A Rationale-based Model for Architecture Design Reasoning

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4.1. Software engineering research methods employing such an approach would select methodologies and technologies which initially appear to be suitable for their environment, and continuously improve and fine tune them to improve their software engineering practices. Although this approach is scientific in its own way, most often than not the knowledge or insights gained would remain within the organisation and the results are not reported. When new ideas are created, the arguments for their early stage development are usually supported by persuasion [138]. Examples of such models include [46, 119]. As time passes, continuous refinement and improvement will prove or disprove their validity. The following sub-sections describe some software engineering research methods. Based on these research methods, the appropriate validation techniques are selected for this research. 4.1 Software engineering research methods Software engineering is still a maturing discipline. Therefore, it is not surprising that many researchers are still debating on how software engineering research should be conducted (e.g. [41, 166, 125, 172]). As reported by Adrion in [167] and by Glass in [49], software engineering research problems have different characteristics and thus different research methods are employed accordingly: • Scientific Method - Scientists develop a theory to explain an observed phenomenon. They propose a model or a theory of behaviour, and validate the hypotheses of the model or theory through experimentation. • Engineering Method - Engineers observe existing solutions and propose new improvements. They measure or analyse the improvements until no further improvements are possible. • Empirical Method - Researchers observe a phenomenon and put forward some hypotheses. They then collect data to test the model using statistical methods or case studies. These data and their analysis are used to support or refute a hypothesis. • Analytical Method - Researchers propose a formal theory or a set of axioms, then derive results from the theory and if possible compare the results with empirical observations. Part of the problem with software engineering research methodology is that the boundaries of the field is not clearly defined. As a result, methodological conflicts arise when 47
4.1. Software engineering research methods there is a cross boundary situation. For instance, a situation where engineering and management issues are to be considered together, then what research method should be used? Additionally, the maturation of software technology over time [138] adds another dimension to software engineering research. Different kinds of problems require different research paradigms. Different research settings also post different research questions. Hence, the methods and techniques used would vary accordingly. A summary of these research settings are listed: • Feasibility - Is there a X, and what is it? Is it possible to accomplish X at all? • Characterisation - What are the characteristics of X? What do we mean by X? What are the varieties of X and how are they related? • Methods/Means - How to accomplish X? What is a better way to accomplish X? How can I automate doing X? • Generalisation - Is X always true of Y? Given X, what will Y be? • Selection - How do I decide between X and Y? Given different research settings, the answers that are sought would be quite different in nature. The techniques that are required to validate those answers would also vary [138]. A summary of these techniques are listed below: • Persuasion - use arguments to support the ideas that have been put forward by going through an example. • Implementation - use a prototype or a case study to demonstrate the idea. • Evaluation - compare different objects of research using a check-list of criteria. The comparison of measurements forms the basis of the evaluation. This approach can use expert-opinion an a basis for evaluation. • Analysis - analyse the facts and the consequences through derivation and proof of a formal model, or use empirical methods such as statistical methods to carry out analysis in a controlled situation. • Experience - a subjective evaluation based on personal experience and observations about the use of the result in actual practice. Since case study research are often validated using anecdotal evidence which can be subjective, careful justifications of the evidence would be necessary. Yin described six 48
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A Rationale-based Model for Archite
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maintenance. These techniques can h
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Declaration This thesis contains no
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2.2.6 DoD Architecture Framework .
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5.4.6 Risk assessment in architectu
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8.2 The architecture rationalisatio
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12.2 Contributions . . . . . . . .
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Page 17 and 18: 11.13A Process to Synchronise Chang
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Page 23 and 24: 1.2. Research motivations and resea
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Page 27 and 28: 1.4. Structure of the thesis the ch
Page 29 and 30: Part I Problem Analysis 10
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Page 73 and 74: on a regular basis. Their inputs ha
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Page 89 and 90: 5.3. Survey findings We used Spearm
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Page 99 and 100: Part III The Representation and App
Page 101 and 102: 6.1. A conceptual model for design
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Page 107 and 108: 6.3. Architecture elements Figure 6
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Page 113 and 114: 6.4. Architecture rationale depicts
Page 115 and 116: 6.5. The extended AREL To prevent c
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6.6. A UML representation of AREL a
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6.6. A UML representation of AREL a
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6.7. AREL usability AE by ≪AEsupe
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6.8. Summary The AREL model is exte
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7.1. The EFT system reasoning, a co
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7.1. The EFT system The processing
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7.1. The EFT system not chosen beca
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7.1. The EFT system Figure 7.5: Int
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7.1. The EFT system sequence checki
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7.1. The EFT system Figure 7.7: Dec
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7.1. The EFT system Therefore, in a
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7.1. The EFT system Figure 7.10: De
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7.2. An empirical study to validate
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7.3. Summary The case study is spec
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8.1. Background Based on these assu
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8.2. The architecture rationalisati
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8.3. Other applications of ARM As d
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8.3. Other applications of ARM Figu
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8.3. Other applications of ARM area
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Chapter 9 Architecture rationale an
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9.1. Background 9.1 Background In t
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9.2. Traceability of architecture r
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9.4. AREL and eAREL traceability ap
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Chapter 10 Architecture decision de
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10.1. Background 10.1.2 Introductio
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10.2. Building a BBN to represent a
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10.3. Reasoning about change impact
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10.5. Summary design object may cau
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11.1. Capturing architecture design
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11.1. Capturing architecture design
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11.2. Checking AREL models Figure 1
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11.3. Tracing AREL models Figure 11
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11.4. Analysing AREL with BBN • S
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11.5. Limitations Figure 11.13: A P
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Chapter 12 Conclusions 12.1 Summary
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12.2. Contributions reasoning metho
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12.2. Contributions implementations
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12.3. Future work architecture deci
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12.3. Future work to examine the co
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BIBLIOGRAPHY [10] B. W. Boehm, Soft
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BIBLIOGRAPHY [37] A. Eden and R. Ka
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BIBLIOGRAPHY [62] J. D. Herbsleb an
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BIBLIOGRAPHY [89] N. Lassing, D. Ri
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BIBLIOGRAPHY [115] D. L. Parnas,
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BIBLIOGRAPHY [142] Z. Simsek and J.
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BIBLIOGRAPHY [167] W. F. Tichy, N.
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Appendix A AREL Tool User Manual 1
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4.1 AREL Check Model When the Check
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4.2 AREL Model Tracing AREL model t
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Figure 9 - result of downward trace
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To initiate the graph’s creation,
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onto the diagram 14 Assign values t
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Useful Definitions The following ar
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) Some projects only c) Not at all
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19. I revisit architecture design d
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Complaint Procedure If you have any
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Privacy Protection Only investigato
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B. Exploring design reasoning. 1. W
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3. Why does the system use asynchro
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C. General Comments on AREL Modelli
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IEEE Computer Society Press. A. Tan
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