• About the BA Major

    About the BA Major

    The goal of the BA degree in Computer Science (BACS) is to educate students so they can develop a deep understanding of computing and critical thinking skills that will allow them to pursue a wide variety of possible careers, including an opportunity to become academic, cultural, and industrial leaders in areas that integrate the arts and sciences with computing.

    Computer Science is the study of information processes. Computer scientists learn how to describe information processes, how to reason about and predict properties of information processes, and how to implement information processes elegantly and efficiently in hardware and software. The Computer Science curriculum concentrates on developing the deep understanding of computing and critical thinking skills that will enable graduates to pursue a wide variety of possible fields and to become academic, cultural, and industrial leaders. The core curriculum focuses on developing methods and tools for describing, implementing, and analyzing information processes and for managing complexity including abstraction, specification, and recursion. Computing connects closely with a wide range of disciplines including, but not limited to, the visual arts, music, life sciences including biology and cognitive science, the physical sciences, linguistics, mathematics, and the social sciences. The Computer Science major provides students with a strong foundation in computer science, combined with courses in arts, humanities, and sciences, in order to develop broad understanding of other areas and their connections to computing.

    Faculty: The Computer Science department has fifty-one faculty members. Our faculty is strongly committed to teaching as well as conducting world-class research. Faculty interests span major areas of computer science with particular strengths in algorithms, artificial intelligence, computer architecture, computer vision, cyber-physical systems, machine learning, programming languages, security, sensor networks, software engineering, and theory.

    Declaring a BA Major

    For information on how to declare a BA Major in Computer Science, please visit our Major and Minor Declaration page.

    More Information

    For information about the major, or to be added to an email list for further announcements, contact Tom Horton (horton@virginia.edu), Director of the Interdisciplinary Major in Computer Science.

    The information contained on this website is for informational purposes only.  The Undergraduate Record and Graduate Record represent the official repository for academic program requirements. These publications may be found at:

    Undergraduate Record: www.virginia.edu/registrar/catalog/ugrad.html 
    Graduate Record: www.virginia.edu/registrar/catalog/grad.html

  • BS vs. BA

    The Computer Science department offers two Computer Science degrees: the Interdisciplinary Major in Computer Science degree offered through the College of Arts & Sciences (BACS), and the Bachelor of Science in Computer Science degree offered through the School of Engineering and Applied Sciences. In addition to the two Computer Science degrees, we also offer a Bachelor of Science in Computer Engineering degree which is jointly administered with the Electrical and Computer Engineering Department .

    The main differences between the two Computer Science degrees are:

    1. The BACS degree is in the College of Arts & Sciences; the BSCS is in the School of Engineering and Applied Science. This means the degrees have different general requirements. The general requirements for the College of Arts & Sciences are the competency requirements (see the Undergraduate Record for details). For example, the traditional option for these includes two writing requirements, a foreign language, and area requirements in natural science and mathematics, social sciences, humanities, and historical studies. The general requirements for the School of Engineering and Applied Sciences include mathematics, chemistry, physics, technical electives, humanities electives, and science, technology, and society courses (see the curriculum for details). To enroll in the BACS major, students must be enrolled in the College of Arts & Sciences. To enroll in the BSCS major, students must be enrolled in the School of Engineering and Applied Science.
    2. Students in the BACS degree first take the CS1110-CS2110. After completing the first two courses, students are prepared for the same courses, and both BACS and BSCS are required to take these courses: CS2102, CS2150, CS3330, and CS4102.
    3. BSCS students (starting after Summer 2019) are required to take CS2330 (Digital Logic Design), CS3102 (Theory of Computation), CS3240 (Advanced Software Development Techniques), and CS4414 (Operating Systems).
      The BACS degree requires students to take one of these four courses: CS 3102 (Theory of Computation), CS 3240 (Advanced Software Development), CS 4414 (Operating Systems), or CS 4610 (Programming Languages).

    4. Both degrees require additional courses be taken as CS electives, which are CS courses at the 3000-level or above that are in addition to a degree's required courses described above. The BACS degree requires 4 CS elective courses (12 credits), while the BSCS requires 5 courses (15 credits).

    5. The BACS degree requires four integration electives, which are not part of the BSCS degree. The integration electives are courses in other departments that have strong connections with computing. Click here or see below for a list of pre-approved integration electives.

    6. The BSCS degree (like all Engineering School degrees) requires a fourth-year thesis. This involves taking STS 4010 (in which students write a thesis proposal) and STS 4020 (in which students complete a thesis report), and working with a technical advisor on a thesis project. BACS students are not required to complete a thesis, but may enter the distinguished majors program. To complete a distinguished major, a BACS student must complete a fourth year thesis project that is approved by two readers.
  • Curriculum


    To complete the BA in Computer Science, students must satisfy the pre-requisites, then complete 27 credits of CS coursework as well as 12 credits of related non-CS coursework as described below.

    A student must also meet the COLLEGE COMPETENCY AND AREA REQUIREMENTS.  Also, note that that one required course, CS4102, has a math prerequisite of APMA 1090 or MATH 1210 or MATH 1310 (or equivalent coursework in high school).


    To be accepted into the major, students must satisfy the following pre-requisites. Coursework used to satisfy these must have a grade of C+ or higher.

    • An introductory computer science course, such as CS 1110, CS 1111, CS 1112, CS 1113 or CS 1120.
    • CS 2110, Software Development Methods, or an equivalent.


    Required CS Courses (15 credits)

    • CS2102: Discrete Mathematics 
      Introduces discrete mathematics and proof techniques involving first order predicate logic and induction. Application areas include sets (finite and infinite), elementary combinatorial problems, and finite state automata. Development of tools and mechanisms for reasoning about discrete problems. 
      Prerequisite: CS1110, CS1111, CS1112, or CS1113
    • CS 2150: Program and Data Representation
      Introduces programs and data representation at the machine level. Data structuring techniques and the representation of data structures during program execution. Operations and control structures and their representation during program execution. Representations of numbers, arithmetic operations, arrays, records, recursion, hashing, stacks, queues, trees, graphs, and related concepts.
      Prerequisite: CS 2110 and CS 2102 with grades of C- or higher.
    • CS 3330: Computer Architecture
      Includes the organization and architecture of computer systems hardware; instruction set architectures; addressing modes; register transfer notation; processor design and computer arithmetic; memory systems; hardware implementations of virtual memory, and input/output control and devices. 
      Prerequisite: CS2150 with a C- or higher
    • CS 4102: Algorithms 
      Introduces the analysis of algorithms and the effects of data structures on them. Algorithms selected from areas such as sorting, searching, shortest paths, greedy algorithms, backtracking, divide- and-conquer, and dynamic programming. Data structures include heaps and search, splay, and spanning trees. Analysis techniques include asymptotic worst case, expected time, amortized analysis, and reductions between problems.
      Prerequisite: CS 2102 and 2150 with grades of C- or higher, and APMA 1090 or MATH 1210 or MATH 1310
    • One of the following four courses: CS 3102 (Theory of Computation), CS 3240 (Advanced Software Development), CS 4414 (Operating Systems), or CS 4610 (Programming Languages). See course descriptions in the Undergraduate Record for pre-requisites


    CS Elective Courses (12 Credits)

    These are CS courses at the 3000-level or above, in addition to the required courses listed above. At most 3 credits of CS 4993 (Directed Independent Study) can be counted towards this requirement. CS 4980 and CS 4998 cannot be counted towards this requirement.


    Integration Electives (12 Credits)

    These are non-CS courses that contribute to this program of study by exploring applications of computing to arts and sciences fields in a significant way or by providing fundamental computing depth and background. Integration electives are courses offered by departments in the College of Liberal Arts and Sciences. The list of approved courses is available in the next section of this page.


  • Integration Electives

    Integration Electives

    BACS students are required to complete a sequence of four integration electives. Integration electives are courses typically offered by departments other than Computer Science, and should either provide fundamental computing depth and background or explore applications of computing to arts and sciences fields.

    Below is a list of the courses that are approved as integration electives. This list is not meant to be exhaustive, and you may find a course that is not on the list that appears to satisfy the goals of an integration elective. PLEASE NOTE: We are in the process of updating our approved class list and this website. Once you have been declared as a BACS major, these approved classes ought to automatically be updated in SIS. If they are not, or if you have found a class that is not on this list, then you can reach out to us regarding the Integration Elective Petition/Exception process.


    American Studies

    • AMST 3463: Language & New Media



    • ANTH 3171: Culture of Cyberspace: Digital Fluency for an Internet-Enabled Society
    • ANTH 3490: Language and Thought


    Studio Art

    • ARTS 2220: Introduction to New Media I
    • ARTS 2222: Introduction to New Media II
    • ARTS 3220: Intermediate New Media 
    • ARTS 3222: Intermediate New Media II
    • ARTS 4220: Advanced New Media I
    • ARTS 4222: Advanced New Media II



    • BIOL 4230: Bioinformatics and Functional Genomics



    • CHEM 3240: Coding in Matlab/Mathematica with Applications



    • DRAM 2110: Lighting Technology
    • DRAM 2210: Scenic Technology
    • DRAM 2240: Digital Design: Re-making and Re-imagining
    • DRAM 3825: Media Design Studio



    • ECON 3720: Econometric Methods 
    • ECON 4010 Game Theory
    • ECON 4020: Auction Theory and Practice
    • ECON 4720: Econometric Methods


    English Writing & Rhetoric

    • ENWR 2640: Composing Digital Stories and Essays
    • ENWR 3640: Writing with Sound


    Environmental Science

    • EVSC 3020: GIS Methods
    • EVSC 4010: Introduction to Remote Sensing
    • EVSC 4070: Advanced GIS



    • HIST 2212: Maps in World History
    • HIUS 3162: Digitizing America



    • LING 3400: Structure of English


    General Linguistics

    • LNGS 3250: Intro to Linguistic Theory



    • MATH 3100: Intro Mathematical Probability
    • MATH 3120: Intro Mathematical Statistics
    • MATH 3315: Advanced Linear Algebra and Differential Equations
    • MATH 3350: Applied Linear Algebra
    • MATH 3351: Elementary Linear Algebra
    • MATH 4080: Operations Research
    • MATH 4300: Elementary Numerical Analysis

    Media Studies

    • MDST 2010: Introduction to Digital Media
    • MDST 3050: History of Media
    • MDST 3102: Copyright, Commerce and Culture
    • MDST 3404: Democratic Politics in the New Media Environment
    • MDST 3500: Comparative Histories of the Internet
    • MDST 3701: New Media Culture
    • MDST 3702: Computers and Languages
    • MDST 3703: Digital Liberal Arts
    • MDST 3704: Games and Play
    • MDST 3750: Money, Media and Technology
    • MDST 3751: Values, Value, and Valuation
    • MDST 3755: Social Media and Society
    • MDST 4101: Privacy & Surveillance
    • MDST 4700: Theory of New Media
    • MDST 4803: Computational Media



    • MUSI 2350: Technosonics: Digital Music & Sound Art Composition
    • MUSI 2390: Intro to Music & Computers
    • MUSI 3390: Intro to Music & Computers
    • MUSI 4535: Interactive Media
    • MUSI 4540: Computer Sound Generation
    • MUSI 4543: Sound Studio
    • MUSI 4545: Computer Applications in Music
    • MUSI 4610: Sound Synthesis
    • MUSI 4600: Performance with Computers



    • PHIL 1410: Forms of Reasoning
    • PHIL 1510: Ethics of Computing
    • PHIL 2330: Computers, Minds and Brains
    • PHIL 2340: The Computational Age
    • PHIL 2420: Introduction to Symbolic Logic



    • PHYS 2660: Fundamentals Scientific Computing



    • PSYC 2150: Introduction to Cognition
    • PSYC 2200: Survey of the Neural Basis of Behavior
    • PSYC 2300: Introduction to Perception
    • PSYC 4110: Psycholinguistics
    • PSYC 4111: Language Development & Disorders
    • PSYC 4125: Psychology of Language
    • PSYC 4150: Cognitive Processes
    • PSYC 4200: Neural Mechanisms of Behavior
    • PSYC 4300: Theories of Perception
    • PSYC 4400: Approaches to Quantitative Methods in Psychology
    • PSYC 4682: Mobile Technology in Mental Health Research



    • STAT 1100: Chance: Intro to Statistics
    • STAT 1120: Intro to Statistics
    • STAT 2020: Statistics for Biologists
    • STAT 2120: Intro to Statistical Analysis
    • STAT 3010: Statist Computing & Graphics
    • STAT 3080: From Data to Knowledge
    • STAT 3120: Intro to Mathematical Statistics
    • STAT 3220: Introduction to Regression Analysis
    • STAT 3240: Coding in Matlab/Mathematica with Applications
    • STAT 4220: Applied Analytics for Business
    • STAT 4260: Databases (only if CS 4750 has not been taken)
    • STAT 4630: Statistical Machine Learning


    In recent years, we have approved petitions for the following special topics courses, but they would not be included in the official list or encoded in SIS until they are given permanent course numbers. 

    • AAS: Digital Caribbean Studies
    • CHEM: Intro to Computational Bio
    • ECON: AI & the Future of Work
    • ENSP: Hacking for Humanists
    • HIST: Digital History
    • MDST: Internet, Propaganda, and the "Dark Web"
    • MDST: Critical Game Design
    • MDST: Politics of Video Games
    • MUSI: Computer Applications in Music
    • MUSI: Interactive Media
    • MUSI: Sound Synthesis
    • PHIL: Minds, Machines, and Persons
    • PLPT: Digital Political Theory
    • PSYC: Mobile Sensing and Health
    • RELG: Gods, Humans, Robots
    • SOC: Networks & Society
    • STAT: Data Analytics and Decision Making
  • Distinguished Majors Program

    Distinguished Majors Program

    Bachelor of Arts Computer Science majors who have completed 18 credit hours towards their major may apply to the Distinguished Majors Program.

    Students who are accepted must complete a report based on two semesters of research. The Distinguished Majors Program features opportunities for students and advisors to collaborate on creative research; it is not a lock-step program with strict content requirements, but an opportunity to work closely with a professor on a project that is interesting and exciting to you.

    The Distinguished Majors Program is not directly comparable to a SEAS Senior Thesis or Capstone Project. Compared to the SEAS requirements, there are few formal guidelines. Instead, the DMP focuses on a creative student research project as advised and approved by an advisor.

    Upon successful completion of the program, students will likely be recommended for a baccalaureate award of DistinctionHigh Distinction, or Highest Distinction. According to College rules, to earn a Distinguished Major, students must have a cumulative GPA of 3.4 or better.

    For more information on the DMP, contact the
    DMP Director: David Evans (https://www.cs.virginia.edu/evans/office, evans@virginia.edu).

    Distinguished Majors Program Requirements

    Students applying to the DMP must have completed 18 credit hours towards their Computer Science major by the end of the semester in which they apply. Students typically apply during the Spring semester of their third year, but it is possible to apply earlier.

    The 18 credit hours can can come from any course used to fulfill the “Major Subject Requirements”, “Computing Electives” or “Integration Electives” of the Interdisciplinary Major in Computer Science Curriculum. (Exceptions to the 18 credit hours rule may be granted at the discretion of the Distinguished Majors Program Director.)

    In addition to the normal requirements for the computer science major, they must register for two semesters of supervised research (CS 4998 for 3 credits each semester). Students may apply to the DMP before completing this supervised research, but students must complete the supervised research to complete the DMP. Based on their independent research, students must complete, to the satisfaction of their advisor and the Distinguished Major Program Director, a project at least one month prior to graduation.

    Please note: The CS 4998 DMP credits do not apply towards the credit hours required for the major. That is, they cannot be used to fulfill any requirement listed on the BACS curriculum.

    Joining the DMP

    Application Deadline: Students must apply by the third semester prior to graduation. Spring graduates should submit their applications in by 29 March of the year before graduation. Winter graduates, must have their applications in by 29 October of the year before the winter graduation. (If these deadlines are missed, students can still join the DMP at the discrection of the DMP Director.)

    Note that applying to the program occurs relatively early in the research process. It is not necessary to have a fully formed research idea to apply for the DMP, although it is expected that you have found a research advisor to work with. It is not necessary to have a second reader identified when you apply to join the DMP.

    Students seeking to enter the DMP should complete the following steps:

    1. Find a research advisor.

    Students must work with a research advisor on their DMP project, and should work with their research advisor to define a DMP project. The research advisor is typically a member of the Computer Science faculty at UVa. Exceptions to this may be granted at the discretion of the DMP Director, and it is often suitable to have an advisor from outside UVA or from another department. Students are expected to meet regularly (typically every week or every other week) with their research advisor throughout the course of the project.

    Many students become involved in research well before the DMP application process — some as early as their first semester at UVA. The most important preparation for students interested in the DMP is becoming involved in research early. Students are encouraged to start early. It is not too early to start talking to professors about research in your first semester, and one of the best ways to get involved in a research group is to impress a professor with what you do in class.  

    If you have an idea for a project you would like to do, but don't have a research advisor, contact the DMP Director to meet to discuss the areas you are interested in working in and for advice on finding a potential advisor. It is a good idea to do this early, especially to increase the likelihood you'll be able to find a summer research position.

    2. Decide on a project and write a research proposal.

    The student and research advisor should discuss the proposed research together, and work together to develop the research proposal.

    The student should write a brief proposal for the project including a (1) clear motivation for the work (why this problem is worth working on and hasn't been solved yet), (2) a summary of related work, (3) a description of what you plan to do and (4) how you will evaluate it. A DMP project should be a research project that seeks to answer some unknown research question; it is not enough to just build some interesting software or study an area in depth. A DMP student should work with her research advisor to develop the project proposal, and the research advisor should review and agree to the proposal.

    The project proposal need not be very detailed as long as the essential elements are in place. There are no formal guidelines (e.g., length, format, etc.) for what constitutes an acceptable project, it is up to the research advisor and the DMP Director to agree that a proposed project is satisfactory. Our expectation is that most DMP projects will result in a paper that could be published in a research conference or workshop. Alternative goals could also be appropriate, but should be discussed with the research advisor and DMP director.

    3. Enlist a second reader (optional to do this before applying).

    DMP projects must have a second reader, who, in addition to the research advisor and DMP director, will be responsible for evaluating the project. The second reader agrees to read the DMP report and provide and evaluation. In most cases, we hope the second reader will also be involved in other phases of the work, providing additional expertise to the DMP researcher.

    Your research advisor may be able to help you find a second reader based on your interests and your project proposal. It is not necessary to have the second reader identified when you submit the DMP application, but is important to find a suitable second reader early in the research. The second reader should be a faculty member most suited to assess the quality and context of your work. If appropriate, the second readers can be a faculty member from another university or from another department at UVA. However, CS faculty members are also acceptable.

    4. Submit the DMP application form and proposal.

    Print out and complete the DMP Application. The application includes a very brief (expected to be no more than one page) research proposal describing your DMP project, which can be submitted as either plaintext or an attached PDF file. After submitting the form, you should receive a notification regarding acceptance within one week (so feel free to follow-up with the DMP Director, evans@virginia.edu, if you do not receive a response by then).


    In general, a Distinguished Majors Program project should be the creative research output of a single DMP student, guided by faculty advisors. In practice, students may, for example, work with a research group or a graduate student in the completion of a project. The DMP report should reflect and represent the student’s individual work, as guided by faculty advisors. The extent to which collaborative work (e.g., a peer-reviewed publication on which two students are co-authors) should be included is left to the discretion of the advisor and DMP Director. So long as the DMP student played an important and clear role in creative aspects of the research and in writing the paper, it is often appropriate to use a co-authored paper as the DMP report, and not necessary to write a separate report from a paper that is published or submitted to a research conference or journal. Since the DMP designation is for individual students, however, if the DMP report is a co-authored paper, it must be clear in the research advisor's evaluation what the DMP student's role was and how she contributed to the research and writing.

    Completing the DMP

    To successfully complete the DMP, students must write a research paper describing their work.

    There are no specific length or formatting requirements for the DMP paper, and it is up to the student and research advisor to decide on this. In most cases, we recommend following the formatting and length requirements of a Computer Science research conference. The research advisor should specify any requirements for the DMP report, in consultation with the DMP director for any unusual situations.

    The DMP report must be completed and submitted at least thirty days prior to graduation (for May 2020 graduation, the deadline is 16 April 2020). DMP students should submit their DMP paper as both a PDF attachment to an email and a paper copy to the DMP director (evans@virginia.edu), their advisor and second reader, by the required deadline (30 days before graduation). The DMP director will follow-up with the student's advisor and second reader to obtain the necessary evaluations.

    Evaluation. Students will usually receive a recommendation for a baccalaureate award of DistinctionHigh Distinction or Highest Distinction upon successful completion of the DMP. The Highest Distinction designation is reserved for work that is of sufficient quality and importance to be published in a significant research venue. Eligible students who complete the program receive baccalaureate awards based on the Distinguished Majors Program Director’s assessment of their thesis advisor and second reader evaluations. This award will be visible on the student’s diploma. 

    Students who fall below a 3.4 cumulative GPA are not eligible to be Distinguished Majors. The 3.4 cumulative GPA is a College of Arts and Sciences school requirement, and it cannot be waived. There is no penalty beyond not receiving the award for students who are no longer eligible.

    Reviews will be completed and the DMP Director's recommendation will be sent to the Chair of the University Committee on Special Programs two weeks before graduation.

  • People



    Tom Horton


    David Evans

    Founding Director & Director of DMP

    Worthy Martin

    Former Director

    Tina Hittinger

    Senior Student Services Coordinator


    Rice Hall, Room 526




    BA Computer Science Steering Committee


    Tom Horton

    Associate Professor of Computer Science

    Jim Cohoon

    Associate Professor of Computer Science

    Jeff Holt

    Professor & Interim Chair of Statistics, Mathematics

    David Leblang

    J. Wilson Newman Professor of Governance and Chair, Politics

    David Germano

    Professor, Religious Studies


    BA Computer Science Founding Committee (2006)

    David Evans, committee chair

    Associate Professor, Computer Science

    J. Milton Adams

    Professor, Biomedical Engineering & Vice Provost of Academic Programs

    David Golumbia

    Assistant Professor, Media Studies, English and Linguistics

    Jeff Holt

    Associate Professor, Mathematics and Chair of Statistics

    George Hornberger

    Professor, Environmental Studies and Associate Dean for the Sciences

    Thomas Horton

    Associate Professor, Computer Science

    Greg Humphreys

    Assistant Professor, Computer Science

    Worthy Martin

    Associate Professor, Computer Science and Associate Director, Institute for Advanced Technology in the Humanities

    Gary McGraw

    CLAS BA Philosophy 1988 and Chief Technology Officer, Cigital, Inc.

    Dennis Proffitt

    Commonwealth Professor of Psychology and Director, Cognitive Science program

    Judith Shatin

    William R. Kenan, Jr. Professor of Music and Director, Virginia Center for Computer Music

    Mary Lou Soffa

    Owen R. Cheatham Professor and Chair of Computer Science (2004-2012)

    Portman Wills

    CLAS Echols 2002

  • Awards


    CRA Outstanding Undergraduate Researchers

    The CRA Outstanding Undergraduate Researchers Award is the premier national research award that recognized undergraduate research in Computer Science, given to students at North American universities by the Computing Research Association.


    Jonathan Burket (BACS 2013), Honorable Mention
    Matthew Weber, Honorable Mention


    Peter Chapman (BACS 2012), Runner-Up
    Jiamin Chen (BACS 2012), Honorable Mention
    Virginia Smith (BACS 2012), Honorable Mention


    Aleksander Morgan (BACS 2011, now at UVa Math), Honorable Mention


    Ethan Fast (BACS 2011, now at Stanford University), Honorable Mention
    Rachel Lathbury (BACS 2010, now at University of Pennsylvania), Honorable Mention


    Rachel Miller (BACS 2009, now at MIT), Finalist

    NSF Graduate Research Fellowships

    The National Science Foundation's Graduate Research Fellowships recognize outstanding graduate students and provides up to three years of funding to support a student's graduate work (over $100,000 total). Students may apply for NSF Graduate Research Fellowships as final-year undergraduates, or in their early years in a graduate program.


    Brielin Brown (BACS 2011, now at UC Berkeley)


    Sara Alspaugh (BACS 2009, now at UC Berkeley)
    Rachel Miller (BACS 2009, now at MIT)


    The information contained on this website is for informational purposes only.  The Undergraduate Record and Graduate Record represent the official repository for academic program requirements. These publications may be found at:
    Undergraduate Record: www.virginia.edu/registrar/catalog/ugrad.html 
    Graduate Record: www.virginia.edu/registrar/catalog/grad.html