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The Carnegie-Mellon curriculum for undergraduate computer science

Author: Mary Shaw
Publisher: New York : Springer, ©1985.
Edition/Format:   Book : EnglishView all editions and formats
Database:WorldCat
Summary:

This curriculum and its description were developed during the period 1981 - 1984

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Additional Physical Format: Online version:
Carnegie-Mellon curriculum for undergraduate computer science.
New York : Springer, ©1985
(OCoLC)561683320
Document Type: Book
All Authors / Contributors: Mary Shaw
ISBN: 0387960996 9780387960999
OCLC Number: 11289881
Notes: "This curriculum and its description were developed during the period 1981-1984 by Stephen D. Brookes ... et al."
Description: 198 pages ; 24 cm
Contents: 1. Introduction and Overview.- 1.1 Goals of the Curriculum Design.- 1.2. Educational Philosophy.- 1.3. Character of the Curriculum.- 1.4. Innovations in the Curriculum.- 1.5. Organization of the Book.- 2. The Nature of Computer Science.- 2.1. Working Definition of Computer Science.- 2.2. A View of Future Computing.- 3. Roles for Universities.- 3.1. The Audience.- 3.2. Use of Computing Technology in Education.- 3.3. The ACM and IEEE Curricula.- 4. Objectives for the Curriculum.- 4.1. Premises.- 4.2. Goals.- 5. The Content of Computer Science.- 5.1. Basics.- 5.1.1. Content.- 5.1.2. Skills.- 5.2. Elementary Computer Science.- 5.2.1. Content.- 5.2.2. Modes of Thought.- 5.2.3. Skills.- 5.3. Liberal Professional Education.- 5.3.1. General Scope.- 5.3.2. Liberal Education.- 5.3.3. Areas Related to Computer Science.- 5.3.3.1. Mathematics and Statistics.- 5.3.3.2. Electrical Engineering.- 5.3.3.3. Physics.- 5.3.3.4. Psychology.- 5.3.3.5. Mechanical Engineering.- 5.3.3.6. Management and Information Science.- 5.3.3.7. Public policy.- 5.4. Advanced Computer Science.- 5.4.1. Control.- 5.4.2. Data.- 5.4.3. Systems.- 5.4.4. Language.- 5.4.5. Foundations.- 5.4.6. Design.- 5.4.7. Communications.- 5.4.8. Applications.- 6. Program Organization.- 6.1. Requirements.- 6.2. Advice on the Use of Electives.- 6.3. Program Flexibility.- 6.4. Sample Program.- 7. Curriculum'78-Is Computer Science Really that Unmathematical?.- 7.1. Curriculum '78 and Mathematics.- 7.2. Mathematics for Computer Scientists.- 8. Mathematics Curriculum and the Needs of Computer Science.- 8.1. Some Words about Computer Science.- 8.2. Mathematical Aspects of Undergraduate Computer Science.- 8.2.1. Mathematical Modes of Thought Used by Computer Scientists.- 8.2.1.1. Abstraction and Realization.- 8.2.1.2. Problem-solving.- 8.2.2. Discrete Mathematics.- 8.2.3. Continuous Mathematics.- 8.3. Some Remarks about Computer Science and Mathematics Curricula.- 8.4. Conclusion.- 9. Theory and Practice in the Fundamental Computer Science Course.- 9.1. Introduction.- 9.2. Course Overview.- 9.3. Major topics in the Fundamental Structures Course.- 9.3.1. Models of Computation: Automata.- 9.3.2. Formal Languages.- 9.3.3.Formal Specification and Verification.- 9.3.4. Algorithmic Analysis.- 9.3.5 Data Types.- 9.3.6. Recursion.- 9.3.7. Programming Exercises.- 9.4. Experiences.- 9.5. Conclusions.- 10. Remarks on the Design.- 10.1. General Philosophy.- 10.2. Relation to Traditional Courses.- 10.3. Course Organization and Style.- 10.4. Course Numbering Scheme.- 11. Course Descriptions.- 11.1. Basic and Introductory Courses.- 11.1.1. Computers in Modern Society [100].- 11.1.2. Programming and Problem Solving [110].- 11.1.3. Discrete Mathematics [150].- 11.2. Elementary and Intermediate Computer Science Courses.- 11.2.1 Fundamental Structures of Computer Science I [211].- 11.2.2 Fundamental Structures of Computer Science II [212].- 11.2.3 Real and Abstract Machines [240].- 11.2.4 Solving Real Problems [300].- 11.2.5 Time and Resources [310].- 11.2.6 Program Organizations [313].- 11.2.7. Languages, Interfaces, and their Processors [320].- 11.2.8. Algorithms and Programs [330].- 11.2.9 Formal Languages, Automata, and Complexity [350].- 11.2.10. Logic for Computer Science [351].- 11.2.11. Introduction to Artificial Intelligence [360].- 11.2.12. Introduction to Robotics [361].- 11.3. Advanced Computer Science Courses.- 11.3.1 Independent Project [400].- 11.3.2. Undergraduate Thesis [401].- 11.3.3. Research Seminar [409].- 11.3.4. Big Data [410].- 11.3.5. Communications and Networks [411].- 11.3.6. Software Engineering [413].- 11.3.7. Software Engineering Lab [414].- 11.3.8. Transducers of Programs [420].- 11.3.9. Advanced Programming Languages and Compilers [421].- 11.3.10. Advanced Algorithms [430].- 11.3.11. Computer Architecture [440].- 11.3.12. VLSI Systems [441].- 11.3.13. Theory of Programming Languages [450].- 11.3.14. Complexity Theory [451].- 11.3.15. Artificial Intelligence-Cognitive Processes [460].- 11.3.16. Artificial Intelligence-1. Introduction and Overview.- 1.1 Goals of the Curriculum Design.- 1.2. Educational Philosophy.- 1.3. Character of the Curriculum.- 1.4. Innovations in the Curriculum.- 1.5. Organization of the Book.- 2. The Nature of Computer Science.- 2.1. Working Definition of Computer Science.- 2.2. A View of Future Computing.- 3. Roles for Universities.- 3.1. The Audience.- 3.2. Use of Computing Technology in Education.- 3.3. The ACM and IEEE Curricula.- 4. Objectives for the Curriculum.- 4.1. Premises.- 4.2. Goals.- 5. The Content of Computer Science.- 5.1. Basics.- 5.1.1. Content.- 5.1.2. Skills.- 5.2. Elementary Computer Science.- 5.2.1. Content.- 5.2.2. Modes of Thought.- 5.2.3. Skills.- 5.3. Liberal Professional Education.- 5.3.1. General Scope.- 5.3.2. Liberal Education.- 5.3.3. Areas Related to Computer Science.- 5.3.3.1. Mathematics and Statistics.- 5.3.3.2. Electrical Engineering.- 5.3.3.3. Physics.- 5.3.3.4. Psychology.- 5.3.3.5. Mechanical Engineering.- 5.3.3.6. Management and Information Science.- 5.3.3.7. Public policy.- 5.4. Advanced Computer Science.- 5.4.1. Control.- 5.4.2. Data.- 5.4.3. Systems.- 5.4.4. Language.- 5.4.5. Foundations.- 5.4.6. Design.- 5.4.7. Communications.- 5.4.8. Applications.- 6. Program Organization.- 6.1. Requirements.- 6.2. Advice on the Use of Electives.- 6.3. Program Flexibility.- 6.4. Sample Program.- 7. Curriculum'78-Is Computer Science Really that Unmathematical?.- 7.1. Curriculum '78 and Mathematics.- 7.2. Mathematics for Computer Scientists.- 8. Mathematics Curriculum and the Needs of Computer Science.- 8.1. Some Words about Computer Science.- 8.2. Mathematical Aspects of Undergraduate Computer Science.- 8.2.1. Mathematical Modes of Thought Used by Computer Scientists.- 8.2.1.1. Abstraction and Realization.- 8.2.1.2. Problem-solving.- 8.2.2. Discrete Mathematics.- 8.2.3. Continuous Mathematics.- 8.3. Some Remarks about Computer Science and Mathematics Curricula.- 8.4. Conclusion.- 9. Theory and Practice in the Fundamental Computer Science Course.- 9.1. Introduction.- 9.2. Course Overview.- 9.3. Major topics in the Fundamental Structures Course.- 9.3.1. Models of Computation: Automata.- 9.3.2. Formal Languages.- 9.3.3.Formal Specification and Verification.- 9.3.4. Algorithmic Analysis.- 9.3.5 Data Types.- 9.3.6. Recursion.- 9.3.7. Programming Exercises.- 9.4. Experiences.- 9.5. Conclusions.- 10. Remarks on the Design.- 10.1. General Philosophy.- 10.2. Relation to Traditional Courses.- 10.3. Course Organization and Style.- 10.4. Course Numbering Scheme.- 11. Course Descriptions.- 11.1. Basic and Introductory Courses.- 11.1.1. Computers in Modern Society [100].- 11.1.2. Programming and Problem Solving [110].- 11.1.3. Discrete Mathematics [150].- 11.2. Elementary and Intermediate Computer Science Courses.- 11.2.1 Fundamental Structures of Computer Science I [211].- 11.2.2 Fundamental Structures of Computer Science II [212].- 11.2.3 Real and Abstract Machines [240].- 11.2.4 Solving Real Problems [300].- 11.2.5 Time and Resources [310].- 11.2.6 Program Organizations [313].- 11.2.7. Languages, Interfaces, and their Processors [320].- 11.2.8. Algorithms and Programs [330].- 11.2.9 Formal Languages, Automata, and Complexity [350].- 11.2.10. Logic for Computer Science [351].- 11.2.11. Introduction to Artificial Intelligence [360].- 11.2.12. Introduction to Robotics [361].- 11.3. Advanced Computer Science Courses.- 11.3.1 Independent Project [400].- 11.3.2. Undergraduate Thesis [401].- 11.3.3. Research Seminar [409].- 11.3.4. Big Data [410].- 11.3.5. Communications and Networks [411].- 11.3.6. Software Engineering [413].- 11.3.7. Software Engineering Lab [414].- 11.3.8. Transducers of Programs [420].- 11.3.9. Advanced Programming Languages and Compilers [421].- 11.3.10. Advanced Algorithms [430].- 11.3.11. Computer Architecture [440].- 11.3.12. VLSI Systems [441].- 11.3.13. Theory of Programming Languages [450].- 11.3.14. Complexity Theory [451].- 11.3.15. Artificial Intelligence-Cognitive Processes [460].- 11.3.16. Artificial Intelligence-Robotics [461].- 11.3.17. Interactive Graphics Techniques [470].- 12. Related Courses.- 12.1. Mathematics Courses.- 12.1.1. Introduction to Discrete Mathematics [Math 127/CS 167 150].- 12.1.2. Calculus I [Math 121].- 12.1.3. Calculus II [Math 122].- 12.1.4. Methods of Applied Math I [Math 259].- 12.1.5. Elements of Analysis [Math 261].- 12.1.6. Operations Research I [Math 292].- 12.1.7. Operations Research II [Math 293].- 12.1.8. Combinatorial Analysis [Math 301/CS 251].- 12.1.9. Linear Algebra [Math 341].- 12.1.10. Numerical Methods [Math 369/CS 352].- 12.1.11. Modern Algebra [Math 473/CS 452].- 12.1.12. Applied Graph Theory [Math 484/CS 430].- 12.1.13. Numerical Mathematics I and II [Math 704 and 705].- 12.1.14. Large-Scale Scientific Computing [Math 712/CS 453].- 12.2. Statistics Courses.- 12.2.1. Probability and Applied Statistics for Physical Scienceand Engineering I [Stat 211/CS 250].- 12.2.2. Probability and Statistics I [Stat 215].- 12.2.3. Statistical Methods for Data Analysis I [Stat 219].- 12.3. Electrical Engineering Courses.- 12.3.1 Linear Circuits: [EE 101/CS 241].- 12.3.2. Electronic Circuits I [EE 102/CS 242].- 12.3.3. Introduction to Digital Systems [EE 133].- 12.3.4. Linear Systems Analysis [EE 218].- 12.3.5. Electronic Circuits II [EE 221/CS 340].- 12.3.6. Analysis and Design of Digital Circuits [EE 222/CS 341].- 12.3.7. Introduction to Solid State Electronics [EE 236].- 12.3.8. Introduction to Computer Architecture [EE 247/CS 440].- 12.3.9. Fundamentals of Control [EE 301].- 12.4. Psychology Courses.- 12.4.1. Psychology of Learning and Problem Solving [Psy 113].- 12.4.2. Information Processing Psychology and Artificial Intelligence [Psy 213].- 12.4.3. Human Factors [Psy 363].- 12.4.4. Cognitive Processes and Problem Solving [Psy 411].- 12.4.5. Thinking [Psy 417].- 12.5. Engineering and Public Policy Courses.- 12.5.1. Law and Technology [EPP 321].- 12.5.2. Telecommunications Policy Analysis [EPP 402].- 12.5.3. Policy Issues in Computing [EPP 380/CS 380].- 12.6. Engineering Courses.- 12.6.1. Real Time Computing in the Laboratory [Engr 252].- 12.6.2. Analysis, Synthesis and Evaluation [Engr 300].- 12.6.3. The History and Formulation of Research and Development Policy [Engr 401].- 12.6.4. Cost-Benefit Analysis [Engr 404].
Responsibility: edited by Mary Shaw.

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