1. CS120: Lecture 1 MP Johnson Hunter College mpjohnson@gmail.com

2. agenda Admin Syllabus Survey Data, storage, representation

3. admin Sessions: 9:48-11:26am / 11:36-1:14pm HW 224 Class page Email Text OHs tba Grading –Hw (written, prog., labs) – O(6) ~ 45% –Exams – 20% + 25% –Class partic/quizzes – 10% Start or end of class Attendance is required – 80%

4. Core Class topics 1Breadth-first tour of CS 2Data –storage –Representation of knowledge) –Compression (JPG, MP3) 3How computers work –Machines 4networks, Internet, OS 1HTML 2FTP, SSH 5Algorithms – good ones? 6Programming / SE / data structures

5. Advanced/optional AI Hardware Crypto Unsolvable problems Search Engines Social/political issues? Other topics? Some parts of class will be challenging Many will be applied/topical – read Slashdot/Digg

6. Survey 1.Name 2.Email (clearly!!) 3.Grade-level 4.Major 5.Why taking class 6.Topics you’re most interested in

7. Q: What are comps? A: machines that compute Q: compute what? A: the output of some algorithm Alg: list of instructions / recipe –Abstract but unambiguous (how?) –Much more later Egs: long division algorithm, gcd, sorting

8. Long (pre)history Abacus (3000BC) – just storage Pascal (1600s) – addition Leibniz (1600s/1700s) – math Babbage Diff. gin (1800s) – math Babbage An. Gin – punched cards All these were mechanical (gears, etc.) –Difficult to make reliable & fast & cheap

9. 20 th C: electronics Circuits, transistors, etc. Mach 1, ENIAC, UNIVAC (1940s) - room-sized Since then: “just” miniaturization Mainframes  supercomps, minis  PCs (“micros”): early 80s on All “essentially” same: –Run many programs (v. arcade machine) –These programs impl. Algs (tho in diff. langs) –They store, rep, use data

10. Today: data CS = abstraction + reduction –“that’s so reductive” In CS, all data is numbers, All numbers are bits (0/1) / bools (F/T) Bit = binary digit boolean ~ George Boole (1800s)

11. Bool logic/algebra Vals: F, T Ops: and, or, xor, not Draw truth tables Xor intuit: soup or sald Can write exprs Exprs can nest

12. Bool expr eg Suppose A ~ empl A is working, B, C Suppose want: should always be exactly one empl working Q: If we only know bool logic, how to test? Q: how to write a “program” for this in bool logic? (A & ~B & ~C) | … (A xor B) & … (A | B | C) …

13. Q: How to compute/eval this? We now understand bool ops, so we could perform each op ourselves –A gp of female workers in WWII were called “computers” Bad: too slow, error-prone Funda strength of comps: can do some (v. simple) things v. fast

14. strategy Don’t: create a special machine to comp whole expr/function/program Do: create a little machine for each component, then combine –Forget about software for now! How? First, bool ops  gates

15. gates

16. Gates  elec circuit No one of these is v. interesting But two big insights: –Can create an implement gate electronically 0/1  low/high current –Gates can be combined to produce powerful computations / representations  electronic circuits / chips Draw circuits for each expr Of course, want software (non-kickable) For that we need a compiler…

17. Circuits as memory Flipflop: special circuit that can store data –1 bit per FF To store, send pulse in top or bottom (0 is ddf) Go through Reading for next week: wiki entries on boolean logic and two’s complete (through section 2 only)