CS2013-final-report

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Programming Languages (PL) Programming languages are the medium through which programmers precisely describe concepts, formulate algorithms, and reason about solutions. In the course of a career, a computer scientist will work with many different languages, separately or together. Software developers must understand the programming models underlying different languages and make informed design choices in languages supporting multiple complementary approaches. Computer scientists will often need to learn new languages and programming constructs, and must understand the principles underlying how programming language features are defined, composed, and implemented. The effective use of programming languages, and appreciation of their limitations, also requires a basic knowledge of programming language translation and static program analysis, as well as run-time components such as memory management.
PL. Programming Languages (8 Core-Tier1 hours, 20 Core-Tier2 hours) Core-Tier1 hours Core-Tier2 hours Includes Electives PL/Object-Oriented Programming 4 6 N PL/Functional Programming 3 4 N PL/Event-Driven and Reactive Programming 2 N PL/Basic Type Systems 1 4 N PL/Program Representation 1 N PL/Language Translation and Execution PL/Syntax Analysis PL/Compiler Semantic Analysis PL/Code Generation PL/Runtime Systems PL/Static Analysis PL/Advanced Programming Constructs PL/Concurrency and Parallelism PL/Type Systems PL/Formal Semantics PL/Language Pragmatics PL/Logic Programming 3 N Y Y Y Y Y Y Y Y Y Y Y Note: • Some topics from one or more of the first three Knowledge Units (Object-Oriented Programming, Functional Programming, Event-Driven and Reactive Programming) are likely to be integrated with topics in the SF-Software Development Fundamentals Knowledge Area in a curriculum’s introductory courses. Curricula will differ on which topics are integrated in this fashion and which are delayed until later courses on software development and programming languages. • Some of the most important core learning outcomes are relevant to object-oriented programming, functional programming, and, in fact, all programming. These learning outcomes are repeated in the Object-Oriented Programming and Functional Programming Knowledge Units, with a note to this effect. We do not intend that a - 156 -
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Computer Science Curricula 2013 Cur
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Computer Science Curricula 2013 Cop
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CS2013 Steering Committee ACM Deleg
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Chapter 5: Introductory Courses ...
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CC152: Computer Architecture and En
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Programming Languages and Technique
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Chapter 1: Introduction ACM and IEE
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KA subcommittee Chairs (as members
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Knowledge Areas The CS2013 Body of
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of the implications of social respo
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Manaris (College of Charleston), Sa
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Chapter 2: Principles Early in its
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novel, interesting, and effective w
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Appreciation of the interplay betwe
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to be able to communicate with, and
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● The learning outcomes and hour
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● Many strong computer-science cu
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include appropriate elective materi
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We use three levels of mastery, def
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Parallel and Distributed Computing
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select topics from Tier-2 (to inclu
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common“CS0” courses: precursor
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Tradeoffs: A programming-focused in
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Parallel Processing Traditionally,
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Chapter 6: Institutional Challenges
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Computer Science Across Campus An a
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programs do not have an explicit li
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accessible, building interdisciplin
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provide for assessing the effective
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AL. Algorithms and Complexity (19 C
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[Core-Tier2] 7. Describe various he
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Learning Outcomes: 1. Define the cl
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Architecture and Organization (AR)
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7. Evaluate the functional and timi
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AR/Interfacing and Communication [1
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Computational Science (CN) Computat
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CN/Introduction to Modeling and Sim
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CN/Processing [Elective] The proces
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CN/Data, Information, and Knowledge
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Discrete Structures (DS) Discrete s
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DS/Basic Logic [9 Core-Tier1 hours]
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DS/Graphs and Trees [3 Core-Tier1 h
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Graphics and Visualization (GV) Com
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GV/Fundamental Concepts [2 Core-Tie
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GV/Geometric Modeling [Elective] To
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GV/Visualization [Elective] Visuali
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HCI/Foundations [4 Core-Tier1 hours
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HCI/User-Centered Design and Testin
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Learning Outcomes: 1. Explain basic
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o Game engines o Mobile augmented r
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IAS. Information Assurance and Secu
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OS/Concurrency 1.5 OS/Scheduling an
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SP/Social Context 0.5 SP/Analytical
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Page 113 and 114: Learning outcomes: 1. Describe the
Page 115 and 116: Information Management (IM) Informa
Page 117 and 118: • Design of core DBMS functions (
Page 119 and 120: 3. Demonstrate use of the relationa
Page 121 and 122: IM/Physical Database Design [Electi
Page 123 and 124: • Presentation, rendering, synchr
Page 125 and 126: IS/Fundamental Issues [1 Core-Tier2
Page 127 and 128: 4. Describe over-fitting in the con
Page 129 and 130: IS/Agents [Elective] Cross-referenc
Page 131 and 132: Learning Outcomes: 1. Explain the d
Page 133 and 134: Networking and Communication (NC) T
Page 135 and 136: NC/Networked Applications [1.5 Core
Page 137 and 138: NC/Social Networking [Elective] Top
Page 139 and 140: OS/Overview of Operating Systems [2
Page 141 and 142: OS/Memory Management [3 Core-Tier2
Page 143 and 144: OS/File Systems [Elective] Topics:
Page 145 and 146: Platform-Based Development (PBD) Pl
Page 147 and 148: Learning Outcomes: 1. Design and im
Page 149 and 150: Because the terminology of parallel
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Page 155 and 156: • Topologies o Interconnects o Cl
Page 157: o Software as a service o Security
Page 161 and 162: PL/Functional Programming [3 Core-T
Page 163 and 164: o o o Enforce invariants during cod
Page 165 and 166: PL/Compiler Semantic Analysis [Elec
Page 167 and 168: • Metaprogramming: Macros, Genera
Page 169 and 170: PL/Language Pragmatics [Elective] T
Page 171 and 172: emphasize formal analysis (e.g., Bi
Page 173 and 174: Learning Outcomes: 1. Analyze and e
Page 175 and 176: Software Engineering (SE) In every
Page 177 and 178: such system are assigned to the cor
Page 179 and 180: Learning Outcomes: [Core-Tier1] 1.
Page 181 and 182: SE/Tools and Environments [2 Core-T
Page 183 and 184: SE/Software Design [3 Core-Tier1 ho
Page 185 and 186: [Elective] • Potential security p
Page 187 and 188: o o o o Code segments Libraries and
Page 189 and 190: Systems Fundamentals (SF) The under
Page 191 and 192: 2. Describe how hardware, VM, OS, a
Page 193 and 194: 2. Describe the scheduling algorith
Page 195 and 196: Social Issues and Professional Prac
Page 197 and 198: understanding of our commitment to
Page 199 and 200: Learning Outcomes: 1. Evaluate stak
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Page 203 and 204: [Elective] 8. Discuss ways to influ
Page 205 and 206: • Differences in access to comput
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and are treated as a topic geared t
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GV The storage of analog signals in
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SDF This new knowledge area pulls t
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Table B-3: Core Learning Topics and
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Table B-4: New and Expanded Core Le
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IAS Core-Tier1: • Analyze the tra
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IS NC Core-Tier2: • Translate a n
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• Describe at least one design te
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• Explain why the creation of cor
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• Use refactoring in the process
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• Apply simple algorithms for exp
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Appendix C: Course Exemplars While
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IS U. San Francisco Artificial Inte
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ACM/IEEE-CS CS2013 Course-Exemplar
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CSCI 140: Algorithms, Pomona Colleg
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AL PD advanced data structures algo
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What is the format of the course Th
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CS 256 Algorithm Design and Analysi
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and other applications including Ba
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• Data races and higher-level rac
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CS/ECE 552: Introduction to Compute
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Body of Knowledge coverage KA Knowl
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AR Assembly Level Machine Organizat
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Altruism/Collaboration/Competition,
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everyday lives, and therefore at le
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COSC/MATH 201: Modeling and Simulat
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ehaviors, simplifying assumptions;
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MAT 267: Discrete Mathematics, Unio
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Identify a problem and analyze it i
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CS109 covers: • Counting • Comb
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CS 250 - Discrete Structures I, Por
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CS 251 - Discrete Structures II, Po
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DS Graphs and Trees Tree, tree trav
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The course gives an overview to a v
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CS371: Computer Graphics, Williams
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Texture mapping, including minifica
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Other materials are: R and RStudio
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3. Assignment (20% + 10%) Due in we
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CO328: Human Computer Interaction,
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Human Computer Interaction, Univers
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Human-Computer Interaction, Stanfor
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Human Information Processing (HIP),
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Software and Interface Design, Univ
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Computer Systems Security (CS-475),
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Ullman and Widom, 2 nd edition, Pre
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Technology, Ethics, and Global Soci
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SP Professional Communication These
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Why do you teach the course this wa
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search, probabilistic reasoning, lo
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Students are expected to spend abou
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CS188: Artificial Intelligence, Uni
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Introduction to Artificial Intellig
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Computer Networks, Williams College
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NC Introduction All 1.5 NC Networke
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CSCI 432 Operating Systems, William
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OS Security and Protection Access c
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Assignment Five: Memory management
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Programming Language: C Assignment
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Parallel Programming Principle and
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PD Parallel Algorithms, Analysis, a
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• Grama, A., Gupta, A., Kumar V.
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Body of Knowledge coverage For each
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1: Map-reduce for CS1/WMR 2: Multic
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What is the format of the course Co
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Csc 453: Translators and Systems So
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CSCI 434T: Compiler Design, William
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AR Machine-level representation of
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Languages and Compilers, Utrecht Un
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COMP 412: Topics in Compiler Constr
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separate compilation is the key fea
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programming languages. A major them
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CSCI 1730: Introduction to Programm
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CSC 2/454: Programming Language Des
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PL Runtime Systems Data layout; sto
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How are students assessed Over 10 w
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Programming Languages and Technique
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esults from programming language th
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PL Event-driven and Reactive Progra
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Overall, students learn the followi
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PL Type systems Compositional type
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What is the format of the course Th
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Introduction to Computer Science, H
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PD PD/Parallelism Fundamentals Para
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• Analytical Reasoning: Assertion
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CS1101: Introduction to Program Des
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Finally, the design process from
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documentation activity that occurs
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SE Software Validation and Verifica
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Cloud computing and the shift in th
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SE-2890 Software Engineering Practi
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Software Development, Quinnipiac Un
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• Networking subsystem focusing o
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SF Input/output Programmed data tra
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◦ C preprocessors, multifile prog
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Ethics in Technology (IFSM304), Uni
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Analyze basic logical fallacies in
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Specific topics include: • Capaci
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Additional topics The sustainabilit
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How are students assessed The basic
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Ethics & the Information Age (CSI 1
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SP Intellectual Property Overview a
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privacy. Students are asked to shar
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The Digital Age, Grinnell College G
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AR Digital logic and digital system
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COS 126: General Computer Science,
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Prospective computer science majors
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CSCI 0190: Accelerated Introduction
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An Overview of the Two-Course Intro
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Course textbooks and materials Free
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programming (scripting) is covered
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One way to document this spiral app
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3. Data types and structures 1. pri
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◦ Comparison of results for small
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Appendix D: Curricular Exemplars Th
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Bluegrass Community and Technical C
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Knowledge Units in a Typical Major
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Notation: < 25% of KU covered # 25-
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Appendix: Information on Individual
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Curricular Analysis The Knowledge U
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management, the Internet, e-mail, t
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Mathematical Foundations (two desig
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Multi-paradigm, Introductory Sequen
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Additional Comments Although the ex
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CSC 312 - Implementation of Program
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• Biocomputation • Unspecialize
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Additional Comments We instituted a
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CS 145: Introduction to Databases T
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Williams College Department of Comp
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Possible Curricular Revisions Note
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CSCI 237 - Computer Organization Th
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surface scattering functions, binar
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A Cooperative Project of
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