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Professor John Dooley talks with students during the Sumo Robot competition. #

Academics > Majors & Minors > Computer Science

Courses

Contact

Jaime Spacco

Associate Professor & Chair of Computer Science

2 East South Street

Galesburg, IL 61401-4999

309-341-7956

jspacco@​knox.edu

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Requirements

Requirements for the major
11 credits as follows:

  • Introductory courses: CS 141, CS 142
  • Core Computer Science courses: CS 205, CS 208, CS 214, CS 220, and CS 292
  • Support course: MATH 175 or MATH 300
  • Advanced study: Three additional CS courses at the 300 level. MATH 311 can substitute for one of these
  • Capstone experience: After completion of CS 292, students must engage in a capstone experience resulting in a written report and an oral presentation. Students may select from
    1. completing a College Honors project
    2. completing a one-term senior research seminar (CS 399), which may also count as an elective
    3. completing CS 322 Software Engineering, which may also count as an elective
    4. completing a full-credit independent study or topics course, which may also count as an elective.

The department chair must certify fulfillment of the capstone experience requirement.

With permission of the chair, up to two credits in related studies outside the department may be counted toward electives in the major.

Requirements for the minor

5 credits as follows:

  • CS 141 (Introduction to Computer Science) or CS 147 (Introduction to Scientific Computing)
  • CS 142 (Program Design and Methodology)
  • Three credits above the 100-level, of which at least one must be at the 300-level. With permission of the chair, one of these may be substituted with a related course from a different department

Course Descriptions

CS 127. Computing, Technology, and Society. (1)

An overview of computer science. Topics include history and future of computing, robotics, computers in fiction, computer hardware, artificial intelligence, networking and the World-Wide-Web, social and ethical implications of technology, and an introduction to structured problem solving in a high-level programming language. Designed for non-majors. Not open to students with credit in CS 142 or above; W; Offered occasionally; Staff;

CS 141. Introduction to Computer Science. (1)

An introduction to the fundamental principles of computer science focusing on problem solving and abstraction techniques. Students will learn to break down problems and specify solutions at a level of detail that lets them be executed by a machine. Specific concepts taught include control structures, data types, and object-oriented design. The course is currently taught using Java. MNS; QSR; QL; Offered every fall and winter; Staff;

CS 142. Program Design and Methodology. (1)

A continued study of principles of computer science and programming. This course teaches students how to design increasingly complex programs in a manageable way, using abstract data structures, data encapsulation, and other software engineering concepts. It also addresses some of the classic algorithms in computer science and begins studying how to analyze their complexity. This course is currently taught using Java. MNS; QSR; Prerequisite(s): CS 141 or permission of the instructor; QL; Offered every winter and spring; Staff;

CS 160. Programming Practice. (1/2)

Individual instruction in programming and laboratory skills. The student will implement several programming projects over the course of the term, regularly meeting with the supervising faculty member. Projects will be appropriate to the level of the student. Prerequisite(s): CS 141; May be repeated once for credit; Staff;

CS 180. Programming Language and Tools Workshop. (1/2)

Students will study programming languages and development environment topics. This course will be offered as needed to support the Computer Science curriculum. Programming languages offered may include, but are not limited to: Lisp, Scheme, Prolog, C, Python, Perl, C++. Tools offered may include Linux/Unix system administration, and shell programming. Prerequisite(s): CS 142 or permission of the instructor; Version CS 180F Programming Challenges is graded on an S/U basis. May be repeated for credit using different languages; Staff;

CS 205. Algorithm Design and Analysis. (1)

Advanced data structures and analysis of algorithms and their complexity. Trees, graphs, hashing, analysis of sorting algorithms, divide and conquer algorithms, dynamic programming, development of complex abstract data types typically with an object-oriented approach, an introduction to complexity theory. Prerequisite(s): CS 142 and MATH 175, or permission of the instructor; QL; Offered annually, typically in the winter; D. Bunde;

CS 208. Programming Languages. (1)

A critical study of the design issues that underlie modern programming languages. Students will study and use languages from a variety of programming paradigms, including functional, logic, imperative, and object­oriented. Prerequisite(s): CS 142 or permission of the instructor; Offered every year; D. Bunde;

CS 214. Introduction to Computing Systems. (1)

An introduction to low-level programming and computer hardware, with the goal of understanding how features of the hardware and operating system affect the performance of programs. Introduces assembly language and C. Topics include caching, memory management, and concurrency. Prerequisite(s): CS 142 or permission of the instructor; Offered every year; D. Bunde;

CS 220. Applied Data Structures. (1)

Solve real-world problems by applying the key data structures covered in CS 142 to real­world data. Some possible problems to solve include detecting likely plagiarism in a large collection of documents, evaluating possible outcomes in board games using graphs, determining the likelihood an email message is “spam”, and building a data model for a database. Prerequisite(s): CS 142 or permission of the instructor; Offered every year; J. Spacco;

CS 248. Teaching Assistant. (1/2 or 1)

Prerequisite(s): Permission of instructor; May be graded S/U at instructor's discretion; Staff;

CS 292. Software Development and Professional Practice. (1)

Covers topics in software development essential to the design and development of larger software projects. Topics include requirements management, design, code construction, testing, concurrency, parallel programming and project management. Students typically work in teams on a medium-sized software project. Issues of social responsibility, intellectual property, copyright, and assessing the risks in computer systems are discussed. Prerequisite(s): Any 200-level Computer Science course.; O; W; QL; Offered annually; M. McGill;

CS 295. Special Topics. (1/2)

Courses offered occasionally to students in special areas of Computer Science not covered in the usual curriculum. Staff;

CS 303. Computer Graphics. (1)

Mathematical theories, algorithms, software systems, and hardware devices for computer graphics. Translation, rotation, scaling, projection, clipping, segmented display files, hidden line and surface elimination, surface texturing, 2-D and 3-D graphics, and input of graphical data. Prerequisite(s): Any CS course numbered 205 or higher; QL; Typically offered alternate years; Staff;

CS 305. Operating Systems. (1)

Advanced management of computer resources such as storage, processors, peripheral devices, and file systems. Storage allocation, virtual memory, scheduling algorithms, synchronization, mutual exclusion, deadlock, concurrent programming, processes, inter-process communication, protection, operating system organization. Prerequisite(s): CS 214; QL; Offered occasionally; Staff;

CS 308. Networks and Distributed Systems. (1)

Covers advanced topics in computer/data networking. Topics include media types, network architectures, common networking practices and components, network design fundamentals, network management technologies and practices, and an introduction to various service and maintenance protocols (IP, DNS, DHCP, WINS, etc.). Prerequisite(s): CS 214; QL; Offered occasionally; Staff;

CS 309. Parallel Programming. (1)

Advanced study of principles and techniques for parallel programming. Topics include load balance, dependencies, overhead, scaling, synchronization, and heterogeneity. Students will express parallelism using a variety of libraries and languages, learning approaches that provide different combinations of abstraction and programmer control in both shared and distributed memory environments. Prerequisite(s): CS 214 or permission of the instructor; Typically offered alternate years; D. Bunde;

CS 317. Artificial Intelligence. (1)

A survey of topics in the branch of computer science concerned with creating and understanding "intelligent" computer systems, including advanced search techniques and heuristics, knowledge representation, expert systems, natural language processing, machine learning, and game playing. Topics will also include the study of the nature of intelligence and the representation of intelligent machines in fiction. Prerequisite(s): CS 142 or permission of the instructor; QL; Typically offered alternate years; J. Spacco;

CS 320. Database Systems. (1)

Theory and management of database management systems, including database models, design principles, data structures and query organization for efficient access, query languages, database-interface applications, normalization and relational concepts such as views, procedural database programming and referential integrity. Prerequisite(s): CS 220; QL; Typically offered alternate years; J. Spacco;

CS 322. Software Engineering. (1)

Building large-scale computing systems uses requirements analysis, project planning, extensive documentation, cooperative teamwork, and design techniques to decompose a system into independent units. The course covers all the phases of large-scale system development: software process, estimation and scheduling, configuration management, and project management. Students typically work together in teams to build a term-long project, gaining practical experience with developing larger systems. Prerequisite(s): CS 292; O; W; QL; Typically offered alternate years; M. McGill;

CS 330. Cryptography and Computer Security. (1)

With the increasing ubiquity of computers and computer networks, issues of privacy and security are becoming increasingly important for computing professionals. This course introduces students to a number of related areas in computer security. Topics covered include classical cryptography, public-key cryptography, block and stream ciphers, file system security, network security, Internet and web-based security, and design principles behind cryptographic systems. In addition, the course examines social, political, legal, and ethical issues related to security systems. Prerequisite(s): CS 214; O; QL; Typically offered alternate years; Staff;

CS 340. Human-Computer Interaction. (1)

As computing becomes more pervasive, there is a growing need to understand the point where humans and machines connect. This course is a survey of topics that arise from examination of this connection. Topics include user interface design, usability analysis, scientific visualization, novel interfaces, and an exploration of what happens when it all goes terribly wrong. Prerequisite(s): CS 220; O; QL; Offered occasionally; M. McGill;

CS 348. Teaching Assistant. (1/2 or 1)

Prerequisite(s): Permission of instructor; May be graded S/U at instructor's discretion; Staff;

CS 360A. Startup Term: Planning, Teamwork, Execution. (1)

Students work in terms on an entrepreneurial startup project. Teams must produce a business plan and, ideally, an alpha version of a product. This course encompasses how well each team member handles the "little things" necessary for a successful startup venture: prioritizing tasks, meeting deadlines, staying on schedule, overcoming problems as they arise, applying theoretical material from 350B and 360C to their startup endeavor, etc. Prerequisite(s): Sophomore standing and acceptance of Startup Term application; Cross Listing: IDIS 360A; Typically offered alternate years; J. Spacco; E. Spittell;

CS 375. Computing Models and Complexity. (1)

This course examines the fundamental question "What can be computed?" by looking at different models of computing, including finite automata, regular expressions, context-free grammars, and Turing machines. It also considers time and space complexity for computable problems with a particular focus on computational lower bounds and NP-completeness. Prerequisite(s): CS 142 and MATH 175 or permission of the instructor; Offered alternate years; D. Bunde;

CS 395. Special Topics. (1/2 or 1)

Courses offered occasionally to students in special areas of Computer Science not covered in the usual curriculum. Staff;

CS 399. Research Seminar in Computer Science. (1)

An advanced study of a special topic in computer science not substantially covered in the regular curriculum. Resources are usually drawn from the current computing literature. Emphasis is on student presentations and independent writing and research. Students submit a major paper and give a public lecture. Prerequisite(s): CS 292 and junior standing; May be taken more than once for credit but only one instance will count as an elective for the computer science major.; Staff;

CS 400. Advanced Studies. (1/2 or 1)

See College Honors Program. Staff;

Professor John Dooley and student, in a computer science class.
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Printed on Tuesday, December 12, 2017

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