8,487 research outputs found
Automated Synthesis of Distributed Self-Stabilizing Protocols
In this paper, we introduce an SMT-based method that automatically
synthesizes a distributed self-stabilizing protocol from a given high-level
specification and network topology. Unlike existing approaches, where synthesis
algorithms require the explicit description of the set of legitimate states,
our technique only needs the temporal behavior of the protocol. We extend our
approach to synthesize ideal-stabilizing protocols, where every state is
legitimate. We also extend our technique to synthesize monotonic-stabilizing
protocols, where during recovery, each process can execute an most once one
action. Our proposed methods are fully implemented and we report successful
synthesis of well-known protocols such as Dijkstra's token ring, a
self-stabilizing version of Raymond's mutual exclusion algorithm,
ideal-stabilizing leader election and local mutual exclusion, as well as
monotonic-stabilizing maximal independent set and distributed Grundy coloring
A planning approach to the automated synthesis of template-based process models
The design-time specification of flexible processes can be time-consuming and error-prone, due to the high number of tasks involved and their context-dependent nature. Such processes frequently suffer from potential interference among their constituents, since resources are usually shared by the process participants and it is difficult to foresee all the potential tasks interactions in advance. Concurrent tasks may not be independent from each other (e.g., they could operate on the same data at the same time), resulting in incorrect outcomes. To tackle these issues, we propose an approach for the automated synthesis of a library of template-based process models that achieve goals in dynamic and partially specified environments. The approach is based on a declarative problem definition and partial-order planning algorithms for template generation. The resulting templates guarantee sound concurrency in the execution of their activities and are reusable in a variety of partially specified contextual environments. As running example, a disaster response scenario is given. The approach is backed by a formal model and has been tested in experiment
Abstract Learning Frameworks for Synthesis
We develop abstract learning frameworks (ALFs) for synthesis that embody the
principles of CEGIS (counter-example based inductive synthesis) strategies that
have become widely applicable in recent years. Our framework defines a general
abstract framework of iterative learning, based on a hypothesis space that
captures the synthesized objects, a sample space that forms the space on which
induction is performed, and a concept space that abstractly defines the
semantics of the learning process. We show that a variety of synthesis
algorithms in current literature can be embedded in this general framework.
While studying these embeddings, we also generalize some of the synthesis
problems these instances are of, resulting in new ways of looking at synthesis
problems using learning. We also investigate convergence issues for the general
framework, and exhibit three recipes for convergence in finite time. The first
two recipes generalize current techniques for convergence used by existing
synthesis engines. The third technique is a more involved technique of which we
know of no existing instantiation, and we instantiate it to concrete synthesis
problems
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Enterprise application reuse: Semantic discovery of business grid services
Web services have emerged as a prominent paradigm for the development of distributed software systems as they provide the potential for software to be modularized in a way that functionality can be described, discovered and deployed in a platform independent manner over a network (e.g., intranets, extranets and the Internet). This paper examines an extension of this paradigm to encompass âGrid Servicesâ, which enables software capabilities to be recast with an operational focus and support a heterogeneous mix of business software and data, termed a Business Grid - "the grid of semantic services". The current industrial representation of services is predominantly syntactic however, lacking the fundamental semantic underpinnings required to fulfill the goals of any semantically-oriented Grid. Consequently, the use of semantic technology in support of business software heterogeneity is investigated as a likely tool to support a diverse and distributed software inventory and user. Service discovery architecture is therefore developed that is (a) distributed in form, (2) supports distributed service knowledge and (3) automatically extends service knowledge (as greater descriptive precision is inferred from the operating application system). This discovery engine is used to execute several real-word scenarios in order to develop and test a framework for engineering such grid service knowledge. The examples presented comprise software components taken from a group of Investment Banking systems. Resulting from the research is a framework for engineering servic
Synthesizing and executing plans in Knowledge and Action Bases
We study plan synthesis for a variant of Knowledge and Action Bases (KABs). KABs have been recently introduced as a rich, dynamic framework where states are full-fledged description logic (DL) knowledge bases (KBs) whose extensional part is manipulated by actions that can introduce new objects from an infinite domain. We show that, in general, plan existence over KABs is undecidable even under severe restrictions. We then focus on the class of state-bounded KABs, for which plan existence is decidable, and we provide sound and complete plan synthesis algorithms, through a novel combination of techniques based on standard planning, DL query answering, and finite-state abstractions. All results hold for any DL with decidable query answering. We finally show that for lightweight DLs, plan synthesis can be compiled into standard ADL planning. © 2016, CEUR-WS. All rights reserved
Verifying Web Applications: From Business Level Specifications to Automated Model-Based Testing
One of reasons preventing a wider uptake of model-based testing in the
industry is the difficulty which is encountered by developers when trying to
think in terms of properties rather than linear specifications. A disparity has
traditionally been perceived between the language spoken by customers who
specify the system and the language required to construct models of that
system. The dynamic nature of the specifications for commercial systems further
aggravates this problem in that models would need to be rechecked after every
specification change. In this paper, we propose an approach for converting
specifications written in the commonly-used quasi-natural language Gherkin into
models for use with a model-based testing tool. We have instantiated this
approach using QuickCheck and demonstrate its applicability via a case study on
the eHealth system, the national health portal for Maltese residents.Comment: In Proceedings MBT 2014, arXiv:1403.704
A Tool-Supported Approach for Concurrent Execution of Heterogeneous Models
International audienceIn the software and systems modeling community, research on domain-specific modeling languages (DSMLs) is focused on providing technologies for developing languages and tools that allow domain experts to develop system solutions efficiently. Unfortunately, the current lack of support for explicitly relating concepts expressed in different DSMLs makes it very difficult for software and system engineers to reason about information spread across models describing different system aspects [4]. As a particular challenge, we investigate in this paper relationships between, possibly heterogeneous, behavioral models to support their concurrent execution. This is achieved by following a modular executable metamodeling approach for behavioral semantics understanding, reuse, variability and composability [5]. This approach supports an explicit model of concurrency (MoCC) [6] and domain-specific actions (DSA) [10] with a well-defined protocol between them (incl., mapping, feedback and callback) reified through explicit domain-specific events (DSE) [12]. The protocol is then used to infer a relevant behavioral language interface for specifying coordination patterns to be applied on conforming executable models [17]. All the tooling of the approach is gathered in the GEMOC studio, and outlined in the next section. Currently, the approach is experienced on a systems engineering language provided by Thales, named Capella 7. The goal and current state of the case study are exposed in this paper. 7 Cf. https://www.polarsys.org/capella
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