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Ebrahim Bagheri E.Bagheri@unb.ca
The Integration of Para-consistent Conceptual Models Influenced by Uncertainty: A Belief-theoretic Approach Ebrahim Bagheri Supervisor: Dr. Ali A. Ghorbani 11/22/2018
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Agenda Introduction Background and Related Work Challenges Motivations
Proposed Model Contributions to Knowledge Evaluation Methods Thesis Timeline 11/22/2018
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Introduction Software development is a problem solving process
The dimensions of the problem are: Context Environment Situation Users etc. Solving a problem requires suitable tools! 11/22/2018
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Introduction (cntd.) Conceptual models are those tools
Conceptual modeling is also known as problem analysis, or conceptualization Useful for the formalization of experts understanding of a problem Also useful for the systematic classification of knowledge and procedures 11/22/2018
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Why Conceptualize? Make real-world concepts tangible
Support communication and collaboration Detect missing information, errors, or even misinterpretations Specify software behavior Provide an orientation on software performance 11/22/2018
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The Process Early Late Problem Domain Conceptualization Product
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Famous Models Software Engineering: Knowledge Engineering:
Classical: Telos, DFD, SADT, ERD, … Advanced: UML, EM, KAOS, i*, … Knowledge Engineering: Model, CML, KARL, CommonKADS 11/22/2018
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Viewpoint-Based Models
Different areas and amount of knowledge helps better analyze a problem Employing more information sources for getting a better insight High complexity of a software system requires collaborative design effort Sources of information (participants) are known as viewpoints 11/22/2018
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Related Work Viewpoint-Oriented Requirement Definition (VORD – Preview): Employ any notation Formal definition of Viewpoint: viewpoint name viewpoint focus (boundary and scope) viewpoint concern (e.g. organizational goals, business objectives, etc.) viewpoint information sources viewpoint requirement definitions viewpoint activity history 11/22/2018
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Related Work (cntd.) Nuseibeh et al. define a viewpoint as:
Representation style Domain of interest (area of concern) Requirement specification Work plan (requirement engineering strategy) A work record Inflexible due to strict declaration of: Work plan 11/22/2018
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Related Work (cntd.) Controlled Requirement Expression (CORE):
divide the problem domain into disjoint areas of concern Consistent and complete model when sub-models are merged into a single model How can we clearly split the problem domain? 11/22/2018
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Challenges to VP-based Models
Defining a unique representation style Use of common terminology (vocabulary) Identifying specification overlaps Detecting model discrepancies Merging different models Evaluating the final product 11/22/2018
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Challenges (cntd.) Humans make conception errors due to:
Risk aversion Short term memory Perceptual problems Epistemic uncertainty (aka partial ignorance) Not all information sources are equally reliable Different problem statement strategies 11/22/2018
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Current Solutions Shared ontology: Human expert inspection:
Common application vocabulary Thesauri Human expert inspection: Conflict forms Evaluating conflict metrics Category theory Belnap’s knowledge order 11/22/2018
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Current Solutions (cntd.)
Formal Methods Convert viewpoint specifications into VWPI and use static analyzer First-order logic and use backward and forward chaining Goal regression in KAOS Incrementally elicited ranked structures Make use of epistemic states Apply preference orderings 11/22/2018
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Motivations Lack of attention to the following issues:
Need to capture uncertainty Unify model integration for different CM schemas Address information source reliability Real-time model development, negotiation, and integration Evaluation of integration effectiveness 11/22/2018
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Uncertainty Dempster-Shafer theory of evidence:
A tool for numerically quantifying and reasoning under uncertainty An extension to Probability theory where power set elements receive probability (belief) mass A rich area of research with tools for Belief function combination (e.g. Dempster’s rule of combination) Belief propagation Belief entropy measures (e.g. generalized entropy) 11/22/2018
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Proposed Model Conceptual Modeling Layer Underlying Construct Layer
Develop Individual Conceptual Models (Use Linguistic Terms) Calculate Integration Efficiency Conceptual Model Integration Conceptual Modeling Layer Proposed Model Convert Model to the Underlying Construct Format Integrated Construct Instance Base Underlying Construct Layer Process Viewpoint Beliefs (Opinions) Calculate Pre-Consensus Belief Recommendations Belief Merge Calculate Belief Mass Merge Effectiveness Recommend Belief Mass for Consensus Formation Viewpoint Reliability Assessment Belief Layer 11/22/2018
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Schematic View Discount Discount Viewpoint Viewpoint Discount
Update Update Shared Understanding (Consensus) Viewpoint Viewpoint Update Discount Viewpoint 11/22/2018
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Sample Process Mary Bob John Car Road Parking FA/AC SA/SC Tire Door
Brand FA/SC EW/SC Bob SA/SC: (0.5, 0.15, 0.35) Slight Agreement/Slightly Certain FA/AC: (0.85, 0.05, 0.1) Firm Agreement/Absolutely Certain EW/SC: (0.33, 0.33, 0.33) Either Way/Slightly Certain FA/SC: (0.65, 0.05, 0.3) Firm Agreement/Slightly Certain Sample Process 11/22/2018
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Belief Space (Subjective Logic)
Uncertainty 1 Uncertain Highly Uncertain Very Slightly Certain Highly Certain 1 1 Belief Firm Disagreement Disbelief Slight Disagreement Either Way Slight Agreement Firm Agreement 11/22/2018
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Sample Process (ctnd.) Car Tire Door Brand Road Parking SA/VU EW/AU
Integrated View (Before Pruning) Car Tire Door Brand Road Parking SA/VU EW/AU SA/SC FA/SC Integrated View (After Pruning) Car Tire Door Road Parking Brand 11/22/2018
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Contributions to Knowledge
Employing linguistic terms Addressing uncertainty Creating an underlying modeling construct Consensus building and negotiation Pre-consensus belief recommendation 11/22/2018
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Contributions to Knowledge (cntd.)
Merging conceptual models Evaluating merging effectiveness Information source reliability assessment Tool support for the proposed model 11/22/2018
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Evaluation Methods Formally prove the correctness of the:
Merge operators Belief recommendation algorithms Analyze the behavior of the operators under extreme conditions Conduct several case studies using A number of Computer Science graduate students A tool that will support the proposed solution The preliminary tool is being developed in Eclipse (EMF) 11/22/2018
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Thank you 11/22/2018
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Goal regression The idea of goal regression is linked to planning via plan modification...i.e. in order to achieve P and Q, construct a plan F that achieves P, and then modify F so that it achieves Q while still achieving P. The idea is to protect P so that the choice of where to place the steps for achieving Q is determined relative to the plan for P. 11/22/2018
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