Antony Tang 1, Ann Nicholson 2, Yan Jin 1, Jun Han 1 1 Faculty of ICT, Swinburne University of Technology 2 School of Computer Science and Software Engineering, Monash University Using Bayesian Belief Networks for Change Impact Analysis in Architecture Design

Faculty of ICT Page 2 Presentation Outline Background and Objectives Architecture Design Rationale and Decisions Architecture Rationale and Elements Linkage (AREL) Applying Bayesian Belief Networks to AREL Predicting Change Impacts in Architecture Design Tool Support Conclusions and Future Work

Faculty of ICT Page 3 Background There has been little emphasis on the decision making process on software architecture design. Design Rationale (DR) as a result of a decision is often not captured Even when DR is captured, it is often difficult to explain how decisions relate to and affect the architecture design Change impact cannot be systematically reasoned or explained during the maintenance phase It is difficult to quantify the impact of changes in requirement, design or decision

Faculty of ICT Page 4 What is Design Rationale a reason or an intention for a particular set of thoughts or actions (Cambridge Dictionary) reasons to express the purposes of the designed artefacts with their contextual constraints on realising the purposes (Moran and Carroll 1996) recording the history of how a design comes about through recording logical reasoning to support future reference (Conklin and Burgess-Yakemovic 1996)

Faculty of ICT Page 5 Architecture Design Decisions Early Decision Making Consider Multiple Factors including Functional Requirements, Non-Functional Requirements and Environmental Factors Consider Different Perspectives and Viewpoints Directly and Indirectly Influence the Design Structure of the System Create / Modify Design Elements to Satisfy System Goals / Sub-goals

Faculty of ICT Page 6 Problem Statements How to capture design rationale and represent architecture design decisions in relation to design artefacts? What is the change impact to the system when one or more requirements, designs or decisions are to change?

Faculty of ICT Page 7 Architecture Design Rationale and Design Elements (AREL) Architecture Elements (AE) are requirements and design elements in an Architecture. They are grouped by Architecture Viewpoints (Business, Information, Computation and Engineering) A Design Decision Point is supported by Architecture Rationale (AR) which comprises Qualitative Rationale, Quantitative Rationale and Alternative Architecture Rationale  Qualitative Rationale (QuR) contains constraints, assumptions, arguments, risks & non-risks, weakness and benefits  Quantitative Rationale (QaR) contains measurements of costs, benefits and risks relative to alternative designs  Alternative Design Rationale contains QuR and QaR for alternative designs ARs are related to AEs through a causal relationship

Faculty of ICT Page 8 A Simple AREL Structure in UML Notation > AE and AR Dependency > Design Rationale Encapsulation > Qualitative Rationale Quantitative Rationale Qualitative Rationale Quantitative Rationale Alternative Design & Use Cases

Faculty of ICT Page 9 An AREL Example Input AEs into AR1 Decision supported by AR1 AE as Outcome of AR1 Input AEs into AR3 Decision supported by AR3 Outcome AE of AR3 Note: UML Drawings are created by Enterprise Architect

Faculty of ICT Page 10 Applying Bayesian Belief Networks to AREL Causal Relationship of a decision set AE-AR-AE AE states: Stable / Volatile (indicate the volatility of a requirement or a design object) AR states: Valid / Invalid (indicate the validity of a decision) Root node AE1 contains Prior Probabilities AR1 is conditionally dependent on AE1 (specified by conditional probabilities) AE2 is conditionally dependent on AR1 (specified by conditional probabilities)

Faculty of ICT Page 11 An Example Using Cheque Image Clearing Requirement ANSI Std X9.37,X9.46 Requirements Bundling/reconciling Requirement checks/min Requirement No loss/No duplicate Decision Single-pass processing Design Single-pass presentment design R1.0R2.0R12.0R11.0P(AR1=V|R1. 0,R2.0,R12.0, R11.0) SSSS1.0 SSSV0.9 SSVS SVSS0.8 more……

Faculty of ICT Page 12 An Example Using Cheque Image Clearing (cont’d) Decision AR2 Select multi-nodes over Large single node Design Dual-Node design Decision AR3 Use Fail-over mechanism Design Design for Fail Over Recovery Decision Select Checkpoint Recovery over Full File Recovery Design Design for Checkpoint Recovery

Faculty of ICT Page 13 Predicting Change Impacts Insert Evidence, Say single node Decision based on dual-node no longer valid Node Recovery has to change Checkpoint decision may / may not be affected

Faculty of ICT Page 14 Diagnostic Reasoning Insert Evidence, Say single pass design was to change

Faculty of ICT Page 15 Tool Support UML Package (e.g. Enterprise Architect) to capture and represent AEs and ARs  Capture Quantitative and Qualitative Rationale  Capture Requirements, Information, Design and Deployment Models  Relate them using > association BBN Package (e.g. Netica) to Quantify Causal Relationship  Capture Prior probabilities for root nodes  Capture Conditional Probability Tables for other nodes  Compute Joint Probabilities AREL Tools:  Check Directed Cycle  Extract UML Model into BBN  Merge the model modifications in the two tool-sets

Faculty of ICT Page 16 AREL Tool Set – Extract UML Model into BBN

Faculty of ICT Page 17 AREL Tool Set – Merge UML and BBN Changes

Faculty of ICT Page 18 Conclusions & Future Work AREL defines a causal relationship between architecture elements and decisions (supported by architecture rationale) Apply BBN to AREL to quantify the strength of the causal relationships between architecture elements and decisions This application enables  Tracing of design rationale with requirements and design artefacts  Estimate change impacts / diagnose design reasoning using BBN Further Considerations  Semi-objective probability estimations based on experience  Costs-benefits of applying the method Future Work  Apply utility function to estimate expected cost of maintenance

Faculty of ICT Page 19 Related Work Zhang & Jarzabek, “ A Bayesian Network Approach to Rational Architectural Design ”, International Journal of Software Engineering and Knowledge Engineering, Vol. 15, No. 4 (2005) Possible designs Design Outcomes

Faculty of ICT Page 20 Related Work (Cont’d) Characteristics of Zhang and Jarzabek’s work  Model different combinations of design choices  Use BBN to calculate the quality of the configuration of the architecture for selecting an architecture design Differences to Our Work  Decision making is an incremental process  The design rationale behind a decision is based on many considerations, encapsulated in a decision node  The architecture design is modelled in a series of causes and effects to represent what has been decided  Use the BBN model for analysing change impact

Faculty of ICT Page 21 Thank you.