aose methodologies

Table of Contents


There has been a surge of interest in agent-oriented software engineering in recent years. Numerous methodologies for developing agent-based systems have been proposed in the literature and the area of agent-oriented methodologies is maturing rapidly. Evaluating methodologies’ strengths, weaknesses, and domains of applicability play an important role in improving them and in developing the “next-generation” of methodologies. In this paper, we present a reliable framework that adopts statistical techniques to compare agent-oriented methodologies. Based upon this framework we performed a comparison of four AOSE methodologies MaSE, Prometheus, Tropos, and Gaia.


Agent-oriented techniques represent an exciting new means of analyzing, designing, and building complex software systems. They have the potential to significantly improve current practice in software engineering and to extend the range of applications that can feasibly be tackled. “One of the most fundamental obstacles to large scale take-up of agent technology is the lack of mature software development methodologies for agent-based systems.” (Luck, McBurney & Preist, 2003, p.11). Even though AOSE methodologies have been proposed, few are mature or described in sufficient detail to be of real use. The area of agent-oriented methodologies is maturing rapidly and that the time has come to begin drawing together the work of various research groups to develop the next generation of agent-oriented software engineering methodologies (Castro, Kolp & Mylopoulos, 2002; Bresciani et al. n.d.). An important step is to understand the differences between the various key methodologies and to understand each methodology’s strengths, weaknesses, and domains of applicability. In this paper, we perform a comparison of several well-known methodologies. A qualified
The methodology has been selected based on the availability of the documentation that describes it, the familiarity of the agent community with it, and its domain of applicability. As a result, the following 9 methodologies have been selected as treatments for our experiment: Gaia, MaSE, Prometheus, Tropos, MAS-CommonKADS, MESSAGE, FIPA-OS, JiVE and CNFM (Elamy and Far, 2005). In this paper, we perform a comparison on four well-known AOSE methodologies MaSE, Prometheus, Tropos, and Gaia. In section 2, we briefly introduce these methodologies. Section 3, we describe a framework for comparing AOSE methodologies. We then (section 5) select the Appropriate Statistical Model techniques to compare AOSE methodologies. In section 6 we apply the framework to compare the methodologies.

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FULL Paper PDF file:


Parandoosh F. and Kaviani S. (2007).
In Proceedings of the Second International Conference on Evaluation of Novel Approaches to Software Engineering, pages 56-65
DOI: 10.5220/0002585200560065
Copyright c SciTePress

We would like to thank Dr.Faraahi, for his valuable
Comments on a draft of this paper.

PDF reference  and original file: Click here

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Professor Siavosh Kaviani was born in 1961 in Tehran. He had a professorship. He holds a Ph.D. in Software Engineering from the QL University of Software Development Methodology and an honorary Ph.D. from the University of Chelsea.