A Rationale-based Model for Architecture Design Reasoning

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12.3. Future work umented, but the survey does not allow us to observe the actual capture process that practising architects go through. We plan to design and execute a large scale field study into the software design process. This study will consist of multiple case studies, as described by [174] and successfully demonstrated by [27]. Some of the techniques we plan to use include studying practitioners’ attitudes towards design rationale use and documentation. We will conduct in-depth interviews and examination of design specifications. We expect these experimental techniques will enable us to discover the answers to many questions regarding the behaviour of architects during design. Although we can show AREL’s explanatory and reasoning power to help understand an existing system with the empirical study, we cannot demonstrate AREL’s reasoning capabilities to support a new system’s development in this thesis. It is our intention to test this aspect of AREL in the future. In a new experiment, we will apply AREL to the architecture design process to assess its performance on the effectiveness of capture and its usefulness in supporting architecture design. The results will allow us to further refine AREL. The experts from the empirical study have reacted positively towards the AREL approach, but they have also questioned the cost-effectiveness of the method. A cost-benefit analysis on AREL’s applications would be necessary. Different perspectives could be taken in this analysis: (a) the cost and benefit of using AREL and ARM in different phases of the software development life-cycle; (b) the cost and benefit of applying each of the techniques such as traceability, risk analysis using QNR, and impact analysis using BBN; (c) the cost and benefit of applying these techniques to specific domains or different project scales. The AREL tool-set is only a proof-of-concept, its effectiveness in practice requires a formal evaluation. The tool-set itself also requires better integration between UML modelling and BBN computation. Design rationale capture using AREL and ARM relies very much on architects recording the information diligently. Any automated design rationale capture to enhance this process would be an improvement. Ideas such as language processing, white board capture tool can be expolored. In this thesis, we have provided a high-level classification of the architecture elements by viewpoints. This classification supports the scoping of traceability results. We think that further classifications are required because it will provide further scoping of the trace results when using the AREL traceability methods. The application of BBN to AREL has provided a foundation for change impact analysis. Some further research opportunities in architecture design and software engineering are possible: (a) to predict the cost of change impact to architecture enhancements; (b) 211
12.3. Future work to examine the complexity of the system through analysing the dependency between architecture elements and decisions; (c) to consider using Dynamic Bayesian Networks for temporal analysis as systems evolve over time; (d) to derive from AREL a more abstract and concise model that represents the associations between decisions. 212
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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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6.10 ≪AR≫ and ≪AAR≫ Stereot
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11.13A Process to Synchronise Chang
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5.13 Design Rationale Helps Evaluat
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that architecture design is highly
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1.2. Research motivations and resea
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1.2. Research motivations and resea
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1.4. Structure of the thesis the ch
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Part I Problem Analysis 10
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2.1. Industry practice of design ra
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2.2. Architecture frameworks and de
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Chapter 3 Related work in design ra
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3.2. Why do we need design rational
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3.2. Why do we need design rational
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3.3. Existing methods for capturing
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3.4. Other related studies 3.3.7 Qu
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3.4. Other related studies evolutio
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3.5. How well design rationale meth
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3.5. How well design rationale meth
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Chapter 4 Research methodology and
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4.1. Software engineering research
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4.2. The chosen research and valida
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Part II Architecture Design Rationa
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on a regular basis. Their inputs ha
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5.1. Architecture rationale in the
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5.2. Survey methodology data collec
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5.3. Survey findings experience). I
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5.3. Survey findings Table 5.1: Fre
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5.3. Survey findings Business Goals
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5.3. Survey findings 5.3.5 Document
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5.3. Survey findings Table 5.8 summ
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5.3. Survey findings We used Spearm
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5.3. Survey findings previous desig
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5.4. Discussion of findings Since t
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5.4. Discussion of findings or cons
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5.5. Limitations and use design rat
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Part III The Representation and App
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6.1. A conceptual model for design
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6.2. Architecture Rationale and Ele
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6.2. Architecture Rationale and Ele
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6.3. Architecture elements Figure 6
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6.4. Architecture rationale Figure
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6.4. Architecture rationale • ris
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6.4. Architecture rationale depicts
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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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9.4. AREL and eAREL traceability ap
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Page 185 and 186: Chapter 10 Architecture decision de
Page 187 and 188: 10.1. Background 10.1.2 Introductio
Page 189 and 190: 10.2. Building a BBN to represent a
Page 197 and 198: 10.3. Reasoning about change impact
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Page 211 and 212: 11.1. Capturing architecture design
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Page 215 and 216: 11.2. Checking AREL models Figure 1
Page 217 and 218: 11.3. Tracing AREL models Figure 11
Page 219 and 220: 11.4. Analysing AREL with BBN • S
Page 221 and 222: 11.5. Limitations Figure 11.13: A P
Page 223 and 224: Chapter 12 Conclusions 12.1 Summary
Page 225 and 226: 12.2. Contributions reasoning metho
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Page 233 and 234: BIBLIOGRAPHY [10] B. W. Boehm, Soft
Page 235 and 236: BIBLIOGRAPHY [37] A. Eden and R. Ka
Page 237 and 238: BIBLIOGRAPHY [62] J. D. Herbsleb an
Page 239 and 240: BIBLIOGRAPHY [89] N. Lassing, D. Ri
Page 241 and 242: BIBLIOGRAPHY [115] D. L. Parnas,
Page 243 and 244: BIBLIOGRAPHY [142] Z. Simsek and J.
Page 245 and 246: BIBLIOGRAPHY [167] W. F. Tichy, N.
Page 247 and 248: Appendix A AREL Tool User Manual 1
Page 249 and 250: 4.1 AREL Check Model When the Check
Page 251 and 252: 4.2 AREL Model Tracing AREL model t
Page 253 and 254: Figure 9 - result of downward trace
Page 255 and 256: To initiate the graph’s creation,
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Page 259 and 260: Useful Definitions The following ar
Page 261 and 262: ) Some projects only c) Not at all
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Page 265 and 266: Complaint Procedure If you have any
Page 267 and 268: Privacy Protection Only investigato
Page 269 and 270: B. Exploring design reasoning. 1. W
Page 271 and 272: 3. Why does the system use asynchro
Page 273 and 274: C. General Comments on AREL Modelli
Page 275: IEEE Computer Society Press. A. Tan
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