A Rationale-based Model for Architecture Design Reasoning

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10.2. Building a BBN to represent an AREL model For the intermediate situations where one or more, but not all, of the AE causes are subject to change, the CPT entries must be chosen carefully to reflect the relative weight of the individual causes on the architecture decision. For example, if there are two AE causes and both were of equal weight, say x, when making the decision, the CPT entries would be the same. • P(AR1 = invalid|AE1 = stable, AE2 = volatile) = x • P(AR1 = invalid|AE1 = volatile, AE2 = stable) = x The actual value of x must then reflect the causal impact a single volatile AE is expected to have on the decision; x close to 1 means the decision will become invalid even with the single volatile cause, 0.5 means a fifty-fifty chance, while x close to zero means the decision is reasonably robust if only one AE cause is volatile. A more dominant (AE2 ) and less dominant (AE1 ) cause combination might be represented by: • P(AR1 = invalid|AE1 = stable, AE2 = volatile)=0.8 • P(AR1 = invalid|AE1 = volatile, AE2 = stable)=0.3 In this example, if AE1 is stable and AE2 is volatile, the probability of AR1 being invalid is higher than if AE2 is stable and AE1 is volatile. It indicates that AE2 is more influential to AR1 than AE1 because when AE2 becomes volatile, there is a higher chance that AR1 will become invalid. Relationship B When an architecture decision is made, an AR is created to record the rationale and linked with one or more resulting AEs. During architecture design, if a requirement changes then it is possible that the AR depending on it will be invalidated and so all resulting designs from that AR are more likely to be volatile and subject to change. Note that there is no direct relationship between those AEs that are caused by the same AR, so we need only consider the effect of the AR on each AE individually. In Figure 10.2, for example, even though AE4 and AE5 are both dependent on AR1, they are independent of each other given AR1. So the CPT P(AE i |AR) for each AE i is specified as follows: • P(AE i = volatile|AR = valid) • P(AE i = volatile|AR = invalid) 175
10.2. Building a BBN to represent an AREL model Note that in each case P(AE i = stable) = 1− P(AE i = volatile). In most cases, while the AR is valid, we would not expect the AE to change, hence P(AE i = volatile|AR = valid) would be close to 0. Conversely, if the AR is invalid, the AE is much more likely to change. The more an AE depends on an AR, the more likely it is subject to change when AR becomes invalid, and hence P(AE i = volatile|AR = invalid) becomes closer to 1. If an AE depends only very loosely on an AR, then P(AE i = volatile|AR = invalid) might be set much lower than 1. In Figure 10.2, AR1 → AE4 and AR2 → AE6 are examples of relationship B. Relationship C It is possible that an AE is the result of multiple separate decisions (ARs). For example, in Figure 10.2, AE5 is the result of two separate decisions AR1 and AR2. The conditional probability of AE5 can then be defined as P(AE5|AR1, AR2). Since AE5 is dependent upon both decisions AR1 and AR2 simultaneously, estimates for the CPT can be expressed as: • P(AE5 = volatile|AR1 = valid, AR2 = valid) • P(AE5 = volatile|AR1 = valid, AR2 = invalid) • P(AE5 = volatile|AR1 = invalid, AR2 = valid) • P(AE5 = volatile|AR1 = invalid, AR2 = invalid) The causal relationship being modelled in this CPT is essentially an additive one: the more decisions that are invalid, the higher the probability that the common resultant AE will be volatile. While all of the decisions are still valid, the CPT entry for P(AE5 = volatile) will be close to zero, and if all the decisions are invalid, it will be close to 1. For the intermediate situations where one or more, but not all, of the AR decisions are invalid, the CPT entries must be chosen carefully to reflect the relative weight of the individual decisions on the resultant AE. Assuming AR1 has more influence on AE5 than AR2 in the example, the cause combination could be represented as: • P(AE5 = volatile|AR1 = invalid, AR2 = valid) = 0.8 • P(AE5 = volatile|AR1 = valid, AR2 = invalid) = 0.3 These CPT entries mean that the combination where AR1 is invalid and AR2 is valid is quite likely to cause AE5 to be volatile (probability 0.8). Conversely, when AR1 is valid and AR2 is invalid, the probability that AE5 is volatile is lower (0.3), signifying less influence by AR2. In other words, AR1 has a larger impact on AE5 ’s volatility than AR2. 176
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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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Page 153 and 154: 8.1. Background Based on these assu
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Page 171 and 172: 9.1. Background 9.1 Background In t
Page 173 and 174: 9.2. Traceability of architecture r
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Page 187 and 188: 10.1. Background 10.1.2 Introductio
Page 189 and 190: 10.2. Building a BBN to represent a
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Page 197 and 198: 10.3. Reasoning about change impact
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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
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Page 225 and 226: 12.2. Contributions reasoning metho
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Page 233 and 234: BIBLIOGRAPHY [10] B. W. Boehm, Soft
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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.
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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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