基于元数据的声明型事务框架的设计

阐明了传统EJB声明型事务存在的缺陷,并对AOP分离横切关注的思想及其实现方法进行了深入分析,最后运用AOP并结合IOC模式与动态代理的使用,搭建了一个基于元数据的声明型事务框架.     

Analyzing CAD competence with univariate and multivariate learning curve models

Understanding how learning occurs, and what improves or impedes the learning process is of importance to academicians and practitioners; however, empirical research on validating learning curves is sparse. This paper contributes to this line of research by collecting and analyzing CAD (computer-aided design) procedural and cognitive performance data for novice trainees during 16-weeks of training. The declarative performance is measured by time, and the procedural performance by the number of features used to construct a design part. These data were analyzed using declarative or procedural performance separately as predictors (univariate), or a combination of declarative or procedural predictors (multivariate). Furthermore, a method to separate the declarative and procedural components from learning curve data is suggested.     

Evaluating ASP and Commercial Solvers on the CSPLib

This paper deals with four solvers for combinatorial problems: the commercial state-of-the-art solver ILOG oplstudio, and the research answer set programming (ASP) systems dlv, smodels and cmodels. The first goal of this research is to evaluate the relative performance of such systems when used in a purely declarative way, using a reproducible and extensible experimental methodology. In particular, we consider a third-party problem library, i.e., the CSPLib, and uniform rules for modelling and instance selection. The second goal is to analyze the marginal effects of popular reformulation techniques on the various solving technologies. In particular, we consider structural symmetry breaking, the adoption of global constraints, and the addition of auxiliary predicates. Finally, we evaluate, on a subset of the problems, the impact of numbers and arithmetic constraints on the different solving technologies. Results show that there is not a single solver winning on all problems, and that reformulation is almost always beneficial: symmetry-breaking may be a good choice, but its complexity has to be carefully chosen, by taking into account also the particular solver used. Global constraints often, but not always, help opl, and the addition of auxiliary predicates is usually worth, especially when dealing with ASP solvers. Moreover, interesting synergies among the various modelling techniques exist.     

Rapidly finding CAD features using database optimization

Automatic feature recognition aids downstream processes such as engineering analysis and manufacturing planning. Not all features can be defined in advance; a declarative approach allows engineers to specify new features without having to design algorithms to find them. Naive translation of declarations leads to executable algorithms with high time complexity. Database queries are also expressed declaratively; there is a large literature on optimizing query plans for efficient execution of database queries. Our earlier work investigated applying such technology to feature recognition, using a testbed interfacing a database system (SQLite) to a CAD modeler (CADfix). Feature declarations were translated into SQL queries which are then executed.The current paper extends this approach, using the PostgreSQL database, and provides several new insights: (i) query optimization works quite differently in these two databases, (ii) with care, an approach to query translation can be devised that works well for both databases, and (iii) when finding various simple common features, linear time performance can be achieved with respect to model size, with acceptable times for real industrial models. Further results also show how (i) lazy evaluation can be used to reduce the work performed by the CAD modeler, and (ii) estimating the time taken to compute various geometric operations can further improve the query plan. Experimental results are presented to validate our main conclusions.     

Positive Dedalus programs tolerate non-causality

Declarative networking is a recent approach to programming distributed applications with languages inspired by Datalog. A recent conjecture posits that the delivery of messages should respect causality if and only if they are used in non-monotone derivations. We present our results about this conjecture in the context of Dedalus, a Datalog-variant for distributed programming. We show that both directions of the conjecture fail under a strong semantical interpretation. But on a more syntactical level, we show that positive Dedalus programs can tolerate non-causal messages, in the sense that they compute the correct answer even when messages can be sent into the past.     

Declarative planning in procedural agent architectures

Practical agent languages and their corresponding architectures have often relied on a static plan library with more or less direct trigger-response activation mechanisms as a source for agent behaviours for the sake of runtime efficiency. Although efficient, such a language design choice severely limits an agent’s ability to reason about its goals and adapt to unforeseen circumstances after being deployed. This effectively delegates the task of planning to the designers themselves, who must design plan libraries able to cope with every foreseeable situation an agent might find itself in by designing plans to deal with any contingency. In this paper we develop a formal conversion process from traditional BDI agent languages into declarative planning. Using this conversion process, we show how to integrate domain independent planning algorithms into the BDI interpreter, allowing a designer to program an agent not only through the trigger-response mechanism used in traditional languages, but also in terms of declarative goals. Our contribution here is twofold: firstly we increase an agent’s ability to cope with unforeseen situations and secondly we unburden an agent designer from having to define multiple plan combinations that could be easily generated by a planner.     

A declarative approach for first-order built-in's of Prolog

We provide here a framework for studying Prolog programs with various built-in's that include arithmetic operations, and such metalogical relations likevar andground. To this end we propose a new, declarative semantics and prove completeness of the Prolog computation mechanism w.r.t. this semantics. We also show that this semantics is fully abstract in an appropriate sense. Finally, we provide a method for proving termination of Prolog programs with built-in's which uses this semantics. The method is shown to be modular and is illustrated by proving termination of a number of programs including the unify program of Sterling and Shapiro [17].     

Variability in business processes: Automatically obtaining a generic specification

The existence of different process variants is inevitable in many modern organizations. However, variability in business process support has proven to be a challenge as it requires a flexible business process specification that supports the required process variants, while at the same time being compliant with policies and regulations. Declarative approaches could support variability, by providing rules constraining process behavior and thereby allowing different variants. However, manual specification of these rules is complicated and error-prone. As such, tools are required to ensure that duplication and overlap of rules is avoided as much as possible, while retaining maintainability. In this paper, we present an approach to represent different process variants in a single compound prime event structure, and provide a method to subsequently derive variability rules from this compound prime event structure. The approach is evaluated by conducting an exploratory evaluation on different sets of real-life business process variants, including a real-life case from the Dutch eGovernment, to demonstrate the effectiveness and applicability of the approach.     

Declarative hybrid routing protocols in Ad hoc NETworks

This paper presents adaptive hybrid protocols based on the declarative network and mainly discusses the principle and realization of the Bayesian-estimation based adaptive hybrid protocol in the declarative network, which is well adapted to the Mobile Ad hoc NETwork (MANET). The adaptive hybrid protocol is designed for ad hoc networks which have characteristics like self-organizing, no trusted party, flexibility, etc. The nodes that run the hybrid protocol can automatically select one routing protocol that is suitable for different network environment. The Bayesian-estimation based adaptive strategy, that improves the adaptability and stability of the protocol, succeeds in the Rapidnet, a declarative network engine. The result in the Rapidnet proves that the hybrid protocol and the adaptive strategy are feasible. The experiment on the ns-3 simulator, an emerging discrete-event network simulator, validates that this protocol performs well and reduces communication overheads.