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CS152: Programming Languages
Lecture 1 — Course Introduction
Dan Grossman Spring 2011
Today
(^) Administrative stuff
(^) Introducing myself (^) Expanded version because I’m a visitor
(^) Course motivation and goals (^) A Java example
(^) Course overview (^) Expanded version because you’re shopping
(^) Course pitfalls
(^) Start on Caml tutorial (most of Thursday) (^) Advice: start playing with it soon to learn and/or remember (e.g., hw1, problem 1) Dan Grossman CS152 Spring 2011, Lecture 1 2
Course facts
(^) Dan Grossman, Maxwell Dworkin 233, [email protected]
(^) TF: Paul Govereau, Maxwell Dworkin 309, [email protected]
(^) Office hours to-be-determined (see web page) (^) Also encouraged to make appointments with me or even just stop by
(^) Web page for: (^) “homework 0” (^) homework 1, fairly carefully pipelined with first lectures (^) Do not wait to do it all
Dan Grossman CS152 Spring 2011, Lecture 1 3
Coursework
(^) 6 homework assignments [almost surely] (^) “Paper/pencil” (LATEX recommended?) (^) Programming (Caml required) (^) Where you’ll probably learn the most (^) Do challenge problems if you want but not technically “extra”
(^) One “introduction/summary” to a published research paper (^) More details in a few weeks; high work/length ratio
(^) 2 exams (^) my reference sheet plus your reference sheet; samples provided
(^) No textbook (^) But several books on reserve (see web page and ask) (^) Will post slides and will try to write lecture notes (^) Lecture notes from CS152 Spring 2010 may prove useful (^) 80%+ same material, but somewhat different order/style
Dan Grossman CS152 Spring 2011, Lecture 1 4
Academic integrity
(^) Don’t cheat in my class (^) I’ll be personally offended (^) Being honest is far more important than your grade
(^) Rough guidelines (^) can sketch idea together (^) cannot look at code solutions
(^) Ask questions and always describe what you did
(^) Please do work together and learn from each other
Logistical Advice
(^) Take notes: (^) Slides posted, but they are enough to teach from not to learn from (^) Will often work through examples by hand
(^) Arrive on time: (^) Unlike many CS people, I start and end punctually (10:07–11:30) (^) Missing the first N minutes is so much less efficient than missing the last N minutes (^) I know you can get here on time (cf. exam days)
Talking about myself
I’m a “visiting faculty member” just for this semester
(^) Normally at the University of Washington in Seattle
(^) This should not scare you away from taking this course
(^) Let me compensate for you not being able to look up my evaluations or ask your friends about me...
Dan Grossman CS152 Spring 2011, Lecture 1 7
What will this guy be like?
(^) Last year’s CS152 is a reasonable approximation
(^) I’ve taught this material [mostly to graduate students] 8 times
(^) Planning about 15% new stuff to keep things fresh/improving and because the term is longer
(^) I love teaching and I love the material in this course (^) Hopefully “Lecture 1” is the most boring one? (^) Most professors don’t teach while on sabbatical
Dan Grossman CS152 Spring 2011, Lecture 1 8
Student Evaluations
Evaluations from last time I taught a similar course (Fall 2009)
Excellent Very Good Fair Poor Very Good Poor Course as a whole 62% 29% 8% 0% 0% 0% Course content 50% 33% 17% 0% 0% 0% Instructor’s contribution 83% 12% 4% 0% 0% 0% Instructor’s effectiveness 79% 12% 8% 0% 0% 0% Instructor’s interest 75% 12% 12% 0% 0% 0% Amount learned 54% 17% 25% 4% 0% 0% Grading techniques 42% 42% 12% 4% 0% 0%
Dan Grossman CS152 Spring 2011, Lecture 1 9
More about me
Saving you a Google search: (^) http://www.cs.washington.edu/homes/djg (^) http://www.facebook.com/profile.php?id= Professional life story: (^) St. Louis suburbs → Rice → Cornell → UW (^) UW universally “top-10” CS and arguably # (^) But try to convince my grandma (^) Seriously, if looking at grad school, we should talk (^) Programming languages from theory to practice (^) Morrisett was my Ph.D. advisor; Chong was an office-mate (^) I’m here to refresh, collaborate, learn, and teach — and have fun Other: Ice hockey, cycling and running, non-fiction, my nephew, beer, ...
Dan Grossman CS152 Spring 2011, Lecture 1 10
What could go wrong?
So this is sort of like “study abroad” for the professor instead of the students
(^) Please don’t get too upset when I mess up the jargon, but correct me (^) TF, semester, concentration, ...
(^) Different logistics than I’m used to (^) web page, grades, photocopier, ... (^) will probably all settle down after this week
(^) Help me if you see me lost on campus :-)
More importantly, we may have to work together on the pace (^) But based on last year’s CS152, I think we’ll be fine
Programming-language concepts
Focus on semantic concepts:
What do programs mean (do/compute/produce/represent)?
How to define a language precisely?
English is a poor metalanguage
Aspects of meaning:
equivalence, termination, determinism, type,...
This course does not gives superficial exposure to N weird PLs (^) More like CS121 than CS51, but not really like either (^) But it will help you learn new languages via foundations
Course nongoals
(^) Study syntax; learn to specify grammars, parsers
(^) Transforming 3 + 4 or (+ 3 4) or +(3, 4) to “application of plus operator to constants three and four” (^) Stop me when I get too sloppy
(^) Learn specific programming languages (but some ML)
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What we will do
(^) Define really small languages (^) Usually Turing complete (^) Always unsuitable for real programming
(^) Extend them to realistic languages less rigorously
(^) Digress for cool results (this is fun!?!)
(^) Study models very rigorously via operational models
(^) Do programming assignments in Caml
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Plenty of Theory
Hard to give a taste of what the “theory” will look like, but here is some cut-and-paste from topics we will cover in the next few weeks
Lectures 3–
H ; e ⇓ c H ; x := e → H, x → c ; skip
H ; e ⇓ c c> 0 H ; if e s 1 s 2 → H ; s 1
H ; e ⇓ c c≤ 0 H ; if e s 1 s 2 → H ; s 2
Lectures 7–
Γ, x : τ 1 e : τ 2 Γ λx. e : τ 1 → τ 2
Γ e 1 : τ 2 → τ 1 Γ e 2 : τ 2 Γ e 1 e 2 : τ 1
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Caml
(^) Caml is an awesome, high-level language
(^) We will use a tiny core subset of it that is well-suited for manipulating recursive data structures (like programs!)
(^) You mostly have to learn it outside of class (^) Don’t procrastinate (^) Don’t hesitate to ask questions
(^) Resources on course webpage
(^) I am not a language zealot, but knowing ML makes you a better programmer
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Pitfalls
How to hate this course and get the wrong idea:
(^) Forget that we made simple models to focus on the essence
(^) Don’t quite get inductive definitions and proofs when introduced
(^) Don’t try other ways to model/prove the idea (^) You’ll probably be wrong (^) And therefore you’ll learn more
(^) Think PL people focus on only obvious facts (^) Need to start there
Final Metacomment
Acknowledging others is crucial...
This course draws heavily on pedagogic ideas from at least: Chambers, Chong, Felleisen, Flatt, Fluet, Harper, Morrisett, Myers, Pierce, Rugina, Walker And material covered in texts from Pierce, Wynskel, and others (This is a course, not my work.)
Caml tutorial
(^) “Let go of Java/C”
(^) If you have seen SML, Haskell, Scheme, Lisp, etc. this will feel more familiar
(^) If you have seen Caml, focus here on “how I say things” and what subset will be most useful to us in studying PL
(^) Give us some small code snippets so we have a common experience we can talk about
(^) Also see me use the tools
Dan Grossman CS152 Spring 2011, Lecture 1 25
