Lecture 1: Introduction

We dissect nature along lines laid down by our native language. ... Language is not simply a reporting device for experience but a defining framework for it.

-- Benjamin Whorf, Thinking in Primitive Communities

• first time I'm teaching this
• someone please take notes! (counts as class participation)
• everything will be available on the web
• Why study them?
  • programming languages are the heart of computer science
  • part of core
  • needed to express, not to mention understand, algorithms
  • some algorithms short & pretty in one language, not another
  • beware the Turing Tarpit
  • what makes humans unique? languages and planning!
  • one of the most interesting parts of CS & Math
    • proofs (ie convincing arguments) made flesh
    • easy to formalize means easy to understand
  • beautiful
  • practical
    • partial evaluation (specialization)
    • proof carrying code
    • compiler generators
  • more diversity in programming languages than in human ones
  • deeper understanding helps us avoid mistakes, reinvention
  • what we want: modularity, clarity, efficiency, beauty
• Important Ideas and Tools
  • functional programming
    • first class functions
    • higher order functions
    • computer programs are functions, so languages to talk about them must be functional
    • denotational semantics, lambda calculus
  • lazy evaluation
    • modularity tool (put termination in hands of consumer)
    • easier to abstract eg control structures
  • logic programming
    • computation as inference
    • running program = searching for constructive
    • proof that answer exists (eg that sequence of
    • assembly language instructions with same
    • semantics as source program exists)
    • generalization of databases and of human
    • thought (eg modus ponens)
    • reasoning about programs
  • types and type inference
    • particularly tractable kind of reasoning about code
    • error checking (eg violation of type consistency)
    • eliminate redundancy
    • richer type vocabulary (list 'a, tree 'a)
    • improve modularity by automatic abstraction (eg append)
    • good for programming in the large: module system
  • object oriented programming
    • I think you've all heard enough about this!
    • Java if we have time
• Organization of course
  • Two common structures:
    • survey of languages
      • write some code in each
      • Pros: learn syntax, more accessible, syntactic comparison
      • Cons: bogged in details, negative transfer
    • interpreter based
      • write lots of interpreters
      • Pros: deep understanding, avoids syntax
      • Cons: tricky, differences deep in interpreter, sometimes beauty is lost
  • We will use a combination of the two approaches
    • simple interpreters to help learn "core semantics"
    • writing in language to get "feel" for it
• prerequisite: CS 257, ie working knowledge of Scheme
  • Scheme is the lingua franca of programming languages
  • assignment 1, due a week from today: write some stuff in Scheme
  • quiz one week from today: test your knowledge of Scheme
  • waiting list for this class, so fails may be instructor dropped
• grading:
  • homeworks and exercises (70%)
  • participation (10%)
  • final project (20%)
  • maybe final - if needed
• please don't cheat (duh)
• subscribe to the class mailing list

Definitions

Webster's Revised Unabridged Dictionary (1913):

Lingua Franca \Lin"gua Fran"ca\

Any hybrid or other language used over a wide area as a common or commercial tongue among peoples of different speech.