Architecture and design of adaptive object-models

Yoder, Joseph W.; Balaguer, Federico; Johnson, Ralph E.

doi:10.1145/583960.583966

Cited by 73 publications

(67 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…There is a direct relationship between this work and the so-called type object pattern [18,45]. The type object pattern is also known as the adaptive object pattern.…”

Section: The Type Object Patternmentioning

confidence: 99%

“…• Related to that, interpreted approaches tend to use their own data storage, for example, tables consisting of tuples for each property value, including minimally the property type and property value [18]. This is more inefficient with respect to storage space, since for generated types all single-valued property values can be stored in one tuple.…”

Section: Comparing Generative and Interpretive Approachesmentioning

confidence: 99%

See 1 more Smart Citation

Supporting fine-grained generative model-driven evolution

et al. 2010

View full text Add to dashboard Cite

In the standard generative Model-driven Architecture (MDA), adapting the models of an existing system requires re-generation and restarting of that system. This is due to a strong separation between the modeling environment and the runtime environment. Certain current approaches remove this separation, allowing a system to be changed smoothly when the model changes. These approaches are, however, based on interpretation of modeling information rather than on generation, as in MDA. This paper describes an architecture that supports fine-grained evolution combined with generative model-driven development. Fine-grained changes are applied in a generative model-driven way to a system that has itself been developed in this way. To achieve this, model changes must be propagated correctly toward impacted elements. The impact of a model change flows along three dimensions: implementation, data (instances), and modeled dependencies. These three dimensions are explicitly represented in an integrated modeling-runtime environment to enable traceability. This implies a fundamental rethinking of MDA.

show abstract

“…There is a direct relationship between this work and the so-called type object pattern [18,45]. The type object pattern is also known as the adaptive object pattern.…”

Section: The Type Object Patternmentioning

confidence: 99%

Section: Comparing Generative and Interpretive Approachesmentioning

confidence: 99%

Supporting fine-grained generative model-driven evolution

et al. 2010

View full text Add to dashboard Cite

show abstract

“…Likewise, the contributions of this work complement the ongoing research on Adaptive Object Model (AOM) espoused in [17] and [22], where a system with an AOM (also called a Dynamic Object Model) is stated to have an explicit object model that is stored in the database, and interpreted at runtime. Objects are generated dynamically from the AOM schema meta-data that represent data descriptions.…”

Section: Discussionmentioning

confidence: 70%

Managing Evolving Business Workflows through the Capture of Descriptive Information

Gaspard

Estrella

McClatchey

et al. 2003

Conceptual Modeling for Novel Application Domains

View full text Add to dashboard Cite

Abstract. Business systems these days need to be agile to address the needs of a changing world. In particular the discipline of Enterprise Application Integration requires business process management to be highly reconfigurable with the ability to support dynamic workflows, inter-application integration and process reconfiguration. Basing EAI systems on model-resident or on a so-called description-driven approach enables aspects of flexibility, distribution, system evolution and integration to be addressed in a domain-independent manner. Such a system called CRISTAL is described in this paper with particular emphasis on its application to EAI problem domains. A practical example of the CRISTAL technology in the domain of manufacturing systems, called Agilium, is described to demonstrate the principles of model-driven system evolution and integration. The approach is compared to other model-driven development approaches such as the Model-Driven Architecture of the OMG and so-called Adaptive Object Models. Background and Related WorksAs the global marketplace becomes increasingly complex and intricately connected, organizations are constantly pressured to re-organize, re-structure, diversify, consolidate and slim down to provide a winning competitive edge. With the advent of the Internet and e-commerce, the need for coexistence and interoperation with legacy systems and for reduced 'times-to-market', the demand for the timely delivery of flexible software has increased. Couple to this the increasing complexity of systems and the requirement for systems to evolve over potentially extended timescales and the importance of clearly defined, extensible models as the basis of rapid systems design becomes a pre-requisite to successful systems implementation.One of the main drivers in the object-oriented design of information systems is the need for the reuse of design artefacts or models in handling systems evolution. To be able to cope with system volatility, systems must have the capability of reuse and to adapt as and when necessary to changes in requirements. The philosophy that has been investigated in the research reported in this paper is based on the systematic capture of the description of systems elements covering multiple views of the system to be designed (including processes and workflows) using common techniques. Such a description-driven approach [1,2] involves identifying and abstracting the crucial elements (such as items, processes, lifecycles, goals, agents and outcomes) in the

show abstract

“…The Adaptive Object Model (AOM) is such an example. The AOM is described in [17] as a framework that models business units with metadata, which will be interpreted at runtime. This is achieved using the TypeObject, Property and Strategy patterns [18].…”

Section: The Adaptive Object Model (Aom)mentioning

confidence: 99%

Environment support for developing and configuring adaptive agents

Xiao

Greer

2009

MGS

View full text Add to dashboard Cite

Abstract. Adaptivity is very often an important goal for software systems. This paper reviews existing approaches to achieving adaptivity in object oriented systems, particularly those using design patterns, and concludes that there are further opportunities for improving adaptivity in agent systems. The approach described proposes that agents should be coupled with the environment, rules and laws about agent behaviour being externalised in a continuously re-configurable knowledge repository. Tools have been implemented to support the re-configuration. Once new requirements are specified by business experts via the tools, the system automatically adapts its behaviour in the environment, without additional effort from developers. This novel approach pulls together a knowledgebase, configuration tools, and business experts as an integral environment through which the MAS achieves re-configurability ranging from overall infrastructure to individual policy sets. This fosters cost effective software evolution because much of the effort resulting from changes to business strategies and collaborations can be shifted from developers to customers, code change not being required since the environment maintains the dynamics instead.

show abstract

Architecture and design of adaptive object-models

Cited by 73 publications

References 10 publications

Supporting fine-grained generative model-driven evolution

Supporting fine-grained generative model-driven evolution

Managing Evolving Business Workflows through the Capture of Descriptive Information

Environment support for developing and configuring adaptive agents

Contact Info

Product

Resources

About