Affiliation:
1. Towson University
2. Iowa State University and Jet Propulsion Laboratory/Caltech
Abstract
Agent-oriented software engineering (AOSE) has provided powerful and natural, high-level abstractions in which software developers can understand, model and develop complex, distributed systems. Yet, the realization of AOSE partially depends on whether agent-based software systems can achieve reductions in development time and cost similar to other reuse-conscious development methods. Specifically, AOSE does not adequately address requirements specifications as reusable assets. Software product line engineering is a reuse technology that supports the systematic development of a set of similar software systems through understanding, controlling, and managing their common, core characteristics and their differing variation points. In this article, we present an extension to the Gaia AOSE methodology, named Gaia-PL (Gaia-Product Line), for agent-based distributed software systems that enables requirements specifications to be easily reused. We show how our methodology uses a product line perspective to promote reuse in agent-based software systems early in the development life cycle so that software assets can be reused throughout system development and evolution. We also present results from an application to show how Gaia-PL provided reuse that reduced the design and development effort for a large, multiagent system.
Funder
National Science Foundation
Publisher
Association for Computing Machinery (ACM)
Cited by
9 articles.
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1. An Automated Approach to Manage MAS-Product Line Methods;Engineering Multi-Agent Systems;2018
2. Towards a MAS Product Line Engineering Approach;Engineering Multi-Agent Systems;2018
3. Designing a Framework for Smart IoT Adaptations;Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering;2017-10-20
4. Using SPL to Develop AAL Systems Based on Self-adaptive Agents;Advances in Intelligent Systems and Computing;2016
5. Using Models at Runtime to Adapt Self-managed Agents for the IoT;Multiagent System Technologies;2016