A note on a proposed LALR parser for extended context-free grammars

The lemma in “An improved LALR(k) parser generation for regular right part grammars” [Inform. Process. Lett. 47 (1993) 123-129] to test the applicability of the method is shown to be false by means of a counter-example grammar.     

Learning context-free grammars using tabular representations

We present a novel algorithm using new hypothesis representations for learning context-free grammars from a finite set of positive and negative examples. We propose an efficient hypothesis representation method which consists of a table-like data structure similar to the parse table used in efficient parsing algorithms for context-free grammars such as Cocke-Younger-Kasami algorithm. By employing this representation method, the problem of learning context-free grammars from examples can be reduced to the problem of partitioning the set of nonterminals. We use genetic algorithms for solving this partitioning problem. Further, we incorporate partially structured examples to improve the efficiency of our learning algorithm, where a structured example is represented by a string with some parentheses inserted to indicate the shape of the derivation tree of the unknown grammar. We demonstrate some experimental results using these algorithms and theoretically analyse the completeness of the search space using the tabular method for context-free grammars.     

Analyzing ambiguity of context-free grammars

It has been known since 1962 that the ambiguity problem for context-free grammars is undecidable. Ambiguity in context-free grammars is a recurring problem in language design and parser generation, as well as in applications where grammars are used as models of real-world physical structures.We observe that there is a simple linguistic characterization of the grammar ambiguity problem, and we show how to exploit this by presenting an ambiguity analysis framework based on conservative language approximations. As a concrete example, we propose a technique based on local regular approximations and grammar unfoldings. We evaluate the analysis using grammars that occur in RNA analysis in bioinformatics, and we demonstrate that it is sufficiently precise and efficient to be practically useful.     

The rewriting logic semantics project

Rewriting logic is a flexible and expressive logical framework that unifies algebraic denotational semantics and structural operational semantics (SOS) in a novel way, avoiding their respective limitations and allowing succinct semantic definitions. The fact that a rewrite logic theory’s axioms include both equations and rewrite rules provides a useful “abstraction dial” to find the right balance between abstraction and computational observability in semantic definitions. Such semantic definitions are directly executable as interpreters in a rewriting logic language such as Maude, whose generic formal tools can be used to endow those interpreters with powerful program analysis capabilities.     

A syntax-directed parser for recalcitrant grammars

This paper deals with a syntax-directed parsing scheme being used in a PL/I compiler for the CDC 6600. It uses a highly restricted grammar of the class LL(1) for efficiency, with an escape hatch for those cases excluded by the grammar. These cases are handled by oracles that can make decisions without a full-scale syntactic analysis. The input to SYNDIPAR, the SYNtax Directed PARser, consists of syntax equations, semantic routines, and token class definitions; the output consists of a PARSE procedure in PL/I together with certain tables. The PARSE procedure works in conjunction with a lexical scanner, designed to allow look-ahead by oracles in a uniform fashion. The actual parsing process takes place through the interpretation of a program compiled by SYNDIPAR for a parsing machine. The instruction set of the parsing machine is described, and an example of the compilation of a syntax equation is given.     

E-generalization using grammars

We extend the notion of anti-unification to cover equational theories and present a method based on regular tree grammars to compute a finite representation of E-generalization sets. We present a framework to combine Inductive Logic Programming and E-generalization that includes an extension of Plotkin's lgg theorem to the equational case. We demonstrate the potential power of E-generalization by three example applications: computation of suggestions for auxiliary lemmas in equational inductive proofs, computation of construction laws for given term sequences, and learning of screen editor command sequences.     

Evolving Recursive Programs by Using Adaptive Grammar Based Genetic Programming

Genetic programming (GP) extends traditional genetic algorithms to automatically induce computer programs. GP has been applied in a wide range of applications such as software re-engineering, electrical circuits synthesis, knowledge engineering, and data mining. One of the most important and challenging research areas in GP is the investigation of ways to successfully evolve recursive programs. A recursive program is one that calls itself either directly or indirectly through other programs. Because recursions lead to compact and general programs and provide a mechanism for reusing program code, they facilitate GP to solve larger and more complicated problems. Nevertheless, it is commonly agreed that the recursive program learning problem is very difficult for GP. In this paper, we propose techniques to tackle the difficulties in learning recursive programs. The techniques are incorporated into an adaptive Grammar Based Genetic Programming system (adaptive GBGP). A number of experiments have been performed to demonstrate that the system improves the effectiveness and efficiency in evolving recursive programs. Communicated by: William B. Langdon An erratum to this article is available at .     

Expression of syntactic and semantic features in logic-based grammars

In this paper, we introduce and initiate a formalism to represent syntactic and semantic features in logic-based grammars. We also introduce technical devices to express feature-checking and feature-inheritance mechanisms. This leads us to propose some extensions to the basic unification mechanism of PROLOG. Finally, we consider the problem of long-distance dependency relations between constituents in gapping grammars rules from the point of view of morphosyntactic features that may change depending on the position occupied by the moved constituents. What we propose is not a new linguistic theory about features, but rather a formalism and a set of tools that we think will be useful to grammar writers to describe features and their relations in grammar rules.     

Expressing unrestricted grammars by extended definite clause grammars1

A definition of extended definite clause grammars and their relationship to unrestricted grammars are presented. A method for translating extended definite clause grammars describing unrestricted grammars into executable prolog programs is given. Three different parsing techniques are presented, and for each a complete presentation of how to incorporate unrestricted grammars in the actual formalism is done. Extended definite clause grammar is a powerful formalism usable for specifying grammars in natural language processing systems.     

Incremental inconsistency detection with low memory overhead

Ensuring models’ consistency is a key concern when using a model‐based development approach. Therefore, model inconsistency detection has received significant attention over the last years. To be useful, inconsistency detection has to be sound, efficient, and scalable. Incremental detection is one way to achieve efficiency in the presence of large models. In most of the existing approaches, incrementalization is carried out at the expense of the memory consumption that becomes proportional to the model size and the number of consistency rules. In this paper, we propose a new incremental inconsistency detection approach that only consumes a small and model size‐independent amount of memory. It will therefore scale better to projects using large models and many consistency rules. Copyright © 2012 John Wiley & Sons, Ltd.     

Termination of Nested and Mutually Recursive Algorithms

This paper deals with automated termination analysis for functional programs. Previously developed methods for automated termination proofs of functional programs often fail for algorithms with nested recursion and they cannot handle algorithms with mutual recursion.We show that termination proofs for nested and mutually recursive algorithms can be performed without having to prove the correctness of the algorithms simultaneously. Using this result, nested and mutually recursive algorithms do no longer constitute a special problem and the existing methods for automated termination analysis can be extended to nested and mutual recursion in a straightforward way. We give some examples of algorithms whose termination can now be proved automatically (including well-known challenge problems such as McCarthys f_91 function).     

On the implicit acquisition of a context-free grammar by a simple recurrent neural network

The performance of a simple recurrent neural network on the implicit acquisition of a context-free grammar is re-examined and found to be significantly higher than previously reported by Elman. This result is obtained although the previous work employed a multilayer extension of the basic form of simple recurrent network and restricted the complexity of training and test corpora. The high performance is traced to a well-organized internal representation of the grammatical elements, as probed by a principal-component analysis of the hidden-layer activities. From the next-symbol-prediction performance on sentences not present in the training corpus, a capacity of generalization is demonstrated.     

Proving termination of context-sensitive rewriting by transformation

Context-sensitive rewriting (CSR) is a restriction of rewriting that forbids reductions on selected arguments of functions. With CSR, we can achieve a terminating behavior with non-terminating term rewriting systems, by pruning (all) infinite rewrite sequences. Proving termination of CSR has been recently recognized as an interesting problem with several applications in the fields of term rewriting and programming languages. Several methods have been developed for proving termination of CSR. Specifically, a number of transformations that permit treating this problem as a standard termination problem have been described. The main goal of this paper is to contribute to a better comprehension and practical use of transformations for proving termination of CSR. We provide new completeness results regarding the use of the transformations in two restricted (but relevant) settings: (a) proofs of termination of canonical CSR and (b) proofs of termination of CSR by using transformations together with simplification orderings. We have also made an experimental evaluation of the transformations, which complements the theoretical analysis from a practical point of view. This leads to new hierarchies of the transformations which are useful to guide their practical use when implementing tools for proving termination of CSR.     

A web-based topology optimization program

The paper presents a web-based interface for a topology optimization program. The program is accessible over the World Wide Web at the address http://www.topopt.dtu.dk. The paper discusses implementation issues and educational aspects as well as statistics and experience with the program. Received September 29, 2000     

Proof theory of many-valued logic—linear optimization—logic design: connections and interactions

 In this paper proof theory of many-valued logic is connected with areas outside of logic, namely, linear optimization and computer aided logic design. By stating these not widely-known connections explicitly, I want to encourage interaction between the mentioned disciplines. Once familiar with the others’ terminology, I believe that the respective communities can greatly benefit from each other. Received: 20 March 1997 / Accepted: 1 April 1997     

不可否认协议分析的扩展ZQZ逻辑方法

不可否认协议必须满足存活性、不可否认性、公平性和时限性,但当前大多数形式化方法只能分析该类协议的部分性质,证明或证伪协议逻辑的部分正确性.本文通过向ZQZ逻辑添加时间表达式,提出了一种适用于不可否认协议建模与分析的扩展ZQZ逻辑方法,包括推理规则和安全性质模型.展示新方法的应用时,使用其分析了ZG和KPB这两个局部逻辑正确性已知的两方不可否认协议,以及YLL这个逻辑正确性尚在讨论的基于区块链的多方不可否认协议.实验显示,对前两个协议的分析结果与既有事实相符,对第三个协议的分析发现其无法为收方提供设计者所宣称的时限性.以上结论从逆向工程角度佐证了扩展ZQZ逻辑方法是一种行之有效的不可否认协议分析新方法.     

考虑装置运行惯性的炼油过程生产作业优化研究

针对炼油过程生产装置运行的大惯性特性,研究了装置生产方案切换作业的调度优化问题。通过分析装置运行惯性及其产生的方案切换过渡过程,给出了调度优化的作业时间、方案切换和物料加工特点,利用逻辑命题进行了模型化描述。在此基础上,基于连续时间表达,建立了炼油过程生产作业调度优化模型,实现生产利润最大化。通过一个炼油厂生产实例验证了模型的可行性和有效性。