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Haverford College

2011-12 Course Catalog

Natural Sciences: Computer Science, 2011-2012

DescriptionFacultyMajor RequirementsMinor RequirementsThe Computer Science Concentration for Math MajorsThe Computer Science Concentration for Physics MajorsConcentration in Scientific ComputingCoursesDepartment Homepage


Computer Science is the representation and manipulation of information—the study of the theory, analysis, design, and implementation of the data structures that represent information, and the algorithms that transform them. Computer Science is interdisciplinary, with roots in mathematics, physics and engineering, and with applications in virtually every academic discipline and professional enterprise.

Computer Science at Haverford College ( emphasizes these fundamental concepts in conjunction with depth of thought and clarity of expression. This approach is consistent with the principles of scientific education in the liberal arts. The aim is to provide students with a base of skills and capabilities which transcend short-term fashions and fluctuations in computer hardware and software. Computer Science offers a Major, a Concentration for Mathematics Majors, a Concentration for Physics Majors and a Minor. Computer Science also contributes substantially to the Concentration in Scientific Computing.

Details of these programs are given at

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Professor Steven Lindell
Associate Professor David G. Wonnacott
Assistant Professor and Lab Coordinator John P. Dougherty

Affiliated Faculty:
Professor of Mathematics Lynne Butler
J. McLain King Professor of Mathematics Curtis Greene
William H. and Johanna A. Harris Distinguished Professor of Computational Science Robert Manning
Professor of Biology Philip M. Meneely
Professor of Physics Walter Smith
Assistant Professor of Physics Peter Love

At Bryn Mawr College:
Professor Deepak Kumar
Associate Professor Douglas Blank
Assistant Professor Dianna Xu

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Major Requirements

  1. Computer Science 105 and 106.
  2. Computer Science/Math 231 (Discrete Mathematics).
  3. Computer Science 240, 245, 340 and 345.
  4. Computer Science 350 or 355 or 356.
  5. One additional 300 level course in Computer Science, and two additional courses numbered 200 or higher (or related courses in Math or Physics).
  6. Computer Science 480 project and paper.

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The Computer Science Concentration for Mathematics Majors

  1. Computer Science 105 and 106.
  2. Either Computer Science 240 or 245.
  3. Either Computer Science 340 or 345.
  4. One additional Computer Science course numbered 300 or higher.
  5. One additional Computer Science course numbered 200 or higher, or a related course in Mathematics or Physics (such as Math 203, 210, 218, 231, 235, 236, 237, 250, or Physics 316, 322).

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The Computer Science Concentration for Physics Majors

  1. Computer Science 105 and 106.
  2. Physics 316 (Electronic Instrumentation and Computers).
  3. Either Physics 322 (Solid State Physics) or Computer Science/Physics 304 (Computational Physics).
  4. Two additional courses numbered 200 or higher chosen from the Haverford or Bryn Mawr Computer Science programs.

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The Concentration in Scientific Computing

For Math, Physics, Chemistry, Biology, Economics and Astronomy majors:
See separate section in this catalog.

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Minor Requirements

  1. Computer Science 105 and 106.
  2. Computer Science/Math 231 (Discrete Mathematics).
  3. Either Computer Science 240 and (355 or 356), or Computer Science 245 and 350.
  4. Either Computer Science 340 or 345.

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100 The World of Computing NA/QU

Survey of fundamental ideas in computing (user interfaces, algorithms, translation, history, Internet and Web, limits of computation, artificial intelligence, social implications, accessibility) with a weekly laboratory/discussion section and a term project to extend course concepts and demonstrate quantitative reasoning. Prerequisite: none. Does not count toward the major. Typically offered in alternate years.

101 Fluency with Information Technology NA/QU

A study of the skills, concepts and capabilities involved in the design, implementation and effective use of information technology. Using a variety of quantitative techniques, we will explore a range of uses of information technology in various fields. Does not count toward the major. Typically offered in alternate years.

105 Introduction to Computer Science NA/QU

Introduction to the intellectual and software tools used to create and study algorithms: formal and informal problem specification; problem solving and algorithm design techniques; reliability, proofs and testing techniques; program clarity, complexity and efficiency; functional and imperative paradigms; associated programming skills. Weekly programming laboratory section. Typically offered every Fall.

106 Introduction to Data Structures NA/QU

Overview of the intellectual and software tools used to create and study data structures: specification of data types; abstraction and representation; reasoning tools to study correctness and efficiency; classic data structures for collections (set, vector, list, stack, queue, tree, graph); introduction to object-orientated programming. Weekly programming laboratory section. Prerequisite: Computer Science 105 (or 110 at Bryn Mawr) or consent. Typically offered every Spring.

130 Foundations of Rigorous Thinking NA/QU

Quantitative seminar to develop reasoning skills through mathematics: logic and sets. Uses symbology for abstract objects and formal methods of computing. A transition course for non-science students who might wish to do further work in computer or cognitive science. Offered occasionally.

147 A History of Mechanized Thought NA/QU

An exploration of the history of computer and information systems, from early number systems to binary arithmetic, and from the abacus to the modern computer. Includes a laboratory which explores aspects of digital and analog computing. Offered occasionally.

187 Scientific Computing: Discrete Systems NA (Cross-listed in Biology)

A survey of computational techniques with applications in a variety of natural and social sciences, with an emphasis on problems involving discrete systems such as strings and networks. Computer programming is introduced in lecture, so no prior programming experience is required. First priority is to students who have declared a concentration in scientific computing; if space is available, freshmen and sophomores share the second highest priority, with juniors and seniors at the lowest priority. Prerequisite: One semester of any (social or natural) science is recommended. Offered occasionally.

210 Linear Optimization and Game Theory NA/QU (Cross-listed in Mathematics and Economics)

Prerequisite: Math 215 or Math 115 and concurrent registration in Math 215. Typically offered in alternate years.

215 Human Computer Interaction NA

Interaction between people and machines, with a focus on how computer interfaces can be made more convenient. Issues considered will include the study of cognitive principles, foundations of perception and guidelines for accessibility, together with safety and social implications. Prerequisite: One course in Computer Science or permission of the instructor. Offered occasionally.

235 Information and Coding Theory NA (Cross-listed in Mathematics)

This course covers the mathematical theory of the transmission (sending or storing) of information. Included will be encoding and decoding techniques, both for the purposes of data compression and for the detection and correction of errors. Prerequisite: Math 215 (may be taken concurrently). Offered occasionally.

240 Principles of Computer Organization NA

Treatment of the hierarchical design of modern digital computers: boolean logic/algebra; sequential state systems; register machines; instruction sets; memory organization; assembly language programming. Lectures cover the theoretical aspects of system architecture; labs provide implementation experience via a hardware simulator. Prerequisite: Computer Science 106 (or 206 at Bryn Mawr) or consent of instructor. Math 231 recommended. Concurrent enrollment in this and two other Computer Science lab courses requires permission of the instructor. Typically offered yearly in alternation with Bryn Mawr.

245 Principles of Programming Languages NA

Study of the design and implementation of modern programming languages: lexical and syntactic analysis; scoping mechanisms; run-time environments; implementation of structured, functional, object-oriented and concurrent programming languages. Lectures cover theoretical foundations of language design and implementation; labs provide opportunities to both use and implement language features. Prerequisite: Computer Science 106 (or 206 at Bryn Mawr) or consent. Computer Science/Math 231 strongly recommended. Concurrent enrollment in this and two other Computer Science lab courses requires permission of the instructor. Typically offered yearly in alternation with Bryn Mawr.

287 High Performance Computing NA

Introduction to parallel and distributed systems and approaches found in scientific computing, including computational and data intensive applications. Primary lab work on a cluster of Linux workstations with MPI; other architectures and approaches are also covered. Prerequisite: Computer Science 106 (or 260 at Bryn Mawr) or consent. Offered occasionally.

300 Computer Science Research Foundations NA

An introduction to research skills needed for the field of computer science, designed to prepare students for senior thesis or summer research work. Prerequisite: Course open to Junior Computer Science Majors; others by permission.

304 Computational Physics NA/QU (Cross-listed in Physics)

Prerequisite: Junior standing, Physics 213 and either Computer Science 105 or extensive experience with a programming language or consent. Typically offered in alternate years.

340 Analysis of Algorithms NA (Cross-listed in Mathematics)

Qualitative and quantitative analysis of algorithms and their corresponding data structures from a precise mathematical point of view. Performance bounds, asymptotic and probabilistic analysis, worst case and average case behavior. Correctness and complexity. Particular classes of algorithms such as sorting and searching will be studied in detail. Prerequisite: Computer Science 106. Typically offered in alternate years.

345 Theory of Computation NA (Cross-listed in Mathematics)

Introduction to the mathematical foundations of computer science: finite state automata, formal languages and grammars, Turing machines, computability, unsolvability and computational complexity. Prerequisite: Computer Science/Math 231. Typically offered in alternate years.

350 Compiler Design NA

An introduction to compiler design, including the tools and software design techniques required for compiler construction. Students construct a working compiler using appropriate tools and techniques in a semester-long laboratory project. Lectures combine practical topics to support lab work with more abstract discussions of software design and advanced compilation techniques. Prerequisite: Computer Science 245. Typically offered in alternate years.

356 Concurrency and Co-Design in Operating Systems NA

A practical introduction to the principles of shared-memory concurrent programming and of hardware/software co-design, which together underlie modern operating systems; includes a substantial laboratory component, currently using Java's high-level concurrency and the HERA architecture. Prerequisite: Computer Science 240. Typically offered in alternate years.

392 Software Development for Accessibility NA

Prerequisite: Computer Science 106 (or 206 at Bryn Mawr) or consent. Offered occasionally.

393 Physics of Computation NA

Advanced seminar convering the fundamental physical limits and potentials of computation. Prerequisite: Math 235 or Physics 303 or instructor consent. Offered occasionally.

394 Software Tools for Computer Science Research NA (Cross-listed in Mathematics)

Offered occasionally.

399 Senior Thesis NA

Taken for a half credit in both the fall and spring semesters, whose purpose is to prepare the thesis. Seminar for seniors writing theses, dealing with the oral and written exposition of advanced material. Prerequisite: Senior standing.

460 Teaching Assistant NA

Does not count toward the major.

480 Independent Study NA

The pursuit of advanced material under the direct supervision of a faculty member. Prerequisite: permission of instructor.


203 Applied Statistics
210 Linear Optimization and Game Theory
215 Linear Algebra
218 Probability and Statistics
222 Introduction to Scientific Computing
250 Combinatorial Analysis


316 Electronic Instrumentation and Computers
322 Solid State Physics


110 Introduction to Computing
120 Visualizing Information
206 Introduction to Data Structures
212 Computer Graphics
231 Discrete Mathematics
246 Programming Paradigms
250 Computational Models in the Sciences
325 Computational Linguistics
330 Algorithms: Design & Practice
355 Operating Systems
361 Emergence
371 Cognitive Science
372 Artificial Intelligence
376 Androids: Design & Practice
380 Recent Advances in Computer Science

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