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Object Oriented Modelling

Object Oriented Modelling. Object Oriented Modelling. Develop cognitive models to help discover and design OO software Focus is on finance applications High-level Concept Mapping techniques Map CMs to UML, patterns and code. What is a Concept?.

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Object Oriented Modelling

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  1. Object Oriented Modelling

  2. Object Oriented Modelling • Develop cognitive models to help discover and design OO software • Focus is on finance applications • High-level Concept Mapping techniques • Map CMs to UML, patterns and code

  3. What is a Concept? • A regularity in entities, objects, activities or events • Designate a concept by a label • We use concepts as recognition devices • Concepts can be abstract/high-level or concrete/low-level

  4. Examples of Concepts • Instrument, option, IBM stock • Pricing model, PDE, FDM • MC pricing engine • Risk System

  5. Links • We ‘glue’ concepts together to form propositions • Meaningful relationships between concepts • A link is typically a verb or verb phrase • Source: text, word-of-mouth, experience

  6. Examples of Links • FDM uses a PDE • An Asian option has various kinds of payoff • A Cheyette model is a kind of Asian option • Crank Nicolson is a FD scheme • A portfolio consists of instruments

  7. Relationships with OO • Concepts correspond to classes and (sub)systems • Links correspond to ISA, aggregation and association relationships • We create a concept maps, evaluate it and then map to C++ classes and patterns • We recommend it!

  8. Concept Map • A set of concepts with links connecting them • Concepts correspond to nouns, links to verbs and verb phrases • Originally used in Education • Duffy used it for Object Modeling Technique (OMT, 1995)

  9. Example: Australia

  10. Finite Difference Method

  11. Why Concept Maps? • Forces us to think about the problem • Easier to understand and to discuss than ‘flat’ text • Front-end to UML and Design Patterns (Gamma et al) • Many stakeholders can understand them

  12. Concept Mapping Process • We wish to develop techniques for creating concept maps • Cleat input and output (defined process) • Input: text, discussion, domain knowledge • Output: One or more (hierarchical) concept maps

  13. Categories of Concept Maps • Describing the structure of (complex) objects • Describing dependencies in a dependency graph • Data flow in a ‘data graph’ • Any combination of the above

  14. The Filtering Process • Texts tend to be ambiguous • People tend not to ask question • Get a common frame of reference ASAP • Apply standard questions

  15. Questions • What is • What kinds of • How to • When, why • Relationship questions • Follow-on questions

  16. Sources of Confusion • Noise (redundancy) • Silence • Overspecification • Contradiction • Ambiguity • Role (a ‘view’ of the ‘real’ thing, what is the latter?)

  17. The Process • 1. Make a list of words/concepts in current problem • 2. Apply filtering process (modify list in 1.) • 3. Find the links between the words • 4. Construct sentences/propositions between the words in steps 2 and 3 • 5. Construct the concept map

  18. The Map • 1. List key concept • 2. List supporting concepts at next level of generality • 3. Create links between main and supporting concepts • 4. Create cross-links between supporting concepts • 5. Goto step and execute for each supporting concept

  19. Example: Instruments

  20. Example: Monte Carlo

  21. Example: Asian Options

  22. Example: Pricing Models

  23. Example: Merging Concept Maps

  24. What’s next? • Assuming we have a good feeling about the map, start design • UML components, classes and corresponding diagrams • Design patterns • C++ code

  25. Example: Component Diagram

  26. Tips on Text Input • At most 1 A4 • Describe what the system should deliver • What is the input? • Describe the activities in the process from input to output

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