IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Optimized and Distributed Variant Logic for Model-Driven Applications

Optimized and Distributed Variant Logic for Model-Driven Applications
View Sample PDF
Author(s): Jon Davis (Curtin University, Australia)and Elizabeth Chang (University of New South Wales, Australia & Australian Defence Force Academy, Australia)
Copyright: 2018
Pages: 50
Source title: Application Development and Design: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-5225-3422-8.ch044

Purchase

View Optimized and Distributed Variant Logic for Model-Driven Applications on the publisher's website for pricing and purchasing information.

Abstract

The customization of Enterprise Information Systems (EIS) is expensive throughout its lifecycle, especially across an enterprise-wide distributed application environment. The authors' ongoing development of a temporal meta-data framework for EIS applications seeks to minimize these issues with the application model supporting the capability for end users to define their own supplemental or alternate application logic as what they term Variant Logic (VL). VL can be applied to any existing model object, defined by any authorized user, through modeling rather than coding, then executed by any user as an alternative to the original application logic. VL is also preserved during automated application updates and can also interoperate directly between similar model-based execution instances within a distributed execution environment, readily sharing the alternate logic segments. The authors also present an enhanced pre-processing architecture that optimizes the execution of Logic Variants to the same execution order of single path model logic.

Related Content

Babita Srivastava. © 2024. 21 pages.
Sakuntala Rao, Shalini Chandra, Dhrupad Mathur. © 2024. 27 pages.
Satya Sekhar Venkata Gudimetla, Naveen Tirumalaraju. © 2024. 24 pages.
Neeta Baporikar. © 2024. 23 pages.
Shankar Subramanian Subramanian, Amritha Subhayan Krishnan, Arumugam Seetharaman. © 2024. 35 pages.
Charu Banga, Farhan Ujager. © 2024. 24 pages.
Munir Ahmad. © 2024. 27 pages.
Body Bottom