Haiming Chen

Spiking neural P systems with extended rules: universality and languages

We consider spiking neural P systems with rules allowed to introduce zero, one, or more spikes at the same time. The motivation comes both from constructing small universal systems and from generating strings; previous results from these areas are briefly recalled. Then, the computing power of the obtained systems is investigated, when considering them as number generating and as language generating devices. In the first case, a simpler proof of universality is obtained, while in the latter case we find characterizations of finite and recursively enumerable languages (without using any squeezing mechanism, as it was necessary in the case of standard rules). The relationships with regular languages are also investigated.

Inclusion Test Algorithms for One-Unambiguous Regular Expressions

One-unambiguous regular expressions are used in DTD. It is known that inclusion for one-unambiguous regular expressions is in PTIME. However, there has been no study on algorithms for the inclusion. In this paper we present algorithms for checking inclusion of one-unambiguous regular expressions. A classical way is based on automata, following which one algorithm is provided and improvements are given. The other algorithm is based on derivatives, utilizing a property introduced here that the number of derivatives of a one-unambiguous regular expression is finite. We conducted preliminary experiments by implementing typechecking of XML using the algorithms. The results show that typechecking using the new algorithms is more efficient than the typechecking used for XDuce.

Checking determinism of regular expressions with counting

In this paper, we first present characterizations of weak determinism for regular expressions with counting, based on which we develop an O ( | Σ E | | E | ) time algorithm to check whether an expression E with counting is weakly deterministic, where Σ E is the set of distinct symbols in the expression E. Moreover, our algorithm can locate nondeterminism in subexpressions, which is useful for diagnosing purpose. Then we present a characterization of strong determinism for regular expressions with counting, and study the relations between weak determinism and strong determinism. Based on these, we give an O ( | E | ) time algorithm to check strong determinism, improving the previous upper bound of O ( | E | 3 ) time. Finally, historically there has been another definition of strong determinism for standard regular expressions, which we call restricted strong determinism in this paper. We extend this definition to expressions with counting, establish the relation between the two definitions, and give an O ( | E | ) time algorithm to check restricted strong determinism for regular expressions with counting.

A Toolkit for Generating Sentences from Context-Free Grammars

Producing sentences from a grammar, according to various criteria, is required in many applications. It is also a basic building block for grammar engineering. This paper presents a toolkit for context-free grammars, which mainly consists of several algorithms for sentence generation or enumeration and for coverage analysis for context-free grammars. The toolkit deals with general context-free grammars. Besides providing implementations of algorithms, the toolkit also provides a simple graphical user interface, through which the user can use the toolkit directly. The toolkit is implemented in Java and is available at http://lcs.ios.ac.cn/ hiwu/toolkit.php. In the paper, the overview of the toolkit and the description of the GUI are presented, and experimental results and preliminary applications of the toolkit are also contained.

Deciding Determinism of Regular Languages

We investigate the problem to decide for DFAs, NFAs and regular expressions whether they describe deterministic regular languages. For DFAs with limited alphabet size we show the NL-completeness (nondeterministic logarithmic space-completeness) of the problem. Brüggemann-Klein and Wood (Inf. Comput. 142(2), 182–206, (1998)) gave an algorithm deciding for a minimal DFA whether it recognizes a deterministic regular language. Their algorithm requires polynomial time. Based on this algorithm we construct an algorithm for those DFAs which are not necessarily minimal, but limited in the size of the alphabet. We first focus on the case that the DFAs are minimal and extend to general DFAs later on. The new algorithm is substantially modified in contrast to the original one and uses structural properties of minimal DFAs and of special subautomata of the DFAs, called orbit automata. This algorithm runs in nondeterministic logarithmic space. After that we show the NL-hardness of the problem. For NFAs and regular expressions with arbitrary alphabets the problem is shown to be in PSPACE by Czerwiński et al. (2013) (and, in fact, to be PSPACE-complete). Their approach resulted in an algorithm working with space 𝒪(x4)

Discovering Restricted Regular Expressions with Interleaving

\mathcal {O}(x^{4})

Assisting the design of XML schema: diagnosing nondeterministic content models

. However, our approach for the NL-algorithm can be modified to get an algorithm for NFAs and regular expressions using just quadratic space.

Practical Study of Subclasses of Regular Expressions in DTD and XML Schema

Discovering a concise schema from given XML documents is an important problem in XML applications. In this paper, we focus on the problem of learning an unordered schema from a given set of XML examples, which is actually a problem of learning a restricted regular expression with interleaving using positive example strings. Schemas with interleaving could present meaningful knowledge that cannot be disclosed by previous inference techniques. Moreover, inference of the minimal schema with interleaving is challenging. The problem of finding a minimal schema with interleaving is shown to be NP-hard. Therefore, we develop an approximation algorithm and a heuristic solution to tackle the problem using techniques different from known inference algorithms. We do experiments on real-world data sets to demonstrate the effectiveness of our approaches. Our heuristic algorithm is shown to produce results that are very close to optimal.

Determinacy and rewriting of conjunctive queries over unary database schemas

One difficulty in the design of XML Schema is the restriction that the content models should be deterministic, i.e., the unique particle attribution (UPA) constraint, which means that the content models are deterministic regular expressions. This determinism is defined semantically without known syntactic definition for it, thus making it difficult for users to design. Presently however, no work can provide diagnostic information if content models are nondeterministic, although this will be of great help for designers to understand and modify nondeterministic ones. In the paper we investigate algorithms that check if a regular expression is deterministic and provide diagnostic information if the expression is not deterministic. With the information provided by the algorithms, designers will be clearer about why an expression is not deterministic. Thus it contributes to reducing the difficulty of designing XML Schema.

Deterministic Regular Expressions withźInterleaving

DTD and XSD are two popular schema languages widely used in XML documents. Most content models used in DTD and XSD essentially consist of restricted subclasses of regular expressions. However, existing subclasses of content models are all defined on standard regular expressions without considering counting and interleaving. Through the investigation on the real world data, this paper introduces a new subclass of regular expressions with counting and interleaving. Then we give a practical study on this new subclass and five already known subclasses of content models. One distinguishing feature of this paper is that the data set is sufficiently large compared with previous relevant work. Therefore our results are more accurate. In addition, based on this large data set, we analyze the different features of regular expressions used in practice. Meanwhile, we are the first to simultaneously inspect the usage of the five subclasses and analyze different reasons dissatisfying the corresponding definitions. Furthermore, since W3C standard requires the content models to be deterministic, the determinism of content models is also tested by our validation tools.