Attribute grammars (AGs) are a suitable formalism for the development of language processing systems. However, for languages including unrestricted labeled jumps, such as "goto' in C, the optimizers in compilers are difficult to write in AGs. This is due to two problems that few previous researchers could deal with simultaneously, i.e., references of attribute values on distant nodes and circularity in attribute dependency. This paper proposes circular remote attribute grammars (CRAGs), an extension of AGs that allows (1) direct relations between two distant attribute instances through pointers referring to other nodes in the derivation tree, and (2) circular dependencies, under certain conditions including those that arise from remote references. This extension gives AG programmers a natural means of describing language processors and programming environments for languages that include any type of jump structure. We also show a method of constructing an efficient evaluator for CRAGs called a mostly static evaluator. The performance of the proposed evaluator has been measured and compared with dynamic and static evaluators.

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Abstract-Automata play important roles in wide area of computing and the growth of multicores calls for their efficient parallel implementation. Though it is known in theory that we can perform the computation of a finite automaton in parallel by simulating transitions, its implementation has a large overhead due to the simulation. In this paper we propose a new automaton called simultaneous finite automaton (SFA) for efficient parallel computation of an automaton. The key idea is to extend an automaton so that it involves the simulation of transitions. Since an SFA itself has a good property of parallelism, we can develop easily a parallel implementation without overheads. We have implemented a regular expression matcher based on SFA, and it has achieved over 10-times speedups on an environment with dual hexa-core CPUs in a typical case.

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In this paper we introduce two methods for building LALR parsers for regular right part grammars (RRPGs). Both methods build a parser directly from a grammar, require no extra state or data structure, and can deal with all LALR RRPGs.The first method is quite simple. For almost all LALR RRPGs, including the majority of grammars with stacking conflicts, parsing actions are similar to those of LALR parsers for usual context free grammars. No extra action is required to recognize a handle in this case. For other LALR RRPGs, the right hand side of a production is checked to recognize a handle.The second method does not require checking of the right hand side of a production to recognize a handle. Instead, it records the number of conflicts in LR items and in the stack. Unlike previous methods, our method needs no extra data structure.