Queries = examples + counterexamples

Database queries can be expressed as unordered collections of examples and counterexamples. The resulting languages are intuitive, first order complete, and applicable to a variety of data models including relational, object oriented, and visual models. This class of languages based on examples and counterexamples employ a minimal number of constructs with no sequencing or nesting of the constructs implied, allowing a simple and uniform theoretical analysis of their syntax, semantics, and completeness.     

Fixpoint iteration with subsumption in deductive databases

Declarative languages for deductive and object-oriented databases require some high-level mechanism for specifying semantic control knowledge. This paper proposes user-supplied subsumption information as a paradigm to specify desired, prefered or useful deductions at the meta level. For this purpose we augment logic programming by subsumption relations and succeed to extend the classical theorems for least models, fixpoints and bottom-up evaluation accordingly. Moreover, we provide a differential fixpoint operator for efficient query evaluation in deductive databases. This operator discards subsumed tuples on the fly. We also exemplify the ease of use of this programming methodology. In particular, we demonstrate how heuristic AI search procedures can be integrated into deductive databases in this way.This article is a revised and extended version of (Köstler et al., 1993)     

A logic-based integration of active and deductive databases

A logic-based approach to the specification of active database functionality is presented which not only endows active databases with a well-defined and well-understood formal semantics, but also tightly integrates them with deductive databases. The problem of endowing deductive databases with rule-based active behaviour has been addressed in different ways. Typical approaches include accounting for active behaviour by extending the operational semantics of deductive databases, or, conversely, accounting for deductive capabilities by constraining the operational semantics of active databases. The main contribution of the paper is an alternative approach in which a class of active databases is defined whose operational semantics is naturally integrated with the operational semantics of deductive databases without either of them strictly subsuming the other. The approach is demonstrated via the formalization of the syntax and semantics of an active-rule language that can be smoothly incorporated into existing deductive databases, due to the fact that the standard formalization of deductive databases is reused, rather than altered or extended. One distinctive feature of the paper is its use of ahistory, as defined in the Kowalski-Sergot event-calculus, to define event occurrences, database states and actions on these. This has proved to be a suitable foundation for a comprehensive logical account of the concept set underpinning active databases. The paper thus contributes a logical perspective to the ongoing task of developing a formal theory of active databases. Alvaro Adolfo Antunes Fernandes, Ph.D.: He received a B.Sc. in Economics (Rio de Janeiro, 1984), an M.Sc. in Knowledge-Based Systems (Edinburgh, 1990) and a Ph.D. in Computer Science (Heriot-Watt, 1995). He worked as a Research Associate at Heriot-Watt University from December 1990 until December 1995. In January 1996 he joined the Department of Mathematical and Computing Sciences at Goldsmiths College, University of London, as a Lecturer. His current research interests include advanced data- and knowledge-base technology, logic programming, and software engineering. M. Howard Williams, Ph.D., D.Sc.: He obtained his Ph.D. in ionospheric physics and recently a D.Sc. in Computer Science. He was appointed as the first lecturer in Computer Science at Rhodes University in 1970. During the following decade he rose to Professor of Computer Science and in 1980 was appointed as Professor of Computer Science at Heriot-Watt University. From 1980 to 1988 he served as Head of Department and then as director of research until 1992. He is now head of the Database Research Group at Heriot-Watt University. His current research interests include active databases, deductive objectoriented databases, spatial databases, parallel databases and telemedicine. Norman W. Paton, Ph.D.: He received a B.Sc. in Computing Science from the University of Aberdeen in 1986. From 1986 to 1989 he worked as a Research Assistant at the University of Aberdeen, receiving a Ph. D. in 1989. From 1989 to 1995 he was a Lecturer in Computer Science at Heriot-Watt University. Since July 1995, he has been a Senior Lecturer in Department of Computer Science at the University of Manchester. His current research interests include active databases, deductive object-oriented databases, spatial databases and database interfaces.     

Resource location in large scale heterogeneous and autonomous databases

In many large organizations there has been a proliferation of database systems to handle ever increasing volumes of information. In order to explore a potentially huge on-line information space, we must develop an architecture which allows for the dynamic data driven construction of inter-database node relationships in an incremental manner. In this paper we introduce the FINDIT architecture which uses informationmeta-types to provide a basis for such an organization and, consequently, provides a platform for interoperability. A distinction is made between theinformation andinter-node relationship spaces to achieve scalability. Tassili language primitives are used for the incremental building of dynamic inter-node relationships based upon usage considerations.     

Linear logic for deductive databases

This paper deals with deductive databases in linear logic. The semantics of queries, views, constraints, and (view) updates are defineddeclaratively in linear logic. In constrast to classical logic, we can formalise non-shared view, transition constraints, and (view) updates easily. Various proof search strategies are presented along with an algorithm for query evaluation from a bottom-up direction. An additional advantage is that the associated meaning of a given relation can be defined in terms of the validity of a legal update in a given relation. We also defined formally the update principles and showed the correctness of the update translation algorithms. In this approach, we provide virtual view updates along with real view updates, and view DELETIONs are special cases of view REPLACEMENTs. This permits three transactional view update operations (INSERTION, DELETION, REPLACEMENT) in comparison to only (INSERTION, DELETION) in most existing systems. Dong-Tsan Lee, Ph.D.: He is a computer scientist in the Department of Computer Science at University of Western Australia, Perth, Western Australia, Australia. He received the B.S. and M.S. degrees from the Department of Computer Science at National Chiao-Tung University, Taiwan, in 1983 and 1985, respectively, and earned the Ph.D. degree from the Department of Computer Science at University of Western Australia. His research interests include database and artificial intelligence, linear logic, and real-time software engineering. Chin-Ping Tsang, Ph.D.: He is currently an associate professor in the Department of Computer Science at University of Western Australia, Perth, Western Australia, Australia. He received the Ph.D. degree from the University of Western Australia. He was the head of the Department of Computer Science at the University of Western Australia from 1994 to 1997. His research interests include artificial intelligence, non-classicial logic and neural nets.     

Verifying local stratifiability of logic programs and databases

In this paper, we deal with the problem of verifying local stratifiability of logic programs and databases presented by Przymusinski. The notion of dependency graphs is generalized from representing the priority relation between predicate symbols to representing the priority between atoms. Necessary and sufficient conditions for the local stratifiability of logic programs are presented and algorithms for performing the verification are developed. Finally, we prove that a database DB containing clauses with disjunctive consequents can easily be converted into a logic program P such that DB is locally stratified iff P is locally stratified. Yi-Dong Shen, Dr.: Department of Computer Science, Chongqing University, Chongqing, 630044, P.R. China (Present Address) c/o Ping Ran, Department of Heat Power Engineering, Chongqing UniversityResearch interests: Artificial Intelligence, Deductive Databases, Logic Programming, Non-Monotonic Reasoning, Parallel Processing     

Querying datalog with arrays: Design and implementation issues

This paper deals with the implementation of logic queries where array structures are manipulated. Both top-down and bottom-up implementations of the presented logic language, called Datalog ^A , are considered. Indeed, SLD-resolution is generalized to realize Datalog ^A top-down query answering. Further, a fixpoint based evaluation of Datalog ^A queries is introduced, which forms the basis for efficient bottom-up implementation of queries obtained by generalizing rewriting techniques such as magic set method to the case of Datalog ^A programs.Work partially supported by a European Union grant under the EC-US project DEUS EX MACHINA: nondeterminism for deductive databases and by a MURST grant (40% share) under the project Sistemi formali e strumenti per basi di dati evolute.     

Uncertain deductive databases: A hybrid approach

Uncertainty in deductive databases and logic programming has been modeled using a variety of (numeric and non-numeric) formalisms in the past, including probabilistic, possibilistic, and fuzzy set-theoretic approaches, and many valued logic programming. In this paper, we consider a hybrid approach to the modeling of uncertainty in deductive databases. Our model, called deductive IST (DIST) is based on an extension of the Information Source Tracking (IST) model, recently proposed for relational databases. The DIST model permits uncertainty to be modeled and manipulated in essentially qualitative terms with an option to convert qualitative expressions of uncertainty into numeric form (e.g., probabilities). An uncertain deductive database is modeled as a Horn clause program in the DIST framework, where each fact and rule is annotated with an expression indicating the “sources” contributing to this information and their nature of contribution. (1) We show that positive DIST programs enjoy the least model/least fixpoint semantics analogous to classical logic programs. (2) We show that top-down (e.g., SLD-resolution) and bottom-up (e.g., magic sets rewriting followed by semi-naive evaluation) query processing strategies developed for datalog can be easily extended to DIST programs. (3) Results and techniques for handling negation as failure in classical logic programming can be easily extended to DIST. As an illustration of this, we show how stratified negation can be so extended. We next study the problem of query optimization in such databases and establish the following results. (4) We formulate query containment in qualitative as well as quantitative terms. Intuitively, our qualitative sense of containment would say a query Q₁ is contained in a query Q₂ provided for every input database D, for every tuple t, t ε Q₂(D) holds in every “situation” in which t ε Q₁(D) is true. The quantitative notion of containment would say Q₁ is contained in Q₂ provided on every input, the certainty associated with any tuple computed by Q₁ is no more than the certainty associated with the same tuple by Q₂ on the given input. We also prove that qualitative and quantitative notions of containment (both absolute and uniform versions) coincide. (5) We establish necessary and sufficient conditions for the qualitative containment of conjunctive queries. (6) We extend the well-known chase technique to develop a test for uniform containment and equivalence of positive DIST programs. (7) Finally, we prove that the complexity of testing containment of conjunctive DIST queries remains the same as in the classical case when number of information sources is regarded as a constant (so, it's NP-complete in the size of the queries). We also show that testing containment of conjunctive queries is co-NP-complete in the number of information sources.     

Stochastic Concurrent Constraint Programming

We present a stochastic version of Concurrent Constraint Programming (CCP), where we associate a rate to each basic instruction that interacts with the constraint store. We give an operational semantic that can be provided either with a discrete or a continuous model of time. The notion of observables is discussed, both for the discrete and the continuous version, and a connection between the two is given. Finally, a possible application for modeling biological networks is presented.     

Relating the implementation techniques of functional and functional logic languages

Functional logic languages are declarative programming languages that integrate the programming paradigms of functional and logic languages within a single framework. They are extensions of functional languages with principles derived from logic programmingNarrowing, the evaluation mechanism of functional logic languages, can be defined as a generalization ofreduction, the evaluation mechanism of purely functional languages. The unidirectional pattern matching, which is used for parameter passing in functional languages, is simply replaced by the bidirectionalunification known from logic programming languages. We show in this paper, how to extend a reduction machine, that has been designed for the evaluation of purely functional programs to a machine that performs narrowing. The necessary extensions concern the realization of unification and backtracking, for which we fall back upon the methods of Warren’s Prolog engine.²¹⁾ The narrowing machine embodies an optimized treatment of deterministic computations. A complete specification of the reduction and the narrowing machine and of the translation of a sample language into abstract machine code is given. Comparative results of a C-implementation of the reduction and the narrowing machine show that the time overhead of the more complex narrowing evaluation is, in general, less than 10% of the reduction evaluation.     

Reverse engineering database queries from examples: State-of-the-art,challenges, and research opportunities

With the popularization of data access and usage, an increasing number of users without expert knowledge of databases is required to perform data interactions. Often, these users face the challenges of writing and reformulating database queries, which consume a considerable amount of time and frequently yield unsatisfactory results. To facilitate this human–database interaction, researchers have investigated the Query By Example (QBE) paradigm in which database queries are (semi) automatically discovered from data examples given by users. This paradigm allows non-database experts to formulate queries without relying on complex query languages. In this context, this work aims to present a systematic review of the recent developments, open challenges, and research opportunities of the QBE reported in the literature. This work also describes strategies employed to leverage efficient example acquisition and query reverse engineering. The obtained results show that recent research developments have focused on enhancing the expressiveness of produced queries, minimizing user interaction, and enabling efficient query learning in the context of data retrieval, exploration, integration, and analytics. Our findings indicate that future research should concentrate efforts to provide innovative solutions to the challenges of improving controllability and transparency, considering diverse user preferences in the processes of learning personalized queries, ensuring data quality, and improving the support of additional SQL features and operators.     

API2MoL: Automating the building of bridges between APIs and Model-Driven Engineering

Context

A software artefact typically makes its functionality available through a specialized Application Programming Interface (API) describing the set of services offered to client applications. In fact, building any software system usually involves managing a plethora of APIs, which complicates the development process. In Model-Driven Engineering (MDE), where models are the key elements of any software engineering activity, this API management should take place at the model level. Therefore, tools that facilitate the integration of APIs and MDE are clearly needed.

Objective

Our goal is to automate the implementation of API-MDE bridges for supporting both the creation of models from API objects and the generation of such API objects from models. In this sense, this paper presents the API2MoL approach, which provides a declarative rule-based language to easily write mapping definitions to link API specifications and the metamodel that represents them. These definitions are then executed to convert API objects into model elements or vice versa. The approach also allows both the metamodel and the mapping to be automatically obtained from the API specification (bootstrap process).

Method

After implementing the API2MoL engine, its correctness was validated using several APIs. Since APIs are normally large, we then developed a tool to implement the bootstrap process, which was also validated.

Results

We provide a toolkit (language and bootstrap tool) for the creation of bridges between APIs and MDE. The current implementation focuses on Java APIs, although its adaptation to other statically typed object-oriented languages is straightforward. The correctness, expressiveness and completeness of the approach have been validated with the Swing, SWT and JTwitter APIs.

Conclusion

API2MoL frees developers from having to manually implement the tasks of obtaining models from API objects and generating such objects from models. This helps to manage API models in MDE-based solutions.     

Circular attribute grammars with remote attribute references and their evaluators

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 proposescircular 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 amostly static evaluator. The performance of the proposed evaluator has been measured and compared with dynamic and static evaluators. Akira Sasaki: He is a research fellow of the Advanced Clinical Research Center in the Institute of Medical Science at the University of Tokyo. He received his BSc and MSc from Tokyo Institute of Technology, Japan, in 1994 and 1996, respectively. His research interests include programming languages, programming language processors and programming environments, especially compiler compilers, attribute grammars and systematic debugging. He is a member of the Japan Society for Software Science and Technology. Masataka Sassa, D.Sc.: He is Professor of Computer Science at Tokyo Institute of Technology. He received his BSc, MSc and DSc from the University of Tokyo, Japan, in 1970, 1972 and 1978, respectively. His research interests include programming languages, programming language processors and programming environments, currently he is focusing on compiler optimization, compiler infrastructure, attribute grammars and systematic debugging. He is a member of the ACM, IEEE Computer Society, Japan Society for Software Science and Technology, and Information Processing Society of Japan.     

Formal Semantics and Analysis of Component Connectors in Reo

We present an operational semantics for a component composition language called Reo. Reo connectors exogenously compose and coordinate the interactions among individual components that comprise a complex system, into a coherent collaboration. The formal semantics we present here paves the way for a rigorous study of the behavior of component composition mechanisms. To demonstrate the feasibility of such a rigorous approach, we give a faithful translation of Reo semantics into the Maude term rewriting language. This translation allows us to exploit the rewriting engine and the model-checking module in the Maude tool-set to symbolically run and model-check the behavior of Reo connectors.     

Query evaluation in recursive databases: bottom-up and top-down reconciled

It is desirable to answer queries posed to deductive databases by computing fixpoints because such computations are directly amenable to set-oriented fact processing. However, the classical fixpoint procedures based on bottom-up processing — the naive and semi-naive methods — are rather primitive and often inefficient. In this article, we rely on bottom-up meta-interpretation for formalizing a new fixpoint procedure that performs a different kind of reasoning: We specify a top-down query answering method, which we call the Backward Fixpoint Procedure. Then, we reconsider query evaluation methods for recursive databases. First, we show that the methods based on rewriting on the one hand, and the methods based on resolution on the other hand, implement the Backward Fixpoint Procedure. Second, we interpret the rewritings of the Alexander and Magic Set methods as specializations of the Backward Fixpoint Procedure. Finally, we argue that such a rewriting is also needed in a database context for implementing efficiently the resolution-based methods. Thus, the methods based on rewriting and the methods based on resolution implement the same top-down evaluation of the original database rules by means of auxiliary rules processed bottom-up.     

基于VC++与MATLAB混编的故障信号分析系统设计

本软件是以Visual C++6.0为开发平台,调用MATLAB引擎,利用MATLAB强大的数据分析、数值计算、信号分析、绘图显示能力及丰富的函数库,对采集信号进行时域分析、傅立叶分析及小波分析,并基于BP神经网络对机械设备进行故障诊断。同时VC通过ADO与ACCESS数据库进行通信,将信号分析过程中产生的时域特征值、频域特征值、神经网络样本数据与测试数据及诊断结果存储到数据库中。VC++、MATLAB、ACCESS三者相结合,发挥各自的优势,大大缩短了软件的开发周期,使程序代码得到简化,提高了系统的运行效率。     

基于多层结构的应用服务器开发与研究

介绍了一种以Sybase的应用服务器Jaguar CTS为平台,从C/S两层应用到多层及Web数据库应用的实现技术,对多层结构数据库应用开发进行了研究探讨,论述了应用服务器相应的程序开发特性。     

基于稳定模型的软件多样性与安全初探

该文简要阐述了软件多样性与安全性的关系后,基于STABLEMODEL是逻辑程序的语义模型的观点,从软件与逻辑程序设计的关联出发,提出了用逻辑程序设计实现软件多样性的方法。论文首先介绍了逻辑程序中稳定模型的形成、定义、演算方法,通过逻辑程序与稳定模型之间存在的多对一的映射关系,产生软件的多样性。最后,通过具体的分析,提出了基于稳定模型的程序多样性演化方法,这一方法实现了从一个源程序到一系列等价程序的多样性演化,从而提高了系统的鲁棒性和安全性。     

Enhancing accuracy and expressive power of range query answers over incomplete spatial databases via a novel reasoning approach

Modern spatial database applications built on top of distributed and heterogeneous spatial information sources such as conventional spatial databases underlying Geographical Information Systems (GIS), spatial data files and spatial information acquired or inferred from the Web, suffer from data integration and topological consistency problems. This more-and-more conveys in incomplete information, which makes answering range queries over incomplete spatial databases a leading research challenge in spatial database systems research. A significant instance of this setting is represented by the application scenario in which the geometrical information on a sub-set of spatial database objects is incomplete whereas the spatial database still stores topological relations among these objects (e.g., containment relations). Focusing on the spatial database application scenario above, in this paper we propose and experimentally assess a novel technique for efficiently answering range queries over incomplete spatial databases via integrating geometrical information and topological reasoning. We also propose I-SQE (Spatial Query Engine for Incomplete Information), an innovative query engine implementing this technique. Our proposed technique results not only effective but also efficient against both synthetic and real-life spatial data sets, and it finally allows us to enhance the quality and the expressive power of retrieved answers by meaningfully taking advantages from the amenity of representing spatial database objects via both the geometrical and the topological level.