CS2013-final-report

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developing, describing, and justifying algorithmic solutions for new problems. The 1 or 2 programming assignments go a step further by also requiring an implementation; these assignments help students better appreciate both what it means to describe an algorithm clearly and what issues can remain in implementation. To encourage students not to fall behind in the material, two problem sets are due every week (one every lecture). By the end of the semester students should also have a strong appreciation for the role of algorithms. Body of Knowledge coverage KA Knowledge Unit Topics Covered Hours SDF algorithms and design concept and properties of algorithms, role of algorithms, problem-solving strategies, separation of behavior and implementation 1.5 AL basic analysis all core-tier1 all core-tier2 1 1.5 AL algorithmic strategies core-tier1: brute-force, greedy, divide-and-conquer, dynamic programming core-tier2: heuristics 6 .5 AL fundamental data structures and algorithms all core-tier1 core-tier2: heaps, graph algorithms (minimum spanning tree, single source shortest path, all pairs shortest path), string algorithms (longest common subsequence) 3 6 AL basic automata computability and complexity no core-tier1 (covered in other required courses), core-tier2: introduction to P/NP/NPC with examples 0 1 AL AL advanced computational complexity advanced automata theory and computability P/NP/NPC, Cook-Levin, classic NPC problems, reductions 2 none (covered in other required courses) 0 AL advanced data structures algorithms and analysis balanced trees (1-2 examples), graphs (topological sort, strongly connected components), advanced data structures (disjoint sets, mergeable heaps), network flows, linear programming (formulating, duality, overview of techniques), approximation algorithms (2-approx for metric- TSP, vertex cover), amortized analysis 8 Additional topics The above table covers approximately 30 hours of lecture and gives the material that is covered every semester. The remaining hours can be used for review sessions, to otherwise allow extra time for topics that students that semester find particularly confusing, for in-class midterms, or to cover a range of additional topics. In the past these additional topics have included: KA Knowledge Unit Topics Covered AL advanced computational complexity P-space, EXP - 235 -
AL PD advanced data structures algorithms and analysis parallel algorithms, analysis, and programming more approximation algorithms (e.g., Christofides, subsetsum), geometric algorithms, randomized algorithms, online algorithms and competitive analysis, more data structures (e.g., log* analysis for disjoint-sets) critical path, work and span, naturally parallel algorithms, specific algorithms (e.g., mergesort, parallel prefix) PD formal models and semantics PRAM Other comments Starting in the Fall of 2013 approximately 2-3 hours of the currently optional material on parallel algorithms will become a standard part of the class. - 236 -
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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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11. Discuss the importance of usabi
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Learning outcomes: [Core-Tier2] 1.
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Learning outcomes: 1. Describe the
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Information Management (IM) Informa
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• Design of core DBMS functions (
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3. Demonstrate use of the relationa
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IM/Physical Database Design [Electi
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• Presentation, rendering, synchr
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IS/Fundamental Issues [1 Core-Tier2
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4. Describe over-fitting in the con
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IS/Agents [Elective] Cross-referenc
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Learning Outcomes: 1. Explain the d
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Networking and Communication (NC) T
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NC/Networked Applications [1.5 Core
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NC/Social Networking [Elective] Top
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OS/Overview of Operating Systems [2
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OS/Memory Management [3 Core-Tier2
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OS/File Systems [Elective] Topics:
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Platform-Based Development (PBD) Pl
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Learning Outcomes: 1. Design and im
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Because the terminology of parallel
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PD/Parallelism Fundamentals [2 Core
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• Topologies o Interconnects o Cl
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o Software as a service o Security
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PL. Programming Languages (8 Core-T
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PL/Functional Programming [3 Core-T
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o o o Enforce invariants during cod
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PL/Compiler Semantic Analysis [Elec
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• Metaprogramming: Macros, Genera
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PL/Language Pragmatics [Elective] T
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emphasize formal analysis (e.g., Bi
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Learning Outcomes: 1. Analyze and e
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Software Engineering (SE) In every
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such system are assigned to the cor
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Learning Outcomes: [Core-Tier1] 1.
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SE/Tools and Environments [2 Core-T
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SE/Software Design [3 Core-Tier1 ho
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[Elective] • Potential security p
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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
Page 207 and 208: Appendix B: Migrating to CS2013 A g
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Page 211 and 212: GV The storage of analog signals in
Page 213 and 214: SDF This new knowledge area pulls t
Page 215 and 216: Table B-3: Core Learning Topics and
Page 217 and 218: Table B-4: New and Expanded Core Le
Page 219 and 220: IAS Core-Tier1: • Analyze the tra
Page 221 and 222: IS NC Core-Tier2: • Translate a n
Page 223 and 224: • Describe at least one design te
Page 225 and 226: • Explain why the creation of cor
Page 227 and 228: • Use refactoring in the process
Page 229 and 230: • Apply simple algorithms for exp
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Page 237: CSCI 140: Algorithms, Pomona Colleg
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Page 243 and 244: CS 256 Algorithm Design and Analysi
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Page 247 and 248: • Data races and higher-level rac
Page 249 and 250: CS/ECE 552: Introduction to Compute
Page 251 and 252: Body of Knowledge coverage KA Knowl
Page 253 and 254: AR Assembly Level Machine Organizat
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Page 257 and 258: Altruism/Collaboration/Competition,
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Page 261 and 262: COSC/MATH 201: Modeling and Simulat
Page 263 and 264: ehaviors, simplifying assumptions;
Page 265 and 266: MAT 267: Discrete Mathematics, Unio
Page 267 and 268: Identify a problem and analyze it i
Page 269 and 270: CS109 covers: • Counting • Comb
Page 271 and 272: CS 250 - Discrete Structures I, Por
Page 274 and 275: CS 251 - Discrete Structures II, Po
Page 276 and 277: DS Graphs and Trees Tree, tree trav
Page 278 and 279: The course gives an overview to a v
Page 280 and 281: CS371: Computer Graphics, Williams
Page 282 and 283: Texture mapping, including minifica
Page 284 and 285: Other materials are: R and RStudio
Page 286 and 287: 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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Body of Knowledge coverage KA Knowl
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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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