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Nby temporarily deactivating the context analysis. It is planned to modifythe context analysis in a way that enables it to tolerate faulty aubtreestomporarely.Drawbacks in generality and performancePSG is not the ultimate system, as there remain several unsatisfying points.A formal language definition language enables language definers to generateenvirorrnents in a rapid and reliable way. Hawever, the current implementationof the definition language impoees some restrictions on the clans ofLanguages which may be defined with PSG.First of all, if the concrete syntax of a language cannot be made 1L(1),the language cannot be defined within PSG. It is, however, difficult to seehow to incorporate a mere powerful parsing technique. Bottom-up tethniquessuds as inoranental Lit parsing ((Ce 178)) do sat' fit in our framework. LL(k)with k > 1 is problematic in view of the requirement that arbitrary validprefixes of sentential forma must be parseable. .Certain languages have context conditions which are not definable withinthe current definition Language. The soppe and visibility analysis cannothandle features like elliptical reccrd references in PL/1 or FORWARDprocedure declarations in PASCAL (which will lead to a 'double declaration'error). Within our framework - no declarations required before use - FORWARDdeclaraticns do rot make sense an The context analysis phase is unableto handle user-defined polymorphic or overloaded objects such as overloadedfunctions in ADA. We are currently working on a more powerful.apecificationlanguage for context conditions which will overcome these ihortcominge.Finally, the semantics definition language is unable to handle any form ofparallelimm.The performance of PSG enviloossents has not yet reached production quality,as far as context analysis and pregram execution are concerned. For thecontext analysis, this is primarily a problem of the current implementation,which is merely a prototype. We expect that a more eophisticated implementationwill result in a time speedup factor of at least five. However, theintrinsic complexity of the method is greater than that of e.g. attributedgremmersi For an abstract syntax tree containing n nodes the Repo/Teitelbaumalgorithm will perform with 0(n), wheras cur method requires 0(n4ln(n)).Tho performance difficulties concerning pLooxast execution are of a slightlydifferent nature, as we have difficulties to .see hi to speed up theinterpreter simply by. improving its implementation. The interpreter is suchfaster than that of SIS. Bow ever, it is not fast enough ior productionprograms, as is aloo noted by Pleban for PSP ([Ple84]). We think that theseWhortoominga may be overoane by compilation of the metalarquage term*[Dah84b), utilizing techniques like data floe analysis . elimination ofunnecceeary call-by...name and delayed evaluatiseo and elimination of tailrecursion and linear recursion.4. eanclusionWe presented the PSG peuyLeandg system generator, which generates po•0erfalinteractive programing envirorments from formal language definitions. Thepros and cons of using a farmal, entirely nonprocedural Language definitionlanguage have been discussed. It turned out that use of a formal definitionlanguage allowe very simple and rapid generation of reliable and ppwerfulenvironments. On the other hand, certain strange and complicated features ofcertain language, are not definable with the currently implemented definitionlanguage, and the performance of the generated envirorramta has not yetreached production quality. Nevertheless, we believe that the use of formallanguage definitions is an apvcopriate tool, and that the shortcomings inperformance will be captured by more eophioticated inplementations, whichare still under way.5. AtknowlegdementsX .thank the other markers of the project team, namely R. Dahlke. W. Denhapl.H. Minkel, H. J8ger and T. Letschert for their valuable comments duringthe.development of this paper.6. Peferences[Dah84a] Eahlke, R. and Smiting, G.I Programmiersystemgenerator. Arbeitsberidht1994. Be:richt PG2112/84, Fachgebiet Prograreiersprachenand Dbarsattar II, Teduiische Ibchschule Darmstadt, Pebruar 1984.(Bah84b) Bahlke, R. and Letschert, T. Auaf0hrbare denotationale Semantik.Proc. 4. GI-Fachgesprflch tmplamentierung von Programmiersprochen.MArt 1904.(111678) Dj05rnor, D. and Jones, C.D. (eds.): The Vienna Development MethodsThe metalanguage. LOOS 61, Springer Verleg 1978.lee1783 Celentano, A.: Incremental LR parsers. Acta Informatica 10 (1978),307-321.(FeiO4) Weer, G.E. and Feller, P., Generation of language-oriented editors.Proc. Programmierumgebungen and Compiler, Derichte des German Chapter
Implementation Techniques for PrologAndreas Kral'Institut fur ComputersprachenTechnische liniversitat WienArgentinierstraBe 8A-1040 WienandiOmips.complang.tuwien.ac.atAbstractThis paper is a short survey about currently used implementationtechniques for Prolog. It gives an introductionto unification and resolution in Prolog andpresents the memory model and a basic executionmodel. These models are expanded to the ViennaAbstract Machine (VAM) with its two versions, theVAM2p and the VAM 1 p, and the most famous abstractmachine, the Warren Abstract Machine (WAM).The continuation passing style model of Prolog, binaryProlog, leads to the BinWAM. Abstract interpretationcan be applied to gather information about a program.This information is used in the generation of very specializedmachine code and in optimizations like clauseindexing and instruction scheduling on each kind ofabstract machine1 IntroductionThe implementation of Prolog has a long history[Co193). Early systems were implemented by the grouparound Colmerauer in Marseille. The first system wasan interpreter written in Algol by Phillip Roussel in1972. With this experience a more efficient and usablesystem was developed by Gerard Battani, HenryMeloni and Rene Bazzoli [BM73). It was a structuresharing interpreter and had essentially the same builtinpredicates as modern Prolog systems. This systemwas reasonably efficient and convinced others of theusefulness of Prolog. Together with Fernande and LuisPereira David Warren developed the DEC-10 Prolog,the first Prolog compiler [War77]. This compiler andthe portable interpreter C-Prolog spread around theworld and contributed to the success of Prolog. Furtherdevelopments are described in [Roy94] and partlyin this paper.Section 2 presents a basic execution model for Prolog.This model helps to understand the Warren AbstractMachine described in section 3 and the ViennaAbstract Machine described in section 4. Section 5gives on overview of optimizations.2 A basic execution model2.1 IntroductionThe two basic parts of a Prolog interpreter are theunification part and the resolution part. The resolutionis quite simple. It just implements a simplifiedSLD-resolution mechanism that searches the clausestop-down and evaluates the goals from left to right.This strategy immediately leads to the backtrackingimplementation and the usual layout of the data areasand stacks. Resolution handles stack frame allocation,calling of procedures, and backtracking.Unification in Prolog is defined as follows:• two constants unify if they are equal• two structures unify if their functors (name andarity) are equal and all arguments unify• two unbound variables unify and they are boundtogether• an unbound variable and a constant or structureunify and the constant or structure is bound tothe variableThis definition of unification determines the datarepresentation. A thorough analysis of the recursiveunification algorithm pays off because the interpreterspends most of the time in this part.2.2 The representation of dataSince Prolog is not statically typed, the type and valueof a variable can in general be determined only at runtime. Therefore, a variable cell is divided into a valuepart and a tag part which determines the kind of thevalue. Fig. 1 shows a tagged value cell.Basic data objects in Prolog are constants (atomand integer), structures and unbound variables. Sinceunbound variables can be bound together, there are
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