysis techniques. Advanced data structures, amortized analysis and randomized algorithms. Applications to sorting, graphs, and geometry. NP-completeness and approximation algorithms.
(Dual-listed with COM S 412). (3-0) Cr. 3. S.
Prereq: COM S 311, COM S 330
A study of formal techniques for model-based specification and verification of software systems. Topics include logics, formalisms, graph theory, numerical computations, algorithms and tools for automatic analysis of systems. Graduate credit requires in-depth study of concepts.
(Dual-listed with COM S 414). (3-0) Cr. 3. F.
Prereq: COM S 227 or (COM S 207 or GERON 377 or ARTGR 271) or equivalent.
An interdisciplinary course designed for students who are interested in assistive technology, pervasive computing, mobile computing and principles of universal and inclusive design for end users, in particular, the elderly population. Students will work in semester-long projects as interdisciplinary teams to apply knowledge obtained from lectures and mutual presentations. For graduate credit students are required to submit a research report and give an oral presentation.
(Dual-listed with COM S 415). (3-0) Cr. 3. S.
Prereq: COM S 309 or COM S 311, COM S 342
An introduction to the analysis, design, and testing of software for safety-critical and high-integrity systems. Analysis techniques, formal verification, fault identification and recovery, model checking, and certification issues. Emphasizes a case-based and systematic approach to software's role in safe systems.
(Dual-listed with COM S 418). (3-0) Cr. 3. Alt. S., offered odd-numbered years.
Prereq: COM S 311 or permission of instructor
Introduction to data structures, algorithms, and analysis techniques for computational problems that involve geometry. Line segment intersection, polygon triangulation, 2D linear programming, range queries, point location, arrangements and duality, Voronoi diagrams and Delaunay triangulation, convex hulls, robot motion planning, visibility graphs. Other selected topics. Programming assignments.
(Cross-listed with CPR E, MATH). (3-0) Cr. 3. S.
Prereq: CPR E 308 or MATH 481; experience in scientific programming; knowledge of FORTRAN or C
Introduction to parallelization techniques and numerical methods for distributed memory high performance computers. A semester project in an area related to each student’s research interests is required.
(Dual-listed with COM S 426). (Cross-listed with CPR E). (3-2) Cr. 4. F.
Prereq: CPR E 308 or COM S 321, CPR E 315 or COM S 311
Models of parallel computation, performance measures, basic parallel constructs and communication primitives, parallel programming using MPI, parallel algorithms for selected problems including sorting, matrix, tree and graph problems, fast Fourier transforms.
(3-0) Cr. 3. S.
Prereq: COM S 331
A systematic study of the fundamental models and analytical methods of theoretical computer science. Computability, the Church-Turing thesis, decidable and undecidable problems, and the elements of recursive function theory. Time complexity, logic, Boolean circuits, and NP-completeness. Role of randomness in computation.
(Dual-listed with COM S 433). (3-0) Cr. 3. S.
Prereq: Minimum of C- in COM S 331 or consent of the instructor
Modeling and analysis of natural and engineered systems that spontaneously assemble themselves from small components. Topics include biomolecular self-assembly, tile assembly models, computation via self-assembly, distributed folding, origami models, and self-repair. Emphasis on mathematical methods of describing, simulating, programming, and verifying the behaviors of self-assembling systems. Graduate credit requires a written or oral report on current research.
(Dual-listed with COM S 440). (3-1) Cr. 3. Alt. S., offered odd-numbered years.
Prereq: COM S 331, COM S 342, ENGL 250, SP CM 212
Theory of compiling and implementation issues of programming languages. Programming projects leading to the construction of a compiler. Projects with different difficulty levels will be given for 440 and 540. Topics: lexical, syntax and semantic analyses, syntax-directed translation, runtime environment and library support. Written reports.
(Cross-listed with BCB, CPR E, GDCB). (4-0) Cr. 4. F.
Prereq: MATH 165 or STAT 401 or equivalent
Survey of key bioinformatics methods, including hands-on use of computational tools to solve various biological problems. Topics include: database searching, sequence alignment, gene prediction, RNA and protein structure prediction, construction of phylogenetic trees, comparative and functional genomics, and systems biology.
(Cross-listed with CPR E). (3-0) Cr. 3. Alt. S., offered even-numbered years.
Prereq: COM S 311 and either COM S 228 or COM S 208
Design and analysis of algorithms for applications in computational biology, pairwise and multiple sequence alignments, approximation algorithms, string algorithms including in-depth coverage of suffix trees, semi-numerical string algorithms, algorithms for selected problems in fragment assembly, phylogenetic trees and protein folding. No background in biology is assumed. Also useful as an advanced algorithms course in string processing.
(3-0) Cr. 3. Alt. F., offered odd-numbered years.
Prereq: COM S 311 and some knowledge of programming
Discussion and analysis of basic evolutionary principles and the necessary knowledge in computational biology to solve real world problems. Topics include character and distance based methods, phylogenetic tree distances, and consensus methods, and approaches to extract the necessary information from sequence-databases to build phylogenetic trees.
(3-0) Cr. 3. Alt. F., offered odd-numbered years.
Prereq: COM S 311 and some knowledge of programming
Introduction to practical sequence assembly and comparison techniques. Topics include global alignment, local alignment, overlapping alignment, banded alignment, linear-space alignment, word hashing, DNA-protein alignment, DNA-cDNA alignment, comparison of two sets of sequences, construction of contigs, and generation of consensus sequences. Focus on development of sequence assembly and comparison programs.
(3-0) Cr. 3. F.
Prereq: COM S 352
A comparative study of high-level language facilities for process synchronization and communication. Formal analysis of deadlock, concurrency control and recovery. Protection issues including capability-based systems, access and flow control, encryption, and authentication. Additional topics chosen from distributed operating systems, soft real-time operating systems, and advanced security issues.
(Dual-listed with COM S 454). (Cross-listed with CPR E). (3-1) Cr. 3. S.
Prereq: COM S 311, COM S 352
(3-1) Cr. 3. Theoretical and practical issues of design and implementation of distributed systems. The client server paradigm, inter-process communications, synchronization and concurrency control, naming, consistency and replication, fault tolerance, and distributed file systems. Graduate credit requires additional in-depth study of concepts. Programming projects and written reports.
(Dual-listed with COM S 455). (3-0) Cr. 3. Alt. F., offered even-numbered years.
Prereq: COM S 311 and COM S 230, STAT 330, ENGL 150, SP CM 212
Introduction to discrete-event simulation with a focus on computer science applications, including performance evaluation of networks and distributed systems. Overview of algorithms and data structures necessary to implement simulation software. Discrete and continuous stochastic models, random number generation, elementary statistics, simulation of queuing and inventory systems, Monte Carlo simulation, point and interval parameter estimation. Graduate credit requires additional in-depth study of concepts. Oral and written reports.
(3-0) Cr. 3. Alt. S., offered odd-numbered years.
Prereq: COM S 331, MATH 307, and STAT 330
Introduction to the use of stochastic models to study complex systems, including network communication and distributed systems. Data structures and algorithms for analyzing discrete-state models expressed in high-level formalisms. State space and reachability graph construction, model checking, Markov chain construction and numerical solution, computation of performance measures, product-form models, approximations, and advanced techniques.
(Cross-listed with CPR E, M E). (3-0) Cr. 3. F.
Prereq: M E 421, programming experience in C
Fundamentals of computer graphics technology. Data structures. Parametric curve and surface modeling. Solid model representations. Applications in engineering design, analysis, and manufacturing.
(Cross-listed with GEOL, HCI). (2-2) Cr. 3. Alt. F., offered even-numbered years.
Prereq: Graduate-student standing in the mathematical or natural sciences or engineering; basic programming knowledge
Introduction to visualizing scientific information with 3D computer graphics and their foundation in human perception. Overview of different visualization techniques and examples of 3D visualization projects from different disciplines (natural sciences, medicine, and engineering). Class project in interactive 3D visualization using the ParaView, Mayavi, TVTK, VTK or a similar system.
(Dual-listed with COM S 461). (3-1) Cr. 3. F.
Prereq: COM S 311, ENGL 250, SP CM 212.
Models for structured and semistructured data. Algebraic, first order, and user-oriented query languages. Database schema design. Physical storage, access methods, and query processing. Transaction management, concurrency control, and crash recovery. Database security. Information integration using data warehouses, mediators, wrappers, and data mining. Parallel and distributed databases, and special purpose databases. Students enrolling in COM S 561 will require additional study of advanced concepts in database systems.
(Cross-listed with BCB, CPR E). (3-0) Cr. 3. F.
Prereq: COM S 228; COM S 330; credit or enrollment in BIOL 315, STAT 430
Biology as an information science. Review of algorithms and information processing. Generative models for sequences. String algorithms. Pairwise sequence alignment. Multiple sequence alignment. Searching sequence databases. Genome sequence assembly.
(Cross-listed with BBMB, BCB, CPR E). (3-0) Cr. 3. F.
Prereq: BCB 567, BBMB 316, GEN 409, STAT 430
Algorithmic and statistical approaches in structural genomics including protein, DNA and RNA structure. Structure determination, refinement, representation, comparison, visualization, and modeling. Analysis and prediction of protein secondary and tertiary structure, disorder, protein cores and surfaces, protein-protein and protein-nucleic acid interactions, protein localization and function.
(Cross-listed with BCB, CPR E, GDCB, STAT). (3-0) Cr. 3. S.
Prereq: BCB 567 or COM S 311, COM S 228, GEN 409, STAT 430
Algorithmic and statistical approaches in computational functional genomics and systems biology. Elements of experiment design. Analysis of high throughput gene expression, proteomics, and other datasets obtained using system-wide measurements. Topological analysis, module discovery, and comparative analysis of gene and protein networks. Modeling, analysis, simulation and inference of transcriptional regulatory modules and networks, protein-protein interaction networks, metabolic networks, cells and systems: Dynamic systems, Boolean, and probabilistic models. Multi-scale, multi-granularity models. Ontology-driven, network based, and probabilistic approaches to information integration.
(Dual-listed with COM S 472). (3-1) Cr. 3. F.
Prereq: COM S 311, COM S 230 or CPR E 310, STAT 330, ENGL 250, SP CM 212, COM S 342 or comparable programming experience
Specification, design, implementation, and selected applications of intelligent software agents and multi-agent systems. Computational models of intelligent behavior, including problem solving, knowledge representation, reasoning, planning, decision making, learning, perception, action, communication and interaction. Reactive, deliberative, rational, adaptive, learning and communicative agents and multiagent systems. Artificial intelligence programming. A research project and a written report is required for students enrolled in COM S 572.
(3-1) Cr. 3. S.
Prereq: COM S 311, COM S 362, STAT 330
Algorithmic models of learning. Design, analysis, implementation and applications of learning algorithms. Learning of concepts, classification rules, functions, relations, grammars, probability distributions, value functions, models, skills, behaviors and programs. Agents that learn from observation, examples, instruction, induction, deduction, reinforcement and interaction. Computational learning theory. Data mining and knowledge discovery using artificial neural networks, support vector machines, decision trees, Bayesian networks, association rules, dimensionality reduction, feature selection and visualization. Learning from heterogeneous, distributed, dynamic data and knowledge sources. Learning in multi-agent systems. Selected applications in automated knowledge acquisition, pattern recognition, program synthesis, bioinformatics and Internet-based information systems. Oral and written reports.
(Cross-listed with CPR E, HCI). (3-0) Cr. 3. S.
Prereq: Graduate standing or permission of instructor
This class covers statistical and algorithmic methods for sensing, recognizing, and interpreting the activities of people by a computer. This semester we will focus on machine perception techniques that facilitate and augment human-computer interaction. The main goal of the class is to introduce computational perception on both theoretical and practical levels. Participation in small groups to design, implement, and evaluate a prototype of a human-computer interaction system that uses one or more of the techniques covered in the lectures.
(Dual-listed with COM S 477). (3-0) Cr. 3. Alt. F., offered even-numbered years.
Prereq: COM S 228; COM S 230 or CPR E 310, MATH 166, MATH 207 or MATH 317, or consent of the instructor
Selected topics in applied mathematics and modern heuristics that have found applications in areas such as geometric modeling, graphics, robotics, vision, human machine interface, speech recognition, computer animation, etc. Homogeneous coordinates and transformations, perspective projection, quaternions and rotations, polynomial interpolation, roots of polynomials, resultants, solution of linear and nonlinear equations, approximation, data fitting, Fourier series and fast Fourier transform, linear programming, nonlinear optimization, Lagrange multipliers, parametric and algebraic curves, curvature, Frenet formulas, Bezier curves. Programming components. A scholarly report is required for graduate credit.
(Cross-listed with CPR E). (3-0) Cr. 3. F.
Prereq: CPR E 381
Quantitative principles of computer architecture design, instruction set design, processor architecture: pipelining and superscalar design, instruction level parallelism, memory organization: cache and virtual memory systems, multiprocessor architecture, cache coherency, interconnection networks and message routing, I/O devices and peripherals.
(Cross-listed with CPR E). (3-0) Cr. 3.
Prereq: Background in computer architecture, design, and organization
Introduction to reconfigurable computing, FPGA technology and architectures, spatial computing architectures such as systolic and bit serial adaptive network architectures, static and dynamic rearrangeable interconnection architectures, processor architectures incorporating reconfigurabiltiy.
(3-0) Cr. 3. F.
Prereq: COM S 511, COM S 552 or CPR E 489
Design and implementation of computer communication networks: layered network architectures, local area networks, data link protocols, distributed routing, transport services, network programming interfaces, network applications, error control, flow/congestion control, interconnection of heterogeneous networks, TCP/IP, ATM networks, multimedia communications, IP and application multicast, overlay networks, network security and web computing.
(Dual-listed with COM S 487). (3-0) Cr. 3. S.
Prereq: COM S 352 or CPR E 489 or equivalent.
Programming paradigms for building distributed and networking applications, including multithreaded client-server programming, socket programming, distributed object frameworks and programming suites, and web computing and security. Introduction to some on-going research issues in distributed and networking applications, including peer-to-peer computing, multimedia communications, and mobile computing and networking. A written report and an oral presentation is required for students enrolling in COM S 587.
Cr. arr. Repeatable.
Prereq: Permission of instructor
Offered on a satisfactory-fail basis only.
Cr. 1. F.S.
Prereq: Graduate classification
Attend Computer Science Research Colloquia. Written summary is required.
Offered on a satisfactory-fail basis only.
Cr. R. Repeatable. F.S.SS.
Prereq: Graduate Classification
Supervised internship working in professional settings appropriate to the student's degree program. Academic work under faculty supervision.
Cr. 1-3.
Creative component for nonthesis option of Master of Science degree.
Offered on a satisfactory-fail basis only.
Courses for graduate students:
Cr. arr.
Offered on a satisfactory-fail basis only.
(3-0) Cr. 3. Repeatable. Alt. S., offered odd-numbered years.
Prereq: COM S 511, COM S 531
Advanced algorithm analysis and design techniques. Topics include graph algorithms, algebraic algorithms, number-theoretic algorithms, randomized and parallel algorithms. Intractable problems and NP-completeness. Advanced data structures.
(3-0) Cr. 3. Alt. S., offered even-numbered years.
Prereq: COM S 511 or COM S 531
The theory of distributed computation. Algorithms, lower bounds and impossibility results. Leader Elections, mutual exlusion, consensus and clock synchronization algorithms. Synchronous, asynchronous and partially synchronous distributed systems models. Shared memory and message passing systems. Fault-tolerance and randomization. Broadcast and multicast. Wait-free object simulations. Distributed shared memory.
(Cross-listed with CPR E). (3-0) Cr. 3.
Prereq: CPR E 526
Algorithm design for high-performance computing. Parallel algorithms for multidimensional tree data structures, space-filling curves, random number generation, graph partitioning and load balancing. Applications to grid and particle-based methods and computational biology.
(3-0) Cr. 3. Repeatable. Alt. F., offered even-numbered years.
Prereq: COM S 531
Advanced study in the quantitative theory of computation. Time and space complexity of algorithmic problems. The structure of P, NP, PH, PSPACE, and other complexity classes, especially with respect to resource-bounded reducibilities and complete problems. Complexity relative to auxiliary information, including oracle computation and relativized classes, randomized algorithms, advice machines, Boolean circuits. Kolmogorov complexity and randomness.
(3-0) Cr. 3. Repeatable. Alt. F., offered odd-numbered years.
Prereq: COM S 531
Advanced study of the role of randomness in computation. Randomized algorithms, derandomization, and probabilistic complexity classes. Kolmogorov complexity, algorithmic information theory, and algorithmic randomness. Applications chosen from cryptography, interactive proof systems, computational learning, lower bound arguments, mathematical logic, and the organization of complex systems.
(3-0) Cr. 3. Alt. S., offered odd-numbered years.
Prereq: COM S 330
Fundamentals of Game Theory: individual decision making, strategic and extensive games, mixed strategies, backward induction, Nash and other equilibrium concepts. Discussion of Auctions and Bargaining. Repeated, Bayesian and evolutionary games. Interactive Epistemology: reasoning about knowledge in multiagent environment, properties of knowledge, agreements, and common knowledge. Reasoning about and representing uncertainty, probabilities, and beliefs. Uncertainty in multiagent environments. Aspects and applications of game theory, knowledge, and uncertainty in other areas, especially Artificial Intelligence and Economics, will be discussed.
(3-0) Cr. 3. Repeatable. Alt. F., offered odd-numbered years.
Prereq: COM S 552
Concepts and techniques for network and distributed operating systems: Communications protocols, processes and threads, name and object management, synchronization, consistency and replications for consistent distributed data, fault tolerance, protection and security, distributed file systems, design of reliable software, performance analysis.
(3-0) Cr. 3. Alt. F., offered even-numbered years.
Prereq: COM S 228, I E 557/M E 557/CPR E 557/COM S 557
Modern lighting models: Rendering Equation, Spherical Harmonics, Lafortune, Cook-Torrance. Non-polygonal primitives: volumes, points, particles. Textures: filtering, reflections creation. Graphics hardware: pipeline, performance issues, programmability in vertex and fragment path. Per-pixel lighting. Nonphotorealistic rendering. Radiosity; Ray tracing.
(3-0) Cr. 3. Repeatable. Alt. F., offered even-numbered years.
Prereq: COM S 461 or COM S 561
Advanced topics chosen from the following: database design, data models, query systems, query optimization, incomplete information, logic and databases, multimedia databases; temporal, spatial and belief databases, semistructured data, concurrency control, parallel and distributed databases, information retrieval, data warehouses, wrappers, mediators, and data mining.
(3-0) Cr. 3. Repeatable. Alt. S., offered even-numbered years.
Prereq: COM S 572 or COM S 573 or COM S 472 or COM S 474
Selected topics in Computational Learning Theory (PAC learning, Sample complexity, VC Dimension, Occam Learning, Boosting, active learning, Kolomogorov Complexity, Learning under helpful distributions, Mistake Bound Analysis). Selected topics in Bayesian and Information Theoretic Models (ML, MAP, MDL, MML). Advanced statistical methods for machine learning. Selected topics in reinforcement learning.
(3-0) Cr. 3. Repeatable. Alt. S., offered odd-numbered years.
Prereq: COM S 572 or COM S 573 or COM S 472 or COM S 474
Advanced applications of artificial intelligence in bioinformatics, distributed intelligent information networks and the Semantic Web. Selected topics in distributed learning, incremental learning, multi-task learning, multi-strategy learning; Graphical models, multi-relational learning, and causal inference; statistical natural language processing; modeling the internet and the web; automated scientific discovery; neural and cognitive modeling.
(Cross-listed with CPR E). (3-0) Cr. 3. Alt. S., offered odd-numbered years.
Prereq: CPR E 581. Repeatable with Instructor permission
Current topics in computer architecture design and implementation. Advanced pipelining, cache and memory design techniques. Interaction of algorithms with architecture models and implementations. Tradeoffs in architecture models and implementations.
Cr. arr. Repeatable.
Prereq: Approval of instructor
Offered on a satisfactory-fail basis only.