1. PROF. DANIEL ERNST JANUARY 24 TH, 2011 AREAS OF COMPUTER SCIENCE CS 146 The Big Picture in Computer Science

2. What Disciplines Are Close To/Part Of Computer Science? Association of Computing Machinery (ACM) has defined several versions of Computing Curricula CC 2005 lists 5 sub-areas of computing:  Computer Science  Computer Engineering  Information Systems  Information Technology  Software Engineering http://www.acm.org/education/education/curric_v ols/CC2005-March06Final.pdf http://www.acm.org/education/education/curric_v ols/CC2005-March06Final.pdf

3. Representation of Computing Knowledge From CC 2005

4. Quiz question #1 – which of the five? (IS, IT, CS, CE, SE) From CC 2005

5. Quiz question #2 – which of the five? (IS, IT, CS, CE, SE) From CC 2005

6. Quiz question #3 – which of the five? (IS, IT, CS, CE, SE) From CC 2005

7. Quiz question #4 – which of the five? (IS, IT, CS, CE, SE) From CC 2005

8. Quiz question #5 – which of the five? (IS, IT, CS, CE, SE) From CC 2005

9. CHARLES BABBAGE (1791 - 1871) Computer Scientist of the Week

10. Not set in stone – classifications are evolving First take – a possible high-level split  Systems (computer science infrastructure)  Applications (high-level computer science) Areas of Computer Science (1)

11. Major Areas (one fairly arbitrary classification):  Algorithms and Data Structures  Systems  Applications  Theory  Cross-Cutting Areas  Hybrid Areas (with other disciplines) Other views: Wikipedia has multiple different lists – all of which have serious flaws (and change regularly):  http://en.wikipedia.org/wiki/Computer_science http://en.wikipedia.org/wiki/Computer_science  http://en.wikipedia.org/wiki/Outline_of_computer_science http://en.wikipedia.org/wiki/Outline_of_computer_science Areas of Computer Science (2)

12. Algorithms and Data Structures  Algorithms: a series of steps taken to solve a problem  Data Structures: an organized collection of data of one type and operations on that data Systems  Development of lower-level tools and systems for computing Applications  Development of applications of lower-level tools combined with higher-level structures to solve higher-level problems Theory  Theoretical foundations of computer science Hybrid Areas (with other disciplines)  The “computer science + X” areas; e.g. bioinformatics Cross-Cutting Areas  Topics that apply to all of the above What are the Areas?

13. Algorithms  A sequence of finite instructions used to solve some problem  E.g. series of steps to build a house Foundation Frame Roof Interior work  E.g. series of steps for a simple computer program Input Processing Output Example: calculate the area of a circle given its radius Example: input and process a list of numbers to find and display the largest number in the list Algorithms/Data Structures (1)

14. Data Structures  A set of data used to represent a concept, plus the operations that work on that set of data  E.g. a list (of grocery items) plus operations on that list  E.g. a tree (representing the biological taxonomy) plus operations on that tree Kingdoms, classes, orders, genera, species, varieties  E.g. a graph or network of computing systems plus operations on that network Algorithms/Data Structures (2)

15. Algorithm Analysis  Some algorithms are more efficient than others  How can we categorize families of algorithms?  What affects how fast we can execute a given computational algorithm? In-class exercise: different types of algorithms Algorithms/Data Structures (3)

16. Computer Architecture  The internal structure of computing systems  CPU (control unit + arithmetic-logic unit), main memory, secondary memory, input, output  Gate (electronic) logic  Representation of numbers, data, and instructions  Microarchitectural techniques:  Pipelining – keeping multiple resources busy by not waiting for all steps to complete before working on a task  Caching – storage of commonly used data for easy access  Multiprocessing – use of multiple processors to work on tasks in parallel Systems (1)

17. Operating Systems  OS structure (manager, resource allocator)  Processes and Threads, Memory Management, Input and Output, Files, Security  Inter-Process Communication, including mutual exclusion approaches  “Dining Philosophers” problem – classic thought experiments  Deadlock  Scheduling  Issues with multi-processor systems at the software level  Interaction of OS with other systems  Case Studies (Windows, Linux, Mac OS, others) Systems (2)

18. Networks  Open Systems Interconnect (OSI) 7-layer model  Physical, Data Link, Network, Transport, Session, Presentation, Application  Types of systems (end nodes, routers)  Other network equipment (switches, gateways, bridges, hubs, …)  Circuit switching and packet switching  Applications  File Transfer Protocol  Telnet / Secure Shell protocols  Hypertext Transfer Protocol Systems (3)

19. Multiprocessing (“Parallel Processing”)  Can problems be split into work that can be done at the same time by multiple processors? Database Systems (low-level)  Query optimization  Overall system optimization Compiler Development  Lexical analyzer (scanner)  Semantic analyzer (parser) Systems (4)

20. Programming Languages (Practical)  Foundation of many other areas  Major concepts in any high-level language  Data types  Variables  Expressions  Statements  Control Structures Sequence Selection (conditional execution) Repetition (Loops)  Containers Applications (1)

21. Software Engineering / Development  Stages of software development  Requirements gathering  Requirements analysis and specification  Testing  Design High-level (including Design Patterns) Low-level  Implementation  Maintenance  Approaches  Unified Process (more structured, emphasis on modeling, documentation)  Agile Process (less structured, emphasis on client communication, deliverable systems) Applications (2)

22. Database Systems (higher-level)  Conceptual modeling of data (entities, relationships)  Implementation models (relational, object-oriented, object- relational hybrid)  Languages for managing relational data  Structured Query Language (SQL)  Application issues  Programming interfaces (e.g. Java DataBase Connectivity (JDBC))  Efficiency issues (e.g. connection pooling)  Structural issues (e.g. data layers in applications) Applications (3)

23. Web Applications  Web page structure (HTML)  Tools for web development  Major programming environments (Java/J2EE,.NET)  Client-side programming (e.g. JavaScript)  Server-side programming (e.g. Java Server Pages (JSPs), Active Server Pages (ASP))  New web technologies (e.g. AJAX, Web 2.0)  Newer models for web development (e.g. Ruby on Rails)  Service-Oriented Architecture (SOA) Applications (4)

24. Computer Graphics  Areas  Visualization  Animation  Games  Components  Pixels, image types  Display/rendering techniques  Graphics Programming  Rotation  Transformation  Shading Applications (5)

25. Artificial Intelligence  Intelligent systems  Knowledge Representation  Search  Problem solving techniques  Planning Plan alteration  Uncertainty  Robotics  Computer Vision  Natural Language Processing  Fuzzy systems Applications (6)

26. Data Mining  Data analysis  Association rules  Clustering  Recommender Systems  E.g. amazon.com (purchasing)  E.g. MovieLens (movie recommendations) Applications (7)

27. Applications (8) Computational Science and Mathematics  Modeling and Simulation  We know the math behind a lot behaviors: Physical Chemical Social Financial  Let computers calculate out what may happen in a situation  Numerical Algorithms, instead of symbolic  In practice, often done in a broadly interdisciplinary environment

28. Theory of Computation  Finite State Theory  Context-free grammars  Models for computational systems  Intractable problems  P = NP ? Theory (1)

29. Other Areas of Theory  State Theory  Boolean Algebra  Various areas of mathematical theory  Discrete Structures  Numerical Analysis  Linear Algebra  Graph Theory  Advanced Issues Theory (2)

30. Bio/chemical/medical informatics  Mostly applied data mining Scientific simulation Financials – “Quants” Business computing (information systems) Media Art LOTS of others!  I would argue that it is being related in some way to ALL general topics. Hybrid Areas (1)

31. Computer Security / Information Assurance  Involves:  Security of systems  Security of applications  Security theory Ethics in Computing  Privacy  Abuse/Denial of service  Behavior with Anonymity Cross-Cutting Areas(1)

32. Many computer science topics and jobs involve both:  systems and application work  theoretical and applied work  low-level and high-level work Important issues to consider:  Where are your primary interests?  Where are your primary abilities?  How do particular school/job positions intersect with the various areas of computer science? Grey, Not Black and White

33. CS 145 – Fundamentals of Object-Oriented Programming CS 146 – The Big Picture in Computer Science CS 245 – Advanced Programming and Data Structures CS 255 – Algorithms and Discrete Structures CS 268 – Web Programming  or CS 278 – Digital Logic Required CS Courses at UWEC (1)

34. CS 345 – Database Systems CS 352 – Computer Architecture CS 396 – Computer Science Seminar (outside speakers, writing, job prep) CS 330 – Programming Languages CS 355 – Software Engineering 1 CS 362 – Operating Systems CS 485 – Software Engineering 2 CS 462 – Networks (not SE) Plus one or two CS electives Required CS Courses at UWEC (2)

35. CS 370 – Computer Security CS 388 – UNIX Systems Programming CS 420 – Artificial Intelligence CS 450 – Theory of Computation CS 455 – Computer Graphics CE 452 – Advanced Computer Architecture CE 478 – Microcontroller System Design  Both CE electives require CS 278 CS 291/491 – Special Topics  Robotics  Data Mining  Cryptography and Network Security  Parallel Computing Elective CS Courses at UWEC (1)