Course Review

• Basic Scheme programming. Specifying classes of data. Inductive data definitions. Recursive Functions
• Representation Invariants. Relating concrete representations to abstractions. Data Abstractions.
• Specifying Programming Languages. Concrete Syntax. Abstract Syntax. Semantics.
• Environments. Expressed versus Denoted Values. Variable binding and scope. The LET language.
• First class procedures. Lexical scope. The PROC language. Representing procedures.
• Recursive procedures. The LETREC language. Note the relationship between the new concrete environment ADT extended with extend-env-rec and the abstract mathematical environment that we are representing with it.
• Computational effects. The Store. Explicit references. Store-passing specifications.
• Implicit references. Program transformations.
• Continuations as a way to reason about program evaluation. Continuations as an implementation artifact.
• Continuations as a programmer visible feature. Exceptions. Another example: yield in Python.
• Types. Type safety. Strongly typed languages. Statically typed languages. Static versus dynamic semantics. Program analysis. Constraint generation, constraint solving. The halting problem. Careful reading: "what is the type of proc (x) x."
• Continuations (again) as a programmer visible feature. Continuation-passing interpreters. Exceptions (try/catch, throw). Nondeterministic choice. Threads. Globally angelic choice (choose). Restricted angelic choice (choose/cut, fail).
• Imperative threads. Race conditions. CAS (aka compare-and-swap). Reasoning about imperative multi-threading is complicated.
• Objects, Modularity Encapsulation. Dispatch. Subclassing. Subtyping.

Last updated 14 April 2008.