CS2013-final-report

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◦ Comparison of results for small and large data sets ◦ Introduction of tight-bound analysis (Big-θ) • Elements of Java programming ◦ Basic syntax and semantics ◦ Interfaces and classes ◦ Exceptions ◦ Strings ◦ Arrays, ArrayLists, vectors ◦ Comparators; sorting ◦ Generics ◦ Java type system ◦ Iterators ◦ Introduction to the Java class library • An integrated development environment (IDE) (e.g., Eclipse) Course textbooks, materials, and assignments The main textbook is Mark Allen Weiss, Data Structures and Problem Solving Using Java, Fourth Edition, Addison-Wesley, 2009. ISBN: 0-321-54040-5. This is supplemented by numerous on-line readings. In-class work involves an equal mix of lecture and lab-based activities. Students work collaboratively in pairs on the 23 required labs. Students also work individually on several programming assignments and on tests. Body of Knowledge coverage KA Knowledge Unit Topics Covered Hours AL Basic Analysis Knowledge Unit covered in full; additional material in 5 later Analysis of Algorithms course AL Algorithmic Strategies Divide and conquer ; much more in later Analysis of 1 Algorithms course AL Fundamental Data Additional sorting, trees, analysis of algorithms; 8 Structures and Algorithms searching and sorting done in earlier course; graphs in later Analysis of Algorithms course CN Fundamentals Several examples, problems, and assignments utilize 1 modeling and simulation; Math/Stat Dept. offers a full course in Modeling PL Object-Oriented Knowledge Unit covered in full 10 Programming PL Type Systems Supplement to discussion in earlier courses to cover 2 Knowledge Unit in full; additional material in later Programming Language Concepts course PL Language Translation and Automatic vs. manual memory management, garbage 0 Execution collection SDF Algorithms and Design Comparison of iterative and recursive strategies 3 SDF Fundamental Programming Simple I/O, iteration over structures (e.g., arrays) 2 Concepts SDF Fundamental Structures Stacks, queues, priority queues, sets, references and 5 aliasing, choosing data structures covered in objectoriented context SDF Development Methods Program correctness, defensive programming, exceptions, code reviews, test-case generation, pre- and post-conditions, modern programming environments, library APIs, debugging, documentation, program style 6 - 461 -
SE Software Design Design principles, refactoring 1 SE Software Construction Exception handling, coding standards 1 SE Software Verification and Test case generation, approaches to testing 1 Validation SF Resource Allocation and Example/assignment introduce kinds of scheduling: 1 Scheduling FIFO, priority; much additional material in Operating Systems course SP Professional Ethics Codes of ethics, accountability, responsibility 1 - 462 -
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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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o o o o Code segments Libraries and
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Systems Fundamentals (SF) The under
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2. Describe how hardware, VM, OS, a
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2. Describe the scheduling algorith
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Social Issues and Professional Prac
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understanding of our commitment to
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Learning Outcomes: 1. Evaluate stak
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Learning Outcomes: [Core-Tier1] 1.
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[Elective] 8. Discuss ways to influ
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• Differences in access to comput
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Appendix B: Migrating to CS2013 A g
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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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Page 428 and 429: Analyze basic logical fallacies in
Page 430 and 431: Specific topics include: • Capaci
Page 432 and 433: Additional topics The sustainabilit
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Page 440 and 441: privacy. Students are asked to shar
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Page 444 and 445: AR Digital logic and digital system
Page 446 and 447: COS 126: General Computer Science,
Page 448 and 449: Prospective computer science majors
Page 450 and 451: CSCI 0190: Accelerated Introduction
Page 452 and 453: An Overview of the Two-Course Intro
Page 454 and 455: Course textbooks and materials Free
Page 456 and 457: programming (scripting) is covered
Page 458 and 459: One way to document this spiral app
Page 460 and 461: 3. Data types and structures 1. pri
Page 466 and 467: Appendix D: Curricular Exemplars Th
Page 468 and 469: Bluegrass Community and Technical C
Page 470 and 471: Knowledge Units in a Typical Major
Page 472 and 473: Notation: < 25% of KU covered # 25-
Page 474 and 475: Appendix: Information on Individual
Page 476 and 477: Curricular Analysis The Knowledge U
Page 482 and 483: management, the Internet, e-mail, t
Page 484 and 485: Mathematical Foundations (two desig
Page 486 and 487: Multi-paradigm, Introductory Sequen
Page 492 and 493: Additional Comments Although the ex
Page 494 and 495: CSC 312 - Implementation of Program
Page 496 and 497: • Biocomputation • Unspecialize
Page 502 and 503: Additional Comments We instituted a
Page 504 and 505: CS 145: Introduction to Databases T
Page 506 and 507: Williams College Department of Comp
Page 512 and 513: 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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