Doktorarbeit / Dissertation, 2011
199 Seiten
1. Introduction
1.2 Hypotheses
1.3 Objectives
1.4 Contributions
1.5 Thesis Outline
2. Literature Survey on Traceability
2.1 Traceability Reference Models and Meta-Models
2.2 Traceability Approaches to Capture Trace Relations
2.2.1 Formal Approaches
2.2.2 Process Oriented Approaches
2.2.3 Information Retrieval Approaches
2.2.4 String Matching Approaches
2.2.5 Rule Based Approaches
2.2.6 Run-time approaches
2.2.7 Hypermedia and Information Integration approaches
2.3 Representation, Recording and Maintenance of Traceability Relations
2.4 Visualisation of Traceability Relations
2.5 Use of Traceability Relations
2.6 Traceability Approaches for Multi-Agent Systems
2.7 Performance Measures
2.8 Implication of tools that infer trace relations
2.9 Summary
3. Traceability Reference Model
3.1 Overview of the Reference Model
3.2 Multi-agent Oriented Artefacts
3.2.1 i* Framework
3.2.2 Prometheus
3.2.3 JACK
3.3 Traceability Relations
3.3.1 Traceability Relations between i* and Prometheus
3.2.2 Traceability Relations between Prometheus and JACK
3.4 Summary
4. Traceability Framework
4.1. Overview of the Framework
4.2 Traceability and Completeness Checking Rules
Type 1:
Type 2:
Type 3:
4.3 Extended Functions
4.3.1 Completeness checking functions
4.3.2 XQuery functions
4.3.3 XQueryJACKFunctions
4.3.4 XQueryPDTFunctions
4.3.5 XQuerySimilarityFunctions
4.3.6 XQuerySynonymsFunctions
4.3.7 XQueryTAOMFunctions
4.4 Retratos Tool
4.5 Discussion
4.6 Summary
5. Evaluation and Results
5.1 Criteria for Evaluation
5.2 Automatic Teller Machine
5.2.1 Overview of the Case Study
5.2.2 Artefacts
5.2.3 Evaluation
5.3 Air Traffic Control Environment
5.3.1 Overview of the Case Study
5.3.2 Artefacts
5.3.3 Evaluation
5.4 Electronic Bookstore
5.4.1 Overview of the Case Study
5.4.2 Artefacts
5.4.3 Evaluation
5.5 Discussion
5.6 Threats of Validity
5.7 Summary
6. Conclusion and Future Works
6.1 Overall Conclusions
6.2 Hypotheses
6.3 Objectives
6.4 Contributions
6.5 Future Work
6.5 Final Remarks
Bibliography
The primary research objective is to develop a comprehensive traceability framework for multi-agent systems. This involves enabling automatic generation of traceability relations and facilitating completeness checking to address heterogeneity and potential inconsistencies within models across the entire software development lifecycle (specifically using i* framework, Prometheus methodology, and JACK language).
Chapter 1 - Introduction
A multi-agent system consists of a system composed of several agents that are situated in an environment and that interact with each other and with their environment. Multi-agent systems have been proposed as a solution to implement complex systems that need to run in an environment that is open, distributed and highly interactive. An agent is defined by Wooldridge in (Wooldridge, et al., 1995), (Wooldridge, 2002) as a software component that is “situated in some environment and that is capable of autonomous action in this environment in order to meet its design objectives”. Several types of software components fulfil this definition varying from daemons process in UNIX (Frisch, 2002) to complex decision making systems that control unmanned autonomous vehicles (Agent Oriented Software Limited, 2010).
An intelligent agent is an autonomous software component that is categorised to be pro-active, reactive, and social (Wooldridge, 2002). Pro-activeness means that the agent takes initiative in order to achieve its goals. Reactivity means that the agent perceives its environment and responds to its stimulus according to its goals. Social ability means that the agent will be able to communicate with other agents and have abilities such as co-operation, co-ordination, and negotiation.
Several architectures have been proposed to build multi-agent systems such as Jadex (Pokahr, et al., 2005), Jason (Bordini, et al., 2005), and JACK (Busetta, et al., 1999), (Howden, et al., 2001). Agent architectures can be classified in three categories: deliberative architectures, reactive architectures, hybrid architectures.
Chapter 1 - Introduction: Summarizes the concepts of multi-agent systems and BDI architecture, highlighting the challenges of traceability in such systems.
Chapter 2 - Literature Survey on Traceability: Provides an overview of existing traceability approaches, challenges, and classification of traceability models in software engineering.
Chapter 3 - Traceability Reference Model: Introduces the core reference model for artefacts in i* framework, Prometheus methodology, and JACK, including the classification of traceability relations.
Chapter 4 - Traceability Framework: Details the rule-based approach using XQuery, the prototype tool Retratos, and the implementation of completeness checking functions.
Chapter 5 - Evaluation and Results: Presents the evaluation of the framework through three distinct case studies: Automatic Teller Machine, Air Traffic Control Environment, and Electronic Bookstore.
Chapter 6 - Conclusion and Future Works: Summarizes the research findings, addresses how objectives were met, and suggests future improvements to the framework.
Multi-agent systems, BDI architecture, Software Traceability, Traceability Reference Model, Rule-based Framework, Completeness Checking, XQuery, Prometheus Methodology, i* framework, JACK language, Traceability Relations, Automated Traceability, Software Engineering, Model Driven Development, Impact Analysis.
The work focuses on software traceability for multi-agent systems (MAS) that are implemented using the Belief-Desire-Intention (BDI) architecture.
The thesis addresses the complexity, heterogeneity of documentation, lack of full lifecycle support in existing agent-oriented methodologies, and potential incompleteness of models in MAS development.
The main goal is to support the automatic generation of traceability relations and to perform completeness checking on software models throughout the development lifecycle.
The research integrates the i* framework for early requirements, the Prometheus methodology for analysis and design, and the JACK language for implementation, using XML and an extended version of XQuery to define rules.
The framework is validated using three distinct case studies: a small ATM system, a medium-sized Air Traffic Control Environment, and a large-sized Electronic Bookstore application.
Retratos is a prototype tool developed to execute the defined rules, automatically generate traceability relations, identify missing elements, and produce HTML reports of the findings.
The author argues that standard techniques do not sufficiently capture the specific semantics and structural dependencies between different agent-oriented design and implementation artefacts.
This attribute is used within traceability relations to provide a measure of confidence or the level to which the defined rules for a relation have been satisfied.
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