This post is a compilation of my notes on two landmark papers:

  1. The Lisp paper: McCarthy J, Recursive Functions of Symbolic Expressions and Their Execution by Machine, CACM’60
  2. Interpreters paper: Reynolds J C, Definitional Interpreters for Higher-Order Programming Languages, ACM’72

1.The Lisp Paper

This paper by John McCarthy introduces the Lisp programming language and describes its implementation on IBM 704 machines. Lisp stands out among the programming languages of its day (eg: Algol 60) as the first high-level programming language that abstracts the underlying machine completely. Instead, Lisp allows symbolic computation by letting programmers define (recursive) functions over symbolic expressions (called S-expressions). An S-expression is either an atomic symbol (hence “symbolic”), or an ordered pair of S-expressions. Reserving an atomic symbol NIL to denote an empty list, we can construct a list of S-expressions:


using ordered pairs as:


Observe that above is also an S-Expression. Hence, a list of S-expressions is also an S-expression. Since most functions operate on a list of symbols, programming such functions in Lisp is effectively LISt Programming (hence, the name “Lisp”).

Lisp defines five primitive S-functions to construct & destruct lists, and to check equality among atomic symbols:

  1. atom
  2. eq
  3. car
  4. cdr
  5. cons

Lisp, as defined in paper, includes a class of expressions called Meta-expressions (written M-expressions) to let us define and apply S-functions over S-expressions. An M-expression is either

  1. A function application. For eg, f[2; EMPTY] is an M-expression that denotes application of function f over S-expressions of atomic symbols 2 and EMPTY.
  2. A function definition with grammar: fname[x0, …, xn] = expr, and
  3. A conditional expression: [expr1a -> expr1b; …; exprna -> exprnb ]

Using M-expressions and primitive S-functions, we can define a subst function to substitute An S-expression (x) for an atomic symbol (y) in another expression (z) as:

subst[x;y;z] = [
  atom[z] -> [
    eq[z;y] -> x;
    T -> z
  T -> cons [subst[x; y; car[z]]; 
             subst[x; y; cdr[z]]]

This example demonstrates that while M-expressions are control structures (functions & conditional expressions), S-expressions represent data to be manipulated by M-expressions.

The definition (semantics) of Lisp are given as an interepreter program in Lisp itself. McCarthy’s list interpreter, implemented as mutually recursive eval and apply functions, is often cited as an example of metacircular evaluation - defining the evaluation semantics of embedded language in terms of evaluation semantics of host-language, which happens to be same as embedded languge. Interestingly, McCarthy defines Lisp as a dynamically scoped language (Paul Graham says so, but is it really? Reynolds’s 2nd interpreter, which he says is similar to McCarthy’s, is lexically scoped.).

In order to use metacircular lisp interpreter to interpret a lisp program, the program first has to be converted to data. In other words, all M-expressions need to be translated to S-expressions (Note: this means that M-expressions are only a syntactic sugar). A simple algorithm to perform the same has been described in the paper. The algorithm converts all function names and their arguments in the user lisp program (which are meta-variables) to atomic symbols. The interpreter (eval function, to be specific) maintains an environment which defines bindings for these atomic symbols. However, note that the original program may also contain atomic symbols, and these symbols have no attached interpretation. To distinguish between atomic symbols that are present in the user program, and atomic symbols that are introduced while convering M-expressions to S-expressions, the former set of atomic symbols are quoted.

As mentioned previously, Lisp is the first language that abstracted the underlying machine completely. In order to be able to do that, the run-time should be able to manage scarce machine resources, such as memory. Towards this end, Lisp introduced automated memory reclamation, which is now commonly known as “Garbage Collection”.

2.Definitional Interpreters Paper

The Lisp paper defines semantics of Lisp using a metacircular interpreter written in Lisp itself. The definitional interpreters paper by Reynolds exposes subtle aspects of such definitional interpreters. In particular, it shows how semantics of the embedded language (called the defined language) can depend on semantics of the host language (called the defining language), such as its treatment of higher-order functions, and the order of function application . To demonstrate this point, the paper first constructs a metacircular interpreter for a higher-order (defined) language in another higher-order (defining) language, by simply translating an expression (eg: function application) in defined language as the corresponding expression in defining language. The paper makes two observations about this interpreter:

  1. The nature of higher-order functions is not clear.
  2. The order of application is not explicit; the order of evaluating function applications in defined language depends on whether the defining language is call-by-value or call-by-name.

Subsequently, Reynolds proposes two transformations to make the treatment of higher-order functions, and order of function applications explicit in the semantics of defined language:

  1. Defunctionalization: A function in defined language is not a function in defining language. Instead, functions and function closures are represented explicitly as data structures (For eg, as S-expressions in Lisp interpreter), and the semantics of a function application is defined explicitly, as a transformation over data. Defunctionalization effectively lets us write a definitional interpreter for a higher-order language in a first-order language.
  2. CPS transformation: A continuation is a function that explicitly represents “rest of the computation”. At every atomic step of evaluation in a definitional interpreter, if we explicitly describe what “rest of the evaluation” is, then the semantics of defined language no longer depends on order of evaluation of defining language; the order of evaluation is now explicit in the interpreter. This kind of interpreter is said to be written in continuation passing style (CPS).

The paper also describes how imperative features, such as assignments, can be encoded explictly in a definitional interpreter written in applicative style.