LR(k) sparse-parsers and their optimisation

PhD ThesisA method of syntactic analysis is developed which . . is believed to surpass all known competitors in all major respects. I The method is based upon that associated with the LR(k) grammars but is faster because it bypasses all reduction steps concerned with 'chain' productions. These are freely selected productions which are considered semantically irrelevant and whose right parts consist of just a single symbol. The parses produced by the method are 'sparse' in that they contain no references to chain productions - they are termed 'chain-free' parses. The CFLR(k) grammars are introduced as the largest class which can be -Chain-F-ree parsed from -Le-ft to Right while looking ~ symbols ahead of the current point of the parse. The properties of these grammars are examined in detail and their relationship to the conventional LR(k) grammars is explored. Techniques are presented for testing grammars for the CFLR(k) property and for constructing chain-free parsers for those grammars possessing the property. Methods are also presented for. converting ordinary LR(k) parsers into chain-free parsers. CFLR(k) parsers are more widely applicable than their LR(k) counterparts, are faster 'and provide the same excellent detection of syntactic errors. Unfortunately they also tend to be rather larger. A 'simple optimization is presented which completely'overcomes this single disadvantage without sacrificing any of the advantages of the method. These theoretical techniques are adapted to provide truly practical chain-free parsers based on the conventional SLR and,LALR parsing methods. Detailed consideration is given to use of 'default reductions' and related techniques for achd.evfng compact representations of these parsers. The resulting chain-free parsers are not only faster than their ordinary counterparts, but probably smaller too. We believe their advantages are such that they should substantially replace other parsing methods currently used in programming language compilers

Syntactic analysis of LR(k) languages

PhD ThesisA method of syntactic analysis, termed LA(m)LR(k), is discussed theoretically. Knuth's LR(k) algorithm is included as the special case m = k. A simpler variant, SLA(m)LR(k) is also described, which in the case SLA(k)LR(O) is equivalent to the SLR(k) algorithm as defined by DeRemer. Both variants have the LR(k) property of immediate detection of syntactic errors. The case m = 1 k = 0 is examined in detail, when the methods provide a practical parsing technique of greater generality than precedence methods in current use. A formal comparison is made with the weak precedence algorithm. The implementation of an SLA(1)LR(O) parser (SLR) is described, involving numerous space and time optimisations. Of importance is a technique for bypassing unnecessary steps in a syntactic derivation. Direct comparisons are made, primarily with the simple precedence parser of the highly efficient Stanford AlgolW compiler, and confirm the practical feasibility of the SLR parser.The Science Research Council

A New Approach to LL and LR Parsing

Cílem této práce je vytvořit nový efektivní způsob syntaktické analýzy propojením LL a LR přístupů. Pro demonstrační účely je zhotoven nový programovací jazyk podle vzoru programovacího jazyka PHP. Tento jazyk je rozdělen na části, kde pro každou část je použita ta nejvhodnejší ze zmíněných metod. Jednotlivé metody jsou zde podrobněji popsané v kontextu dvou typů přístupů. Jedním z nich je syntaktická analýza shora dolů a tím druhým opačná verze, syntaktická analýza zdola nahoru. Pro každou separovanou část je vytvořen samostatný syntaktický analyzátor. Táto práce poskytuje kompletní teoretický základ k sestrojení všech zde použitých syntaktických analyzátorů a rozkladových tabulek. Nakonec jsou sestrojené analyzátory společne propojeny, což je úspěšné zakončení praktické demonstrace naší metody. V závěru jsou diskutovány dosažené výsledky práce jako efektivnejší druh syntaktické analýzy, modularita přístupu a podobně. Je zde také diskutovaná použitelnost navržené metody za účelem zefektivnení vývoje a rychlosti překladu. Jako poslední jsou uvedeny náměty pro další výzkum v této oblasti.The aim of this thesis is to create a new effective parsing method via connection of LL and LR approaches. For demonstration purpose is made a new programming language according to the pattern of PHP. The language is separated into the sections and for constituent sections is chosen the most appropriate from the mentioned methods. For every section is created its own syntax analyser. The thesis provides a complete theoretical basis to construct every syntax analyser that has been used here. Finally, the syntax analysers are connected together and new method is practically presented. In conclusion, contributions of this work are discussed, such as the faster parser or the improved development. It also discusses usability of the designed method and suggestions for the next possible research in this area.

SLR inference: An inference system for fixed-mode logic programs, based on SLR parsing

AbstractDefinite-clause grammars (DCGs) generalize context-free grammars in such a way that Prolog can be used as a parser in the presence of context-sensitive information. Prolog's proof procedure, however, is based on backtracking, which may be a source of inefficiency. Parsers for context-free grammars that use backtracking, for instance, were soon replaced by more efficient methods, such as LR parsers. This suggests incorporating the principles underlying LR parsing into a parser for grammars with context-sensitive information. We present a technique that applies a transformation to the program/grammar by adding leaves to the proof/parse trees and placing the contextual information in such leaves. An inference system is then easily obtained from an LR parser, since only the parts dealing with terminals (which appear at the leaves) must be modified. Although our method is restricted to programs with fixed modes, it may be preferable to DCGs under Prolog for some programs

PSLR(1): Pseudo-Scannerless Minimal LR(1) for the Deterministic Parsing of Composite Languages

Composite languages are composed of multiple sub-languages. Examples include the parser specification languages read by parser generators like Yacc, modern extensible languages with complex layers of domain-specific sub-languages, and even traditional programming languages like C and C++. In this dissertation, we describe PSLR(1), a new scanner-based LR(1) parser generation system that automatically eliminates scanner conflicts typically caused by language composition. The fundamental premise of PSLR(1) is the pseudo-scanner, a scanner that only recognizes tokens accepted by the current parser state. However, use of the pseudo-scanner raises several unique challenges, for which we describe a novel set of solutions. One major challenge is that practical LR(1) parser table generation algorithms merge parser states, sometimes inducing incorrect pseudo-scanner behavior including new conflicts. Our solution is a new extension of IELR(1), an algorithm we have previously described for generating minimal LR(1) parser tables. Other contributions of our work include a robust system for handling the remaining scanner conflicts, a correction for syntax error handling mechanisms that are also corrupted by parser state merging, and a mechanism to enable scoping of syntactic declarations in order to further improve the modularity of sub-language specifications. While the premise of the pseudo-scanner has been described by other researchers independently, we expect our improvements to distinguish PSLR(1) as a significantly more robust scanner-based parser generation system for traditional and modern composite languages