POP-11

Last updated

POP-11
Paradigm Multi-paradigm: structured, reflective, procedural, functional, declarative
Family Lisp: POP
Designed by Robin Popplestone, Steve Hardy, Chris Mellish, Aaron Sloman, John Williams, Robert Duncan, Simon Nichols, John Gibson
Developers University of Sussex
Systems Designers Ltd.
Integral Solutions Ltd.
University of Birmingham
First appeared1975;49 years ago (1975)
Stable release
16 / January 2020;4 years ago (2020-01)
Typing discipline dynamic
Implementation language POP-11
Platform PDP-11, VAX, SPARC, IA-32, PowerPC, x86-64
OS Cross-platform: VMS, Unix, Linux, Mac OS X, Windows
License Proprietary (1975–1999)
Open-source (1999–present): MITXFree86
Website www.cs.bham.ac.uk/research/projects/poplog/poplog.info.html
Major implementations
AlphaPop, Basic Pop, Pop-9X, Poplog, Spice
Influenced by
POP-2

POP-11 is a reflective, incrementally compiled programming language with many of the features of an interpreted language. It is the core language of the Poplog programming environment developed originally by the University of Sussex, and recently in the School of Computer Science at the University of Birmingham, which hosts the main Poplog website.

Contents

POP-11 is an evolution of the language POP-2, developed in Edinburgh University, and features an open stack model (like Forth, among others). It is mainly procedural, but supports declarative language constructs, including a pattern matcher, and is mostly used for research and teaching in artificial intelligence, although it has features sufficient for many other classes of problems. It is often used to introduce symbolic programming techniques to programmers of more conventional languages like Pascal, who find POP syntax more familiar than that of Lisp. One of POP-11's features is that it supports first-class functions.

POP-11 is the core language of the Poplog system. The availability of the compiler and compiler subroutines at run-time (a requirement for incremental compiling) gives it the ability to support a far wider range of extensions (including run-time extensions, such as adding new data-types) than would be possible using only a macro facility. This made it possible for (optional) incremental compilers to be added for Prolog, Common Lisp and Standard ML, which could be added as required to support either mixed language development or development in the second language without using any POP-11 constructs. This made it possible for Poplog to be used by teachers, researchers, and developers who were interested in only one of the languages. The most successful product developed in POP-11 was the Clementine data mining system, developed by ISL. After SPSS bought ISL, they renamed Clementine to SPSS Modeler and decided to port it to C++ and Java, and eventually succeeded with great effort, and perhaps some loss of the flexibility provided by the use of an AI language.

POP-11 was for a time available only as part of an expensive commercial package (Poplog), but since about 1999 it has been freely available as part of the open-source software version of Poplog, including various added packages and teaching libraries. An online version of ELIZA using POP-11 is available at Birmingham.

At the University of Sussex, David Young used POP-11 in combination with C and Fortran to develop a suite of teaching and interactive development tools for image processing and vision, and has made them available in the Popvision extension to Poplog.

Simple code examples

Here is an example of a simple POP-11 program:

define Double(Source) -> Result;     Source*2 -> Result; enddefine;
Double(123) =>

That prints out:

** 246

This one includes some list processing:

   define RemoveElementsMatching(Element, Source) -> Result;      lvars Index;      [[%      for Index in Source do          unless Index = Element or Index matches Element then              Index;          endunless;      endfor;      %]] -> Result;  enddefine;   RemoveElementsMatching("the", [[the cat sat on the mat]]) => ;;; outputs [[cat sat on mat]]  RemoveElementsMatching("the", [[the cat] [sat on] the mat]) => ;;; outputs [[the cat] [sat on] mat]  RemoveElementsMatching([[= cat]], [[the cat]] is a [[big cat]]) => ;;; outputs [[is a]]  

Examples using the POP-11 pattern matcher, which makes it relatively easy for students to learn to develop sophisticated list-processing programs without having to treat patterns as tree structures accessed by 'head' and 'tail' functions (CAR and CDR in Lisp), can be found in the online introductory tutorial. The matcher is at the heart of the SimAgent (sim_agent) toolkit. Some of the powerful features of the toolkit, such as linking pattern variables to inline code variables, would have been very difficult to implement without the incremental compiler facilities.

See also

Related Research Articles

<span class="mw-page-title-main">Common Lisp</span> Programming language standard

Common Lisp (CL) is a dialect of the Lisp programming language, published in American National Standards Institute (ANSI) standard document ANSI INCITS 226-1994 (S2018). The Common Lisp HyperSpec, a hyperlinked HTML version, has been derived from the ANSI Common Lisp standard.

Logic programming is a programming, database and knowledge representation paradigm based on formal logic. A logic program is a set of sentences in logical form, representing knowledge about some problem domain. Computation is performed by applying logical reasoning to that knowledge, to solve problems in the domain. Major logic programming language families include Prolog, Answer Set Programming (ASP) and Datalog. In all of these languages, rules are written in the form of clauses:

Prolog is a logic programming language that has its origins in artificial intelligence, automated theorem proving and computational linguistics.

Planner is a programming language designed by Carl Hewitt at MIT, and first published in 1969. First, subsets such as Micro-Planner and Pico-Planner were implemented, and then essentially the whole language was implemented as Popler by Julian Davies at the University of Edinburgh in the POP-2 programming language. Derivations such as QA4, Conniver, QLISP and Ether were important tools in artificial intelligence research in the 1970s, which influenced commercial developments such as Knowledge Engineering Environment (KEE) and Automated Reasoning Tool (ART).

Poplog is a reflective, incrementally compiled software development computer programming integrated development environment and system platform for the programming languages POP-11, Common Lisp, Prolog, and Standard ML. It was created originally in the United Kingdom for teaching and research in artificial intelligence, at the University of Sussex, and later marketed as a commercial package for software development, teaching, and research. It was one of the initiatives supported for a time by the UK government-funded Alvey Programme.

In computer science, declarative programming is a programming paradigm—a style of building the structure and elements of computer programs—that expresses the logic of a computation without describing its control flow.

In artificial intelligence, symbolic artificial intelligence is the term for the collection of all methods in artificial intelligence research that are based on high-level symbolic (human-readable) representations of problems, logic and search. Symbolic AI used tools such as logic programming, production rules, semantic nets and frames, and it developed applications such as knowledge-based systems, symbolic mathematics, automated theorem provers, ontologies, the semantic web, and automated planning and scheduling systems. The Symbolic AI paradigm led to seminal ideas in search, symbolic programming languages, agents, multi-agent systems, the semantic web, and the strengths and limitations of formal knowledge and reasoning systems.

Metaprogramming is a computer programming technique in which computer programs have the ability to treat other programs as their data. It means that a program can be designed to read, generate, analyse, or transform other programs, and even modify itself, while running. In some cases, this allows programmers to minimize the number of lines of code to express a solution, in turn reducing development time. It also allows programs more flexibility to efficiently handle new situations with no recompiling.

MDL is a programming language, a descendant of the language Lisp. Its initial purpose was to provide high level language support for the Dynamic Modeling Group at Massachusetts Institute of Technology's (MIT) Project MAC. It was developed in 1971 on a PDP-10 running ITS and later ran on TENEX, TOPS-20, BSD, and AEGIS.

Dynamic compilation is a process used by some programming language implementations to gain performance during program execution. Although the technique originated in Smalltalk, the best-known language that uses this technique is Java. Since the machine code emitted by a dynamic compiler is constructed and optimized at program runtime, the use of dynamic compilation enables optimizations for efficiency not available to statically-compiled programs except through code duplication or metaprogramming.

Hope is a small functional programming language developed in the 1970s at the University of Edinburgh. It predates Miranda and Haskell and is contemporaneous with ML, also developed at the University. Hope was derived from NPL, a simple functional language developed by Rod Burstall and John Darlington in their work on program transformation. NPL and Hope are notable for being the first languages with call-by-pattern evaluation and algebraic data types.

An incremental compiler is a kind of incremental computation applied to the field of compilation. Quite naturally, whereas ordinary compilers make a so-called clean build, that is, (re)build all program modules, an incremental compiler recompiles only modified portions of a program.

POP-2 is a programming language developed around 1970 from the earlier language POP-1 by Robin Popplestone and Rod Burstall at the University of Edinburgh. It drew roots from many sources: the languages Lisp and ALGOL 60, and theoretical ideas from Peter J. Landin. It used an incremental compiler, which gave it some of the flexibility of an interpreted language, including allowing new function definitions at run time and modification of function definitions while a program runs, without the overhead of an interpreted language.

SWI-Prolog is a free implementation of the programming language Prolog, commonly used for teaching and semantic web applications. It has a rich set of features, libraries for constraint logic programming, multithreading, unit testing, GUI, interfacing to Java, ODBC and others, literate programming, a web server, SGML, RDF, RDFS, developer tools, and extensive documentation.

Logic Programming Associates (LPA) is a company specializing in logic programming and artificial intelligence software. LPA was founded in 1980 and is widely known for its range of Prolog compilers, the Flex expert system toolkit and most recently, VisiRule.

ECLiPSe is a software system for the development and deployment of constraint logic programming applications, e.g., in the areas of optimization, planning, scheduling, resource allocation, timetabling, transport, etc. It is also suited for teaching most aspects of combinatorial problem solving, e.g., problem modeling, constraint programming, mathematical programming, and search techniques. It contains constraint solver libraries, a high-level modeling and control language, interfaces to third-party solvers, an integrated development environment and interfaces for embedding into host environments.

<span class="mw-page-title-main">Aaron Sloman</span>

Aaron Sloman is a philosopher and researcher on artificial intelligence and cognitive science. He held the Chair in Artificial Intelligence and Cognitive Science at the School of Computer Science at the University of Birmingham, and before that a chair with the same title at the University of Sussex. Since retiring he is Honorary Professor of Artificial Intelligence and Cognitive Science at Birmingham. He has published widely on philosophy of mathematics, epistemology, cognitive science, and artificial intelligence; he also collaborated widely, e.g. with biologist Jackie Chappell on the evolution of intelligence.

Inductive programming (IP) is a special area of automatic programming, covering research from artificial intelligence and programming, which addresses learning of typically declarative and often recursive programs from incomplete specifications, such as input/output examples or constraints.

References