Computer Science (CS)

http://www.cs.unh.edu

Degrees Offered: Ph.D., M.S. 

This program is offered in Durham.

The Department of Computer Science offers both the M.S. and the Ph.D. in computer science.

The M.S. program is designed to help students increase the breadth and depth of their computer science knowledge, strengthen their software development skills, and build their research skills.

The Ph.D. program is designed to develop a student's ability to carry out advanced research, as well as ensure the breadth and depth of computer science knowledge required to obtain a faculty position in academia or a research position in industry or at a national laboratory.

Admission Requirements

The computer science graduate program is designed for students with a B.S. degree in computer science. However, applications from students whose undergraduate degree is not in computer science are also welcome. In this case, a well­-defined set of undergraduate prerequisites must be completed as part of the M.S. program of study. The prerequisites include an introduction to computer science, object-­oriented programming, data structures, machine organization, operating systems, and computer science theory.

These prerequisites can be satisfied at UNH by the following undergraduate courses:

CS 415Introduction to Computer Science I4
CS 416Introduction to Computer Science II4
CS 515Data Structures4
CS 520Assembly Language Programming and Machine Organization4
CS 620Operating System Fundamentals4
CS 659Introduction to the Theory of Computation4

Some students may need to take additional mathematics classes.

Students without a B.S. or M.S. in computer science are not normally admitted directly into the Ph.D. program, but it is possible to transfer from the M.S. program to the Ph.D. program.

Applicants must submit current scores (within five years) for the general test of the GRE. Students who have taken computer science courses at UNH can request a waiver of this requirement.

Computer Science (CS)

CS 800 - Internship

Credits: 1

Provides an opportunity to apply academic experience in settings associated with future professional employment. A written proposal for the internship must be approved by the department chair. The proposal must specify what the student will learn from the internship, why the student is properly prepared for the internship, and what supervision will be available to the student during the internship. A mid-semester report and a final report are required. Permission required. Computer Science majors only. May be repeated up to a maximum of 3 credits. Cr/F.

CS 812 - Compiler Design

Credits: 3

Formal languages and formal techniques for syntax analysis and parsing; organization of the compiler and its data structures; code generation. LL and LR parsing; automatic generation of scanners and parsers from high-level descriptions. Implementation of features from imperative and object-oriented languages. Students are required to design and implement a compiler for a simple language. Prereq: Machine Organization.

CS 819 - Advanced Programming with Object-Oriented Design

Credits: 3

Advanced problem solving using software design, development and testing techniques that follow the software development life cycle. Object-oriented programming and design. Advanced data structures and algorithm analysis. Prereq: strong prog. skills, exp. with C/C++, match org.

CS 820 - Operating System Programming

Credits: 3

Detailed discussion of operating system concepts and features. Practical examples and exercises that utilize advanced operating system features, including inter-process communication, synchronization, client-server communication, shared memory, threads, remote procedure calls, and device-level I/O. Discussion of POSIX 1003.1 Part I Standards. Prereq: operating system fundamentals or equivalent.

CS 823 - Performance Evaluation of Computer Systems

Credits: 3

This class introduces the main concepts, techniques, and tools needed to evaluate the performance of computer systems under various configurations and workloads. The techniques allow one to perform capacity planning based on quality of service requirements of users and workload characteristics. The course is mainly based on the use of analytic queuing network models of computer systems. The performance techniques are applied to study the performance of centralized, distributed, parallel, and client/server systems. The course also discusses performance measuring tools for operating systems such as Unix and Windows NT. Prereq: operating systems fundamentals or equivalent.

CS 825 - Computer Networks

Credits: 3

Introduction to fundamental concepts of computer networks and exploration of widely-used networking technologies. Topics include principles of congestion and error control; network routing; local, wireless and access networks; application protocol design; and network programming. In-depth discussion of the Internet suite of protocols.

CS 830 - Introduction to Artificial Intelligence

Credits: 3

In-depth introduction to artificial intelligence concentrating on aspects of intelligent problem-solving. Topics include situated agents, advanced search techniques, knowledge representations, logical reasoning techniques, reasoning under uncertainty, advanced planning and control, and learning. Prereq: data structures.

CS 833 - Mobile Robotics

Credits: 3

An introduction to the foundational theory and practices in mobile robotics. Topics include Kinematics of wheeled mobile robots. Seniors for mobile robots, robot navigation and perception, robot vision, localization and mapping of mobile robots. Hands-on experience directed towards implementation with a real robot. Prereq: Programming or permission of instructor.

CS 835 - Introduction to Parallel and Distributed Programming

Credits: 3

Programming with multiple processes and threads on distributed and parallel computer systems. Introduces programming tools and techniques for building applications on such platforms. Course requirements consist primarily of programming assignments. Prereq: Undergraduate course in operating systems fundamentals and computer organization; or permission.

CS 845 - Formal Specification and Verification of Software Systems

Credits: 3

Course focuses on the formal specification and verification of reactive systems, most notably concurrent and distributed systems. Topics relevant to these systems, such as non-determinism, safety and liveness properties, asynchronous communication or compositional reasoning, are discussed. We rely on a notation (T LA+, the Temporal Logic of Actions) and a support tool (TLC, the TLA+ Model Checker). Prereq: Students are expected to be knowledgeable in logic and to be able to write symbolic proofs in predicate calculus. A basic understanding of the notions of assertion, precondition, and post-condition is also assumed.

CS 850 - Machine Learning

Credits: 3

An introduction to fundamental concepts and common methods in machine learning. In addition to theoretical topics, the course involves hands-on experience in making predictions using synthetic and real-world datasets. Prereq: Statistics, Programming or permission of instructor.

CS 853 - Information Retrieval

Credits: 3

Fundamental algorithms and techniques for text processing and text-based information retrieval systems. Topics include how to build an end-to-end information retrieval system, such as a Web search engine. Prereq: Data Structures.

CS 854 - System/Software Test and Evaluation

Credits: 3

This course identifies an integrated software test and evaluation process framework that emphasizes a "systems engineering" approach: the validation and viability of customer/user needs statements, verification of system design, full exercise of developmental testing, system integration/test dovetailing on the prior validations, plus evaluation of system quality attributes. This system engineering approach is intended to contain major problems, including interface issues, to phases preceding system test.

CS 858 - Algorithms

Credits: 3

An introduction to important concepts in the design and analysis of algorithms and data structures, including implementation, complexity, analysis, and proofs of correctness. Prereq: understanding of basic data structures, familiarity with proof methods and basic concepts from discrete mathematics and the ability to program with recursion.

CS 860 - Introduction to Human-Computer Interaction

Credits: 3

Human-computer interaction is a discipline concerned with the design, evaluation and implementation of interactive computing systems for human use and with the study of major phenomena surrounding them. Prereq: operating systems fundamentals.

CS 867 - Interactive Data Visualization

Credits: 3

Detailed discussion of how an understanding of human perception can help us design better interactive displays of data. Topics include: color, space perception, object perception and interactive techniques. Students write interactive programs, give presentations and undertake a project designing and evaluating a novel display technique. Prereq: Introductory level C or C++ programming course. (Also listed as OE 867.)

CS 870 - Computer Graphics

Credits: 3

Input-output and representation of pictures from hardware and software points of view; interactive techniques and their applications; three-dimensional image synthesis techniques. Prereq: data structures.

CS 871 - Web Programming Paradigms

Credits: 3

In this course you will learn languages to program the Web. Languages integrated into browsers, like Javascript, and languages invoked on the server, like Ruby. You will also learn about frameworks, like Rails, and various techniques used to support the programming process. In addition, you will learn languages you will need to create, modify and process Web documents. Although we will learn how to read and write in these languages, our primary goal will be on understanding how the design of these multi-paradigm dynamic languages support the process of delveoping Web applications. Prereq: programming lnaguage concepts or permission.

CS 875 - Database Systems

Credits: 3

Database analysis, design, and implementation. Focus on the relational model. Data description and manipulation languages, schema design and normalization, file and index organizations, data integrity and reliability. Usage of selected DBMS. Prereq: data structures; mathematical proof.

CS 880 - Topics

Credits: 1-4

Material not normally covered in regular course offerings. May be repeated.

CS 898 - Master's Project

Credits: 3

CS 899 - Master's Thesis

Credits: 1-6

May be repeated up to a maximum of 6 credits. Cr/F.

CS 900 - Graduate Seminar

Credits: 1

Regularly scheduled seminars presented by outside speakers, UNH faculty, and graduate students. Topics include reports of research ideas, progress, and results. Cr/F.

CS 920 - Advanced Operating Systems

Credits: 3

This course covers techniques for formally analyzing various fundamental concepts and mechanisms which form the basis of the design of advanced operating systems, including distributed, database, and multiprocessor operating systems. Topics covered include synchronization, mutual exclusion, distributed algorithms, security, fault-tolerance, and distributed resource management. Prereq: operating system fundamentals or equivalent.

CS 925 - Advanced Computer Networks

Credits: 3

Design and analysis of computer networks. Modeling and performance evaluation, queuing theory applied to computer networks. Traffic flow management and error control. Routing algorithms and protocols. Switch and router architectures. Selected issues in high-speed network design. Optical networks. Prereq: CS 825 or equivalent.

CS #931 - Planning for Robots

Credits: 3

Students read research papers and perform a researh project pertaining to planning algorithms for autonomous robots. The main student deliverable is a conference-style paper reporting on the project. Projects may be done in teams and can be demonstrated on physical or simulated robots. Prior exposure to algorithms and artificial intelligence is helpful but not required. Graduate students from other departments are welcome but should consult with the instructor before enrolling.

CS 980 - Advanced Topics

Credits: 3

CS 981 - Advanced Topics in Database Systems

Credits: 3

CS 986 - Advanced Topics in Formal Specification and Verification

Credits: 3

This course explores more thoroughly some of the material introduced in CS 845. It focuses on concurrent and reactive systems and on temporal logics. Topics include safety and liveness properties, asynchronous communication, and compositional reasoning. Support tools, like interactive theorem provers and model-checkers, are presented and used in class. Prereq: introduction to formal specification and verification. May be repeated up to a maximum of 6 credits.

CS 988 - Advanced Topics in Computer Graphics

Credits: 3

CS 989 - Advanced Topics in Algorithms

Credits: 3

CS 998 - Independent Study

Credits: 1-6

CS 999 - Doctoral Research

Credits: 0

Cr/F.