Reliability and fault tolerance techniques for commercial and special purpose computer systems. Failure models and statistics, testing, redundancy techniques, error correcting codes and self-checking circuits, reliability modeling, case studies. Prerequisites: E&C-ENG 314 and 568 or equivalent.

We investigate the state-of-the-art in reconfigurable computing both from a hardware and software perspective. Initially, we review in detail the basic building blocks of most reconfigurable computers, field-programmable gate arrays (FPGAs). These physical limitations are then contrasted with computer-aided design issues such as the selection of circuit component locations in devices (the placement problem) and subsequent circuit interconnection between components (the routing problems).

Experimental investigation of the fundamental aspects of soil behavior including classification, index and engineering properties. Emphasizes experimental determination of the consolidation and stress-strain-strength characteristics of soils for design. Experiments include: classification and basic index tests, hydraulic conductivity, consolidation, triaxial tests and direct simple shear.

Experimental investigation of the fundamental aspects of soil behavior including classification, index and engineering properties. Emphasizes experimental determination of the consolidation and stress-strain-strength characteristics of soils for design. Experiments include: classification and basic index tests, hydraulic conductivity, consolidation, triaxial tests and direct simple shear.

Pre-practicum experience, one half day or one full day, in a public school classroom.

This course covers advanced data management systems, including high-performance database systems and recent big data systems. The course first covers the design and implementation of high-performance database systems including data warehouses, decision support systems, column stores, and parallel databases. It also covers advanced databases to support new data models, including temporal databases, sequence databases, and data stream systems.

A survey of modern programming language principles, focused on
implementing ideas. Topics include interpreters, type-inference
algorithms, program analyses, program verification, and garbage collection.

People are able to infer the characteristics of a scene or object from an image of it. In this course, we will study what is involved in building artificial systems which try to infer such characteristics from an image. Topics include: Basics of image formation - the effect of geometry, viewpoint, lighting and albedo on image formation. Basic image operations such as filtering, convolution and correlation. Frequency representations of images. The importance of scale in images. Measurements of image properties such as color, texture, appearance and shape.

This course provides a rigorous introduction to mathematical logic from an algorithmic perspective. Topics include Propositional Logic: Horn Clause Satisfiability and SAT Solvers; First Order Logic: Soundness and Completeness of Resolution; Compactness Theorem; Automatic Theorem Proving; Model Checking. Students will learn the theory behind and use the following systems, languages, and tools: the Coq theorem prover, Datalog, the NuSMV Model Checker, and SAT and SMT solvers.

An introduction to fundamental concepts in the design and implementation of computer communication networks, their protocols, and applications. Topics include: layered network architectures, applications, network programming interfaces (e.g., sockets), transport, congestion, routing and data link protocols, local area networks, emerging high-speed networks, network management, and network security. Examples drawn primarily from the Internet (e.g., TCP, UDP, and IP) protocol suite. A rudimentary understanding of computer architecture and operating systems helpful.