CS 146 The Big Picture in Computer Science

1. CS 146The Big Picture in Computer Science Prof. Daniel Ernst January 24th, 2011 Areas of 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_vols/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. Computer Scientistof the Week Charles Babbage (1791 - 1871)

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

11. Areas of Computer Science (2) • 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/Outline_of_computer_science

12. What are the Areas? • 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

13. Algorithms/Data Structures (1) • 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

14. Algorithms/Data Structures (2) • 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

15. Algorithms/Data Structures (3) • 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

16. Systems (1) • 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

17. Systems (2) • 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)

18. Systems (3) • 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

19. Systems (4) • 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)

20. Applications (1) • 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

21. Applications (2) • 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)

22. Applications (3) • 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)

23. Applications (4) • 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)

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

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

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

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

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

30. Hybrid Areas (1) • 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.

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

32. Grey, Not Black and White • 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?

33. Required CS Courses at UWEC (1) • 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

34. Required CS Courses at UWEC (2) • 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

35. Elective CS Courses at UWEC (1) • 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