Teaches software design principles for building high-scale Internet services. Focuses on challenges arising when assembling software services that run on many machines in parallel and which require the coordination of multiple software applications.

Introduction to key parts of programming languages: syntax, semantics, and pragmatics. Implementation of a series of interpreters that show how various aspects of programming languages behave.

A practical excursion into building intelligent information systems. Students develop a working program in information access, management, capture, or retrieval. Project definition, data collection, technology selection, implementation, and project management.

In this course, students will design and develop games using the Unity game engine, with focus on team-based projects and agile development practices. Lectures will cover game design theory, game architecture and implementation, and the business of game development. Students will participate in class discussion and evaluation of projects in progress, to develop their skills in iterative design and implementation.

This is a course about developing working prototypes of full-stack mobile web software applications in rapid iterations. Teams design and implement three distinct applications over ten weeks. These projects are the context for introducing (1) cross-functional team development, (2) lean agile value-first product development, and (3) specific web application frameworks and development tools, such as React, Firebase, Cypress, and Github Actions for continuous integration.

Building software is a craft that requires careful design. This course teaches software design principles in a studio setting. Each week, students present their programs to the class for review. Together, the class evaluates the programs for correctness and, more importantly, clarity and design. Expect to learn how to build reliable, maintainable, extensible software and how to read others' codes.

Developing mobile and web applications, using modern sustainable agile practices, such as backlogs, user stories, velocity charts, and test driven development, to deliver value as quickly as possible to end users, clients, developers, and the development organization.

NUvention: Web is an interdisciplinary experiential learning program designed to expose students to the entire product and business development life cycle for a software company.

NUvention: Web is an interdisciplinary experiential learning program designed to expose students to the entire product and business development life cycle for a software company.

The use of tangible interaction to create innovative learning experiences, including distributed cognition, embodied interaction, cultural forms, and design frameworks.

Hands-on experience in the research learning environment. Students lead research projects in social and crowd computing, cyber-learning, human-computer interaction, and artificial intelligence.

Human-Computer Interaction (HCI) serves as the bridge between computing and humanity. This class aims to develop critical thinking skills through effective structures for designing HCI systems.

Introduction to human-computer interaction and design of systems that work for people and their organizations. Understanding the manner in which humans interact with and use computers for productive work.

Fundamentals of digital imaging and modern camera architectures. Hands-on experience acquiring, characterizing, and manipulating data captured using a modern camera platform.

This course covers theory and techniques for information visualization using interactive interfaces to visualize abstract data.

Mathematical software and hardware requirements for computer graphics systems. Data structures and programming languages. Random displays. Graphic applications.

Machine extraction of musical structure in audio and MIDI and score files, covering areas such as source separation and perceptual mapping of audio to machine-quantifiable measures.

Plot, narrative, and character simulation for creating game worlds; artificial intelligence for synthetic characters; tuning gameplay. Substantial programming and project work.

This course will begin with an introduction to the multi-agent language NetLogo. Students will design and implement several NetLogo models and analyze their behavioral regimes. Students will also learn to build models of interaction on social networks (or other types of networks). We will cover methodology for verifying, validating and replicating agent-based models and comparisons with systems dynamics and equation-based models. NetLogo comes with many extensions that support a variety of additional features. Students can use these extensions to create specialized models, such as complex networks, real-time data extraction, data mining, connections to physical devices, etc.. Students will also have an opportunity to explore existing and create their own participatory simulations using the HubNet architecture as well as exploring connecting real world sensors and motors to models. Students can also explore multi-level agent-based modeling in which hundreds or thousands of models are connected with NetLogo's LevelSpace extension.

Introduction to design of simulation-based media, with an emphasis on 2D game design. Mathematical preliminaries: linear, affine, and projective spaces, linear transforms, inner and exterior products, unit quaternions; Architecture: update/render loop, component systems, serialization and deserialization, event handling and asynchronous processing, multitasking; Rendering: scene graphs, meshes, shaders, sprites; Networking; Audio; Physics: particles, rigid bodies, collision detection; Gameplay design.

In this course, students will design and develop games using the Unity game engine, with focus on team-based projects and agile development practices. Lectures will cover game design theory, game architecture and implementation, and the business of game development. Students will participate in class discussion and evaluation of projects in progress, to develop their skills in iterative design and implementation.

Computer and biological vision systems, image formation, edge detection, image segmentation, texture, representation and analysis of two-dimensional geometric structures and of three-dimensional structures.

The compiler is the programmer's primary tool. Understanding the compiler is therefore critical for programmers, even if they never build one. Furthermore, many design techniques that emerged in the context of compilers are useful for a range of other application areas. This course introduces students to the essential elements of building a compiler: parsing, context-sensitive property checking, code linearization, register allocation, etc. To take this course, students are expected to already understand how programming languages behave, to a fairly detailed degree. The material in the course builds on that knowledge via a series of semantics preserving transformations that start with a fairly high-level programming language and culminate in machine code.

Data models and database design. Modeling the real world: structures, constraints, and operations. The entity relationship to data modeling (including network hierarchical and object-oriented), emphasis on the relational model. Use of existing database systems for the implementation of information systems.

A top-down exploration of networking using the five-layer model and the TCP/IP stack, covering each layer in depth. Students build web clients, servers, and a TCP implementation and implement routing algorithms.

Fundamental overview of operating systems, including: concurrency (processes, synchronization, semaphores, monitors, deadlock); memory management (segmentation, paging virtual memory policies); software system architectures (level structures, microkernals); file systems (directory structures, file organization, RAID); protection (access control, capabilities, encryption, signatures, authentication). Requires substantial programming projects.

Basic principles behind distributed systems (collections of independent components that appear to users as a single coherent system) and main paradigms used to organize them.

Basic principles and practices of computer and information security. Software, operating system, and network security techniques, with detailed analysis of real-world examples. Topics include cryptography, authentication, software and operating system security (e.g., buffer overflow), Internet vulnerability (DoS attacks, viruses/worms, etc.), intrusion detection systems, firewalls, VPN, and web and wireless security.

The past decade has seen an explosion in the concern for the security of information. This course introduces students to the basic principles and practices of computer system and networking security, with detailed analysis of real-world examples and hands-on practice. Topics include the basic crypto, authentication, reverse engineering, buffer overflow attacks, vulnerability scanning, web attacks, firewalls, intrusion detection/prevention systems, etc. We will first introduce the basic theory for each type of attack; then we will actually carry them out in 'real-world' settings. The goal is to learn security by learning how to view your machine from a hacker's perspective. In addition, we encourage students to participate in the UCSB International Capture the Flag Competition. Capture the Flag is a network security exercise where the goal is to exploit other machines while defending your own. In fact, this course should prepare you for any one of many capture the flag competitions that take place year-round. We will learn about different types of hacks and perform them. After learning how to execute such exploits and penetrate a network, we will discuss ways to protect a network from others exploiting the same vulnerabilities. Understanding security is essential in all fields of software development and computing. For major or minors in Computer Science, this course can satisfy the system breadth.

This course will cover a broad range of topics including Internet evolution and architectures; analysis and design of network protocols (both wired and wireless); networking issues for Web and gaming applications; analysis and performance of content distribution networks; network security, vulnerability, and defenses.

The bulk of the time in this class examining a virtual machine monitor (VMM) in depth, at the source code level. The course explains the hardware/software interface of a modern x86 computer in detail. A VMM is an operating system that is implemented directly on top of the hardware interface, and itself presents a hardware interface to higher-level software. Students will also acquire valuable kernel development skills.

Advanced concepts in operating systems and distributed computing from historical perspectives to current themes such as peer-to-peer computing and mobile systems.

The development of low-level systems software such as drivers, kernels, etc is very different from the development of applications. This class teaches how such development is done: how to design, implement, debug, and optimize low-level software and use available tools.

Through measurement-based approaches, students analyze the complexity of the Internet, and develop countermeasures against various vulnerabilities of the Internet such as viruses, worms, and denial of service attacks.

Overview of digital logic design. Technology review. Delays, timing in combinational and sequential circuits, CAD tools, arithmetic units such as ALUs and multipliers. Introduction to VHDL.

Structure and timing of typical microprocessors. Sample microprocessor families. Memories, UARTS, timer/counters, serial devices, and related devices. MUX and related control structures for building systems. Standard bus structures. Interrupt programming. Hardware/software design tradeoffs.

Introduction to parallel computing for scientists and engineers. Shared-memory parallel architectures and programming, distributed memory, message-passing data-parallel architectures, and programming.

Design and understanding of the computer system as a whole unit. Performance evaluation and its role in computer system design; instruction set architecture design, data-path design and optimizations (e.g., ALU); control design; single cycle, multiple cycle, and pipeline implementations of processor. Hazard detection and forwarding; memory hierarchy design; cache memories, virtual memory, peripheral devices, and I/O.

Introduction to LISP and programming knowledge-based systems and interfaces. Strong emphasis on writing maintainable, extensible systems.

Semantics-oriented introduction to natural language processing, broadly construed. Representation of meaning and knowledge inference in story understanding, script/frame theory, plans and plan recognition, counter-planning, and thematic structures.

Principles and practice of organizing and building artificial intelligence reasoning systems. Pattern-directed rule systems, truth-maintenance systems, and constraint languages.

Core techniques and applications of AI. Representing, retrieving, and applying knowledge for problem solving. Hypothesis exploration. Theorem proving. Vision and neural networks.

Study of algorithms that improve through experience. Topics typically include Bayesian learning, decision trees, genetic algorithms, neural networks, Markov models, and reinforcement learning. Assignments include programming projects and written work.

Principles and practices of knowledge representation, including logics, ontologies, commonsense knowledge, and semantic web technologies.

This course will begin with an introduction to the multi-agent language NetLogo. Students will design and implement several NetLogo models and analyze their behavioral regimes. Students will also learn to build models of interaction on social networks (or other types of networks). We will cover methodology for verifying, validating and replicating agent-based models and comparisons with systems dynamics and equation-based models. NetLogo comes with many extensions that support a variety of additional features. Students can use these extensions to create specialized models, such as complex networks, real-time data extraction, data mining, connections to physical devices, etc.. Students will also have an opportunity to explore existing and create their own participatory simulations using the HubNet architecture as well as exploring connecting real world sensors and motors to models. Students can also explore multi-level agent-based modeling in which hundreds or thousands of models are connected with NetLogo's LevelSpace extension.

Mathematical foundations of computation, including computability, relationships of time and space, and the P vs. NP problem.

Analysis techniques and algorithm design techniques including sorting and selection algorithms, order statistics, heaps, and priority queues.