With the proliferation of Web services, scientific applications are more and more designed as temporal compositions of services, commonly referred to as workflows. To address this paradigm shift, different workflow ma...
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With the proliferation of Web services, scientific applications are more and more designed as temporal compositions of services, commonly referred to as workflows. To address this paradigm shift, different workflow management systems have been proposed. While their efficiency has been established over centralized static systems, it is questionable over decentralized failure-prone platforms. Scientific applications recently started to be deployed over large distributed computing platforms, leading to new issues, like elasticity, i.e., the possibility to dynamically refine, at runtime, the amount of resources dedicated to an application. This raised again the demand for new programming models, able to express autonomic self-coordination of services in a dynamic platform. Nature-inspired, rule-based computing models recently gained a lot of attention in this context. They are able to naturally express parallelism, distribution, and autonomic adaptation. While their high expressiveness and adequacy for this context has been established, such models severely suffer from a lack of proof of concepts. In this paper, we concretely show how to leverage such models in this context. We focus on the design, the implementation and the experimental validation of a chemistry-inspired scientific workflow management system. (C) 2013 Elsevier B.V. All rights reserved.
This paper presents a rule-based algorithm for performing order-sorted E-unification using an unsorted E-unification decision procedure under assumptions about E that are commonly satisfied in practice. We have implem...
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This paper presents a rule-based algorithm for performing order-sorted E-unification using an unsorted E-unification decision procedure under assumptions about E that are commonly satisfied in practice. We have implemented this algorithm in Maude for use with the Maude-NRL protocol analyzer and have used CiME for unsorted E-unification for E any set of AC and ACU axioms. In many examples of interest, using order-sorted unification over unsorted unification is able to reduce the total number of unifiers considered, and dramatically improve the performance of the Maude-NRL tool.
This paper is an introduction to rule-based programming in Maude. We illustrate in particular the use of operator attributes to structure the state of a system, and the difference between equations and rules. We use w...
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This paper is an introduction to rule-based programming in Maude. We illustrate in particular the use of operator attributes to structure the state of a system, and the difference between equations and rules. We use well-known mathematical games and puzzles for our examples illustrating the expressive power of Maude.
We work through a sequence of evolution scenarios for language-based functionality implemented as rule-based programs. We identify and illustrate different dimensions along which such functionality can evolve, includi...
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We work through a sequence of evolution scenarios for language-based functionality implemented as rule-based programs. We identify and illustrate different dimensions along which such functionality can evolve, including the following: (i) coding style;(ii) coding details;(iii) data model;(iv) crosscutting concerns;and (v) patches. We focus at language interpreters as examples of language-based functionality, but similar scenarios exist for type checkers, static analyses, program transformations, and other sorts of language-based functionality. We opt for Prolog as the rule-based programming language used for the implementation of language-based functionality. We employ the Prolog-basedrule Evolution Kit (REK) for the operationalisation of the evolution scenarios by means of evolutionary transformations. We compile a list of exercises that are meant to help with the digestion of the scenarios and with the further exploration of the overall subject.
A general approach to implement propagation and simplification of constraints consists of applying rules over these constraints. However, a difficulty that arises frequently when writing a constraint solver is to dete...
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A general approach to implement propagation and simplification of constraints consists of applying rules over these constraints. However, a difficulty that arises frequently when writing a constraint solver is to determine the constraint propagation algorithm. In previous work, different methods for automatic generation of rule-based solvers for constraints defined over finite domains have been proposed 1,2,3,4 . In this paper, we present a method for generating rule-based solvers for constraint predicates defined by means of a constraint logic program, even when the constraint domain is infinite.
In this paper, we are interested in the runtime complexity of programs based on multiset rewriting. The motivation behind this work is the study of the complexity of chemistry inspired programming models, which recent...
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In this paper, we are interested in the runtime complexity of programs based on multiset rewriting. The motivation behind this work is the study of the complexity of chemistry inspired programming models, which recently regained momentum due to their adequacy to large autonomous systems. In these models, data are most of the time left unstructured in a container, formally, a multiset. The program to be applied to this multiset is specified as a set of conditioned rules rewriting the multiset. At run time, these rewrite operations are applied concurrently, until no rule can be applied anymore (the set of elements they need cannot be found in the multiset anymore). A limitation of these models stand in their complexity: each computation step may require a complexity in O(n(k)) where n denotes the number of elements in the multiset, and k is the size of the subset of elements method to trigger a given rule. By analogy with chemistry, such elements can be called reactants. In this paper, we explore the possibility of improving the complexity of searching reactants through a static analysis of the rules' condition. In particular, we give a characterisation of this complexity, by analogy to the subgraph isomorphism problem. Given a rule R, we define its rank rk(R) and its calibre C(R), allowing us to exhibit an algorithm with a complexity in O(n(rk)(R)+C(R)) for searching reactants, while showing that rk(R) + C(R) <= k and that rk(R) + C(R) < k most of the time.
In natural situations, movements are often directed toward locations different from that of the evoking sensory stimulus. Movement goals must then be inferred from the sensory cue based on rules. When there is uncerta...
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In natural situations, movements are often directed toward locations different from that of the evoking sensory stimulus. Movement goals must then be inferred from the sensory cue based on rules. When there is uncertainty about the rule that applies for a given cue, planning a movement involves both 'Choosing the relevant rule and computing the movement goal based on that rule. Under these conditions, it is not clear whether primates compute multiple movement goals based on all possible rules before choosing an action, or whether they first choose a rule and then only represent the movement goal associated with that rule. Supporting the former hypothesis, we show that neurons in the frontoparietal reach areas of monkeys simultaneously represent two different rule-based movement goals, which are biased by the monkeys' choice preferences. Apparently, primates choose between multiple behavioral options by weighing against each other the movement goals associated with each option.
rules represent a simplified means of programming, congruent with our understanding of human brain constructs. With the advent of business rules management systems, it has been possible to introduce rule-based program...
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ISBN:
(数字)9783642400377
ISBN:
(纸本)9783642400377;9783642400384
rules represent a simplified means of programming, congruent with our understanding of human brain constructs. With the advent of business rules management systems, it has been possible to introduce rule-based programming to nonprogrammers, allowing them to map expert intent into code in applications such as fraud detection, financial transactions, healthcare, retail, and marketing. However, a remaining concern is the quality, safety, and reliability of the resulting programs. This book is on business rules programs, that is, rule programs as handled in business rules management systems. Its conceptual contribution is to present the foundation for treating business rules as a topic of scientific investigation in semantics and program verification, while its technical contribution is to present an approach to the formal verification of business rules programs. The author proposes a method for proving correctness properties for a business rules program in a compositional way, meaning that the proof of a correctness property for a program is built up from correctness properties for the individual rulesthus bridging a gap between the intuitive understanding of rules and the formal semantics of rule programs. With this approach the author enables rule authors and tool developers to understand, express formally, and prove properties of the execution behavior of business rules programs. This work will be of interest to practitioners and researchers in the areas ofprogram verification,enterprise computing, database management, and artificial intelligence.
Since a rule-based program[1][2] is composed of a set of rules[3], it is easy to improve the whole program by speeding up each rule in the program. We propose a technology to measure execution time of each rule, in or...
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Since a rule-based program[1][2] is composed of a set of rules[3], it is easy to improve the whole program by speeding up each rule in the program. We propose a technology to measure execution time of each rule, in order to analyze the interrelation of rules more clearly, and improve the efficiency of rule-based programs by several methods. Our proposal also includes the technology to measure the execution time of failed applicability checking of rules[4], since in a complicated rule-based program, failed applicability checking of rules may consume plenty of execution time. Among all the rule-based languages, we choose Equivalent Transformation (ET) language[5], which can ensure the correctness of the whole program based on the correctness of ET rules in it.
The modeling language ML-rules allows specifying and simulating complex systems biology models at multiple levels of organization. The development of such simulation models involves a wide variety of simulation experi...
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The modeling language ML-rules allows specifying and simulating complex systems biology models at multiple levels of organization. The development of such simulation models involves a wide variety of simulation experiments and the replicability of generated simulation results requires suitable means for documenting simulation experiments. Embedded domain-specific languages, such as SESSL, cater to both requirements. With SESSL, the user can integrate diverse simulation experimentation methods and third-party software components into an executable, readable simulation experiment specification. A newly developed SESSL binding for ML-rules exploits these features of SESSL, opening up new possibilities for executing and documenting simulation experiments with ML-rules models.
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