Closed World Assumption Research Articles

Empirical assessment of object-oriented implementations with multiple inheritance and static typing

Object-oriented languages involve a threefold tradeoff between runtime efficiency, expressiveness (multiple inheritance), and modularity, i.e. open-world assumption (OWA). Runtime efficiency is conditioned by both the implementation technique and compilation scheme . The former specifies the data structures that support method invocation, attribute access and subtype testing. The latter consists of the production line of an executable from the source code. Many implementation techniques have been proposed and several compilation schemes can be considered from fully global compilation under the closed-world assumption (CWA) to separate compilation with dynamic loading under the OWA, with midway solutions. This article reviews a significant subset of possible combinations and presents a systematic, empirical comparison of their respective efficiencies with all other things being equal . The testbed consists of the Prm compiler that has been designed for this purpose. The considered techniques include C++ subobjects, coloring, perfect hashing, binary tree dispatch and caching. A variety of processors were considered. Qualitatively, these first results confirm the intuitive or theoretical abstract assessments of the tested approaches. As expected, efficiency increases as CWA strengthens. From a quantitative standpoint, the results are the first to precisely compare the efficiency of techniques that are closely associated with specific languages like C++ and Eiffel. They also confirm that perfect hashing should be considered for implementing Java and .Net interfaces.

A Dualism Based Semantics Formalization Mechanism for Model Driven Engineering

Firstly this article presents a thorough discussion of semantics formalization related issues in model driven engineering (MDE). Then motivated for the purpose of software implementation, and attempts to overcome the shortcomings of incompleteness and context-sensitivity in the existing models, we propose to study formalization of semantics from a cognitive background. Issues under study cover the broad scope of overlap vs. incomplete vs. complete, closed world assumption (CWA) vs. open world assumption (OWA), Y(Yes)/N(No) vs. T(True)/F(False), subjective (SUBJ) vs. objective (OBJ), static vs. dynamic, unconsciousness vs. conscious, human vs. machine aspects, and so forth. A semantics formalization approach called EID-SCE (Existence Identification Dualism-Semantics Cosmos Explosion) is designed to meet both the theoretical investigation and implementation of the proposed formalization goals. EID-SCE supports the measure/evaluation in a {complete, no overlap} manner whether a given concept or feature is an improvement. Some elementary cases are also shown to demonstrate the feasibility of EID-SCE.

General default logic

In this paper, we propose a new nonmonotonic logic called general default logic. On the one hand, it generalizes Reiter's default logic by adding to it rule-like operators used in logic programming. On the other hand, it extends logic programming by allowing arbitrary propositional formulas. We show that with this new logic, one can formalize naturally rule constraints, generalized closed world assumptions, and conditional defaults. We show that under a notion of strong equivalence, sentences of this new logic can be converted to a normal form. We also investigate the computational complexity of various reasoning tasks in the logic, and relate it to some other nonmonotonic formalisms such as Lin and Shoham's logic of GK and Moore's autoepistemic logic.

Combining Description Logics and object oriented models in an information integration framework

We present an information integration system called SINTAGMA which supports the semantic integration of heterogeneous information sources using a meta data driven approach. The main idea of SINTAGMA is to build a so called Model Warehouse, containing several layers of integrated models connected by mappings. At the bottom of this hierarchy there are the models representing the actual information sources. Higher level models represent virtual databases which can be queried, as the mappings provide a precise description of how to populate these virtual sources using the concrete ones. The implementation of SINTAGMA uses constraints and logic programming, for example, the complex queries are translated into Prolog goals. This paper focuses on a recent development in SINTAGMA allowing the information expert to use Description Logic (DL) based ontologies in the development of high abstraction level conceptual models. Querying these models is performed using the Closed World Assumption as we argue that traditional Open World DL reasoning is less appropriate in the context of database oriented information integration environments.

OntoDLV: An ASP-based System for Enterprise Ontologies

Enterprise/Corporate ontologies are widely adopted to conceptualize business enterprise information. In this area, the semantic peculiarities of Answer Set Programming (ASP), like the Closed World Assumption (CWA) and the Unique Name Assumption (UNA), are more appropriate than the Ontology Web Language (OWL) assumptions, also because such ontologies frequently stem from relational databases, where both CWA and UNA are adopted. This article presents OntoDLV, a system based on ASP for the specification and reasoning on enterprise ontologies. OntoDLV implements a powerful ontology representation language, called OntoDLP, extending (disjunctive) ASP with all the main ontology features including classes, inheritance, relations and axioms. OntoDLP is strongly typed, and includes also complex type constructors, like lists and sets. Importantly, OntoDLV supports a powerful interoperability mechanism with OWL, allowing the user to retrieve information from OWL ontologies, and build rule-based reasoning on top of OWL ontologies. The system is already used in a number of real-world applications including agent-based systems, information extraction, and text classification.

Towards a logical reconstruction of a theory for locally closed databases

The Closed World Assumption (CWA) on databases expresses the assumption that an atom not in the database is false. This assumption is applicable only in cases where the database has complete knowledge about the domain of discourse. In this article, we investigate locally closed databases, that is: databases that are sound but partially incomplete about their domain. Such databases consist of a standard database instance, augmented with a collection of Local Closed World Assumptions (LCWAs). A LCWA is a “local” form of the CWA, expressing that a database relation is complete in a certain area, called a window of expertise . In this work, we study locally closed databases both from a knowledge representation and from a computational perspective. At the representation level, the approach taken in this article distinguishes between the data that is conveyed by a database and the metaknowledge about the area in which the data is complete. We study the semantics of the LCWA's and relate it to several knowledge representation formalisms. At the reasoning level, we study the complexity of, and algorithms for two basic reasoning tasks: computing certain and possible answers to queries and determining whether a database has complete knowledge on a query. As the complexity of these tasks is unacceptably high, we develop efficient approximate methods for query answering. We also prove that for useful classes of queries and locally closed databases, these methods are optimal , and thus they solve the original query in a tractable way. As a result, we obtain classes of queries and locally closed databases for which query answering is tractable.

Escape Analysis: Embrace the Open World

PDF HTML阅读 XML下载 导出引用 引用提醒 在开放世界中实现逃逸分析 DOI: 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: Supported by the National Natural Science Foundation of Chinaunder Grant No.60573084(国家自然科学基金) Escape Analysis: Embrace the Open World Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:逃逸分析(escape analysis)是一种可以有效减少Java程序中同步负载和内存堆分配压力的跨函数全局数据流分析算法.此前绝大多数逃逸分析的实现都基于一个所谓"封闭世界(closed world)"的前提:所有可能被执行的方法在做逃逸分析前都已经得知,并且,程序的实际运行不会改变它们之间的调用关系.但当真实的Java程序运行时,这样的假设并不成立.Java程序拥有的许多特性,例如动态类加载、调用本地函数以及反射程序调用等等,都将打破所谓"封闭世界"的约定.这样的真实运行环境被称为"开放世界".在开放世界中,实现逃逸分析将面临许多重要的问题,例如,能否正确、全面地捕捉动态载入的类和方法,并分析它们与原有程序的关系;逃逸分析算法的复杂性是否能够得以控制,以保证即时编译器的重新分析时间不会过长,等等.提出一个新的逃逸分析架构,它可以有效地处理上述开放世界所面临的问题.该分析架构将增量分析Java程序,动态捕获新载入和调用的类及方法,同时,在复杂性和精度之间进行权衡,正确、有效地降低程序的运行负载.该分析架构已经在Intel的开放式Java虚拟机系统ORP中实现,经过实际测试,可以有效地消除一些主要基准测试程序,如SPECjbb2000和SPECjvm98的db中70%～94%的同步操作,大幅度地提高15%～31%的程序的运行速度. Abstract:Prior implementations of escape analysis (EA) make a closed-world/whole-program assumption: All methods that can possibly be executed during the program execution are known statically. The Java programming language has several language features, e.g., dynamic class loading, native invocation and reflection, which break the closed-world assumption. These open-world features raise a major concern on the practicability and applicability of the prior approaches to Java applications that use or rely on the features. This paper proposes and evaluates a new escape analysis framework which handles the Java open-world features. The framework also provides a mechanism that controls the analysis complexity to reduce the runtime overhead with acceptable precision. The result shows that the EA framework, which is implemented in Intel's Open Runtime Platform on X86, eliminates 70% and 94% of dynamic synchronized operations and improves the runtime performance 15.77% and 31.28%, for SPECjbb2000 and db of SPECjvm98 respectively. 参考文献 相似文献 引证文献

Reconciling description logics and rules

Description logics (DLs) and rules are formalisms that emphasize different aspects of knowledge representation: whereas DLs are focused on specifying and reasoning about conceptual knowledge, rules are focused on nonmonotonic inference. Many applications, however, require features of both DLs and rules. Developing a formalism that integrates DLs and rules would be a natural outcome of a large body of research in knowledge representation and reasoning of the last two decades; however, achieving this goal is very challenging and the approaches proposed thus far have not fully reached it. In this paper, we present a hybrid formalism of MKNF + knowledge bases , which integrates DLs and rules in a coherent semantic framework. Achieving seamless integration is nontrivial, since DLs use an open-world assumption, while the rules are based on a closed-world assumption. We overcome this discrepancy by basing the semantics of our formalism on the logic of minimal knowledge and negation as failure (MKNF) by Lifschitz. We present several algorithms for reasoning with MKNF + knowledge bases, each suitable to different kinds of rules, and establish tight complexity bounds.

Extended RDF as a Semantic Foundation of Rule Markup Languages

Ontologies and automated reasoning are the building blocks of the Semantic Web initiative. Derivation rules can be included in an ontology to define derived concepts, based on base concepts. For example, rules allow to define the extension of a class or property, based on a complex relation between the extensions of the same or other classes and properties. On the other hand, the inclusion of negative information both in the form of negation-as-failure and explicit negative information is also needed to enable various forms of reasoning. In this paper, we extend RDF graphs with weak and strong negation, as well as derivation rules. The ERDF stable model semantics of the extended framework (Extended RDF) is defined, extending RDF(S) semantics. A distinctive feature of our theory, which is based on Partial Logic, is that both truth and falsity extensions of properties and classes are considered, allowing for truth value gaps. Our framework supports both closed-world and open-world reasoning through the explicit representation of the particular closed-world assumptions and the ERDF ontological categories of total properties and total classes.

Closed-world tracking of multiple interacting targets for indoor-sports applications

In this paper we present an efficient algorithm for tracking multiple players during indoor sports matches. A sports match can be considered as a semi-controlled environment for which a set of closed-world assumptions regarding the visual as well as the dynamical properties of the players and the court can be derived. These assumptions are then used in the context of particle filtering to arrive at a computationally fast, closed-world, multi-player tracker. The proposed tracker is based on multiple, single-player trackers, which are combined using a closed-world assumption about the interactions among players. With regard to the visual properties, the robustness of the tracker is achieved by deriving a novel sports-domain-specific likelihood function and employing a novel background-elimination scheme. The restrictions on the player’s dynamics are enforced by employing a novel form of local smoothing. This smoothing renders the tracking more robust and reduces the computational complexity of the tracker. We evaluated the proposed closed-world, multi-player tracker on a challenging data set. In comparison with several similar trackers that did not utilize all of the closed-world assumptions, the proposed tracker produced better estimates of position and prediction as well as reducing the number of failures.

On the Expressiveness of Levesque's Normal Form

Levesque proposed a generalization of a database called a proper knowledge base (KB), which is equivalent to a possibly infinite consistent set of ground literals. In contrast to databases, proper KBs do not make the closed-world assumption and hence the entailment problem becomes undecidable. Levesque then proposed a limited but efficient inference method V for proper KBs, which is sound and, when the query is in a certain normal form, also logically complete. He conjectured that for every first-order query there is an equivalent one in normal form. In this note, we show that this conjecture is false. In fact, we show that any class of formulas for which V is complete must be strictly less expressive than full first-order logic. Moreover, in the propositional case it is very unlikely that a formula always has a polynomial-size normal form.

Using views to generate efficient evaluation plans for queries

We study the problem of generating efficient, equivalent rewritings using views to compute the answer to a query. We take the closed-world assumption, in which views are materialized from base relations, rather than views describing sources in terms of abstract predicates, as is common when the open-world assumption is used. In the closed-world model, there can be an infinite number of different rewritings that compute the same answer, yet have quite different performance. Query optimizers take a logical plan (a rewriting of the query) as an input, and generate efficient physical plans to compute the answer. Thus our goal is to generate a small subset of the possible logical plans without missing an optimal physical plan. We first consider a cost model that counts the number of subgoals in a physical plan, and show a search space that is guaranteed to include an optimal rewriting, if the query has a rewriting in terms of the views. We also develop an efficient algorithm for finding rewritings with the minimum number of subgoals. We then consider a cost model that counts the sizes of intermediate relations of a physical plan, without dropping any attributes, and give a search space for finding optimal rewritings. Our final cost model allows attributes to be dropped in intermediate relations. We show that, by careful variable renaming, it is possible to do better than the standard “supplementary relation” approach, by dropping attributes that the latter approach would retain. Experiments show that our algorithm of generating optimal rewritings has good efficiency and scalability.

JTL

We present an overview of JTL (the Java Tools Language, pronounced "Gee-tel"), a novel language for querying JAVA [8] programs. JTL was designed to serve the development of source code software tools for JAVA, and as a small language which to aid programming language extensions to JAVA. Applications include definition of pointcuts for aspect-oriented programming, fixing type constraints for generic programming, specification of encapsulation policies, definition of micro-patterns, etc. We argue that the JTL expression of each of these is systematic, concise, intuitive and general.JTL relies on a simply-typed relational database for program representation, rather than an abstract syntax tree. The underlying semantics of the language is restricted to queries formulated in First Order Predicate Logic augmented with transitive closure (FOPL).Special effort was taken to ensure terse, yet readable expression of logical conditions. The JTL pattern <B>public abstract class</B>, for example, matches all abstract classes which are publicly accessible, while <B>class</B> (<B>public</B> clone();) matches all classes in which method clone is public. To this end, JTL relies on a DATALOG-like syntax and semantics, enriched with quantifiers and pattern matching which all but entirely eliminate the need for recursive calls.JTL's query analyzer gives special attention to the fragility of the "closed world assumption" in examining JAVA software, and determines whether a query relies on such an assumption.The performance of the JTL interpreter is comparable to that of JQuery after it generated its database cache, and at least an order of magnitude faster when the cache has to be rebuilt.

Advances in intelligent information processing

Advances in intelligent information processing

A different paradigm for expert systems: an introduction to logic programming and related knowledge representation issues

Abstract: Current expert system technology is 30 years old. Expert system shells find their origins in the work of early expert systems, most notably MYCIN which was developed at Stanford in the mid‐1970s. Even Prolog programmers are settling for less robust reasoning power. The logic programming community (from which both expert systems and Prolog arose) has made notable advances since those times. These advances are lacking from current expert system technology. The advances include a well‐developed theory of multiple forms of negation, an understanding of open domains and the closed world assumption, default reasoning with exceptions, reasoning with respect to time (i.e. a solution to the frame problem, and introspection with regard to previous beliefs), reasoning about actions, introspection, and maintaining multiple views of the world simultaneously.The contribution of this paper is to discuss these developments in a singular, integrated, practical, digestible manner. Some of these ideas exist in a variety of papers spread across decades. They also exist in the minds of a very small community of researchers. Some of these ideas are unpublished. The presentation in this paper is from a different point of view, and intended to be more comprehensive and pedagogical. The presentation is also intended to be accessible to a much wider audience. Both the synthesis and the simplicity of this presentation are absent from the literature.

Toward open-world software: Issues and challenges

Traditional software development is based on the closed-world assumption that the boundary between system and environment is known and unchanging. However, this assumption no longer works within today's unpredictable open-world settings, which demand techniques that let software react to changes by self-organizing its structure and self-adapting its behavior.

An algebra for specifying valid compound terms in faceted taxonomies

A faceted taxonomy is a set of taxonomies, each describing a given knowledge domain from a different aspect. The indexing of the domain objects is done using compound terms, i.e. conjunctive combinations of terms from the taxonomies. A faceted taxonomy has several advantages over a single taxonomy, including conceptual clarity, compactness, and scalability. A drawback, however, is the cost of identifying compound terms that are invalid, i.e. terms that do not apply to any object of the domain. This need arises both in indexing and retrieval, and involves considerable human effort for specifying the valid compound terms one by one. In this paper, we propose and present in detail an algebra which can be used to specify the set of valid compound terms in an efficient and flexible manner. It works on the basis of the original simple terms of the facets and a small set of positive and/or negative statements. In each algebraic operation, we adopt a closed-world assumption with respect to the declared positive or negative statements. In this paper we elaborate on the properties of the algebraic operators and we describe application and methodological issues.

Epistemic foundation of stable model semantics

Stable model semantics has become a very popular approach for the management of negation in logic programming. This approach relies mainly on the closed world assumption to complete the available knowledge and its formulation has its basis in the so-called Gelfond–Lifschitz transformation. The primary goal of this work is to present an alternative and epistemic-based characterization of stable model semantics, to the Gelfond-Lifschitz transformation. In particular, we show that stable model semantics can be defined entirely as an extension of the Kripke-Kleene semantics. Indeed, we show that the closed world assumption can be seen as an additional source of ‘falsehood’ to be added cumulatively to the Kripke-Kleene semantics. Our approach is purely algebraic and can abstract from the particular formalism of choice as it is based on monotone operators (under the knowledge order) over bilattices only.

The problem of missing data in geoscience databases

SQL is the (more or less) standardised language that is used by the majority of commercial database management systems. However, it is seriously flawed, as has been documented in detail by Date, Darwen, Pascal, and others. One of the most serious problems with SQL is the way it handles missing data. It uses a special value ‘NULL’ to represent data items whose value is not known. This can have a variety of meanings in different circumstances (such as ‘inapplicable’ or ‘unknown’). The SQL language also allows an ‘unknown’ truth value in logical expressions. The resulting incomplete three-valued logic leads to inconsistencies in data handling within relational database management systems. Relational database theorists advocate that a strict two-valued logic (true/false) be used instead, with prohibition of the use of NULL, and justify this stance by assertion that it is a true representation of the ‘real world’. Nevertheless, in real geoscience data there is a complete gradation between exact values and missing data: for example, geochemical analyses are inexact (and the uncertainty should be recorded); the precision of numeric or textual data may also be expressed qualitatively by terms such as ‘approximately’ or ‘possibly’. Furthermore, some data are by their nature incomplete: for example, where samples could not be collected or measurements could not be taken because of inaccessibility. It is proposed in this paper that the best way to handle such data sets is to replace the closed-world assumption and its concomitant strict two-valued logic, upon which the present relational database model is based, by the open-world assumption which allows for other logical values in addition to the extremes of ‘true’ and ‘false’. Possible frameworks for such a system are explored, and could use Codd's ‘marks’, Darwen's approach (recording the status of information known about each data item), or other approaches such as fuzzy logic.

Any-world assumptions in logic programming

Due to the usual incompleteness of information representation, any approach to assign a semantics to logic programs has to rely on a default assumption on the missing information. The stable model semantics, that has become the dominating approach to give semantics to logic programs, relies on the Closed World Assumption (CWA), which asserts that by default the truth of an atom is false. There is a second well-known assumption, called Open World Assumption (OWA), which asserts that the truth of the atoms is supposed to be unknown by default. However, the CWA, the OWA and the combination of them are extremal, though important, assumptions over a large variety of possible assumptions on the truth of the atoms, whenever the truth is taken from an arbitrary truth space. The topic of this paper is to allow any assignment (i.e. interpretation), over a truth space, to be a default assumption. Our main result is that our extension is conservative in the sense that under the “everywhere false” default assumption (CWA) the usual stable model semantics is captured. Due to the generality and the purely algebraic nature of our approach, it abstracts from the particular formalism of choice and the results may be applied in other contexts as well.