Lisp (historically LISP, an abbreviation of "list processing") is a family of programming languages with a long history and a distinctive, fully parenthesized prefix notation. Originally specified in the late 1950s, it is the second-oldest high-level programming language still in common use, after Fortran. Lisp has changed since its early days, and many dialects have existed over its history. Today, the best-known general-purpose Lisp dialects are Common Lisp, Scheme, Racket, and Clojure. Lisp was originally created as a practical mathematical notation for computer programs, influenced by (though not originally derived from) the notation of Alonzo Church's lambda calculus. It quickly became a favored programming language for artificial intelligence (AI) research. As one of the earliest programming languages, Lisp pioneered many ideas in computer science, including tree data structures, automatic storage management, dynamic typing, conditionals, higher-order functions, recursion, the self-hosting compiler, and the read–eval–print loop. The name LISP derives from "List Processor". Linked lists are one of Lisp's major data structures, and Lisp source code is made of lists. Thus, Lisp programs can manipulate source code as a data structure, giving rise to the macro systems that allow programmers to create new syntax or new domain-specific languages embedded in Lisp. The interchangeability of code and data gives Lisp its instantly recognizable syntax. All program code is written as s-expressions, or parenthesized lists. A function call or syntactic form is written as a list with the function or operator's name first, and the arguments following; for instance, a function f that takes three arguments would be called as (f arg1 arg2 arg3).
History
John McCarthy began developing Lisp in 1958 while he was at the Massachusetts Institute of Technology (MIT). He was motivated by a desire to create an AI programming language that would work on the IBM 704, as he believed that "IBM looked like a good bet to pursue Artificial Intelligence research vigorously." He was inspired by Information Processing Language, which was also based on list processing, but did not use it because it was designed for different hardware and he found an algebraic language more appealing. Due to these factors, he consulted on the design of the Fortran List Processing Language, which was implemented as a Fortran library. However, he was dissatisfied with it because it did not support recursion or a modern if-then-else statement (which was a new concept when Lisp was first introduced). McCarthy's original notation used bracketed "M-expressions" that would be translated into S-expressions. As an example, the M-expression car[cons[A,B]] is equivalent to the S-expression (car (cons A B)). Once Lisp was implemented, programmers rapidly chose to use S-expressions, and M-expressions were abandoned. M-expressions surfaced again with short-lived attempts of MLisp by Horace Enea and CGOL by Vaughan Pratt. Lisp was first implemented by Steve Russell on an IBM 704 computer using punched cards. Russell was working for McCarthy at the time and realized (to McCarthy's surprise) that the Lisp eval function could be implemented in machine code. According to McCarthy
Steve Russell said, look, why don't I program this eval ... and I said to him, boss, boss, you're confusing theory with practice, this eval is intended for reading, not for computing. But he went ahead and did it. That is, he compiled the eval in my paper into IBM 704 machine code, fixing bugs, and then advertised this as a Lisp interpreter, which it certainly was. So at that point Lisp had essentially the form that it has today ... The result was a working Lisp interpreter which could be used to run Lisp programs, or more properly, "evaluate Lisp expressions". Two assembly language macros for the IBM 704 became the primitive operations for decomposing lists: car (Contents of the Address part of Register number) and cdr (Contents of the Decrement part of Register number), where "register" refers to registers of the computer's central processing unit (CPU). Lisp dialects still use car and cdr () for the operations that return the first item in a list and the rest of the list, respectively. McCarthy published Lisp's design in a paper in Communications of the ACM on April 1, 1960, entitled "Recursive Functions of Symbolic Expressions and Their Computation by Machine, Part I". He showed that with a few simple operators and a notation for anonymous functions borrowed from Church, one can build a Turing-complete language for algorithms. The first complete Lisp compiler, written in Lisp, was implemented in 1962 by Tim Hart and Mike Levin at MIT, and could be compiled by simply having an existing LISP interpreter interpret the compiler code, producing machine code output able to be executed at a 40-fold improvement in speed over that of the interpreter. This compiler introduced the Lisp model of incremental compilation, in which compiled and interpreted functions can intermix freely. The language used in Hart and Levin's memo is much closer to modern Lisp style than McCarthy's earlier code. Garbage collection routines were developed by MIT graduate student Daniel Edwards, prior to 1962. During the 1980s and 1990s, a great effort was made to unify the work on new Lisp dialects (mostly successors to Maclisp such as ZetaLisp and NIL (New Implementation of Lisp)) into a single language. The new language, Common Lisp, was somewhat compatible with the dialects it replaced (the book Common Lisp the Language notes the compatibility of various constructs). In 1994, ANSI published the Common Lisp standard, "ANSI X3.226-1994 Information Technology Programming Language Common Lisp".
Timeline
Connection to artificial intelligence Since its inception, Lisp was closely connected with the artificial intelligence research community, especially on PDP-10 systems. Lisp was used as the implementation of the language Micro Planner, which was used in the famous AI system SHRDLU. In the 1970s, as AI research spawned commercial offshoots, the performance of existing Lisp systems became a growing issue, as programmers needed to be familiar with the performance ramifications of the various techniques and choices involved in the implementation of Lisp.
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