1. Exploring the Intentional Dimension during Software (Architecture) Design adding the “why” and the “who/where” to the “what” and the “how” Daniel Gross Faculty of Information Studies University of Toronto Conceptual meta modeling through prototyping based on case study material The First Tropos Workshop Nov. 2001, Trento-Italy

2. Presentation Objective Illustrate a research method for conceptual meta modeling to represent the intentional dimension (intents & know-how) –borrowing from the (qualitative) social science grounded theory research methodology (Glasser & Strauss, 1976; Corbin & Strauss, 1990) Illustrate an integrated research environment for prototyping (tool) meta model & modeling methods –as an integral part of the research method –illustrate the use of a meta-case tool (Meta-Edit+) as such an environment

3. Research questions Conceptual meta modeling question: –Are i* concepts adequate/sufficient to capture software design intents, know-how and reusable knowledge from project documentation? If not, what extensions are needed? Modeling methodology question: –What methods for capturing & reusing intents and know-how from project documentation can be proposed? Research methodology question: –Using case study material, how can we systematically explore i* expressiveness and suggest further extensions and modeling-methodology support? Note: focus on post- mortem-capturing This presentation focus

4. Grounded theory method “meta-model” Based on (Strauss & Corbin, 1990) Initial “meta model” for basic social processes Developing concepts/categori es based on data

5. Conceptual meta modeling with case study material (in the spirit of grounded theory research methodology (Glasser & Strauss, 1976)) Case study material Conceptual meta model based on concepts/classifications, relationships Initial meta model & method Start with a theory (basic ontology)*: “Intentionality is making deliberate design decision to achieve stakeholders’ goals” “Intentionality is distributed among stakeholders and within the system during software design and evolution” * Grounded theory purists don’t like to start with a theory – others argue we inevitably start with one Refine theory concepts analyzing & prototyping with case study material Design knowledge capturing & reuse needs Computational analysis support needs Design guidance support needs New modeling concepts emerge from research data Theory guides to know what to look for in the research data Note: theory concepts need to be found in the actual data, otherwise they don’t make sense (at least in the analyzed case study)

6. “Research method” Modeling Meta modeling Conceptual modeling & analysis (prototyping meta model & method) Research Cycle Capture intent & solution knowledge with existing modeling constructs,Identify limitations Analyze documentation Draw distinctions among meta model constructs and and relationships Specify operational “design process” semantics Document rationales, notes, research issues & relate constructs to research data Use Meta case facilities Start with preliminary agent and goal meta model & method steps Analyzing documentation Method modeling Refine method steps and/or specify new analysis & tool capabilities Knowledge based meta modeling Abstract, classify and parameterize knowledge Specify instantiations and/or bindings semantics

7. Meta modeling with Meta-Edit+ Method steps meta model (basically a flow-chart meta model) methods instances Meta-modeling design, objectives, rationales, definitions & notes Meta modeling design rationales Meta modeling design rationales meta modeling rationale instances methods instances Method model under design Research data capturing & linking Meta-model under design based on actor and goal concepts conceptual model instances capturing intentional design Meta-meta model based on GOPRR (Graph-Object-Property-Relationship-Role concepts) Meta model under design Missing: process-orientation & knowledge-level support, Intended use Daniel’s extensions

8. Lets experiment with a meta model that captures design options and goals Meta concepts Meta relationships

9. Capturing meta model design rationale Declaring meta model construct Reference to document location is captured Capturing meta model construct rationales & source

10. Initial capturing method

11. Captured information with current meta model and capturing method Based on Mitel’s System Operation, Administration, Maintenance, Provision reusable platform architecture documentation

12. Identifying potential meta model extensions Analyzing the data we realize that some design options depend on preceding ones. –we note this for potential meta model extensions … may be useful for tracing impact when retracting design decisions. –we also note a new meta design goal “achieving change impact traceability.” In the text some design options are discussed for the future. –we note the potential need for a new meta-attribute for “designOption” : “potentialFutureDesignOption.” The need to cluster goals and design decisions into actors. –May need method & process-support extensions to guide the clustering. Some decisions relate to product classes (“reusable platforms”) while others are “instantiations” of these (“OAMP reusable platform). –We identify the need to distinguish between actor Classes and instances (“a-system” vs. “this-system”).

13. e.g. “precedence” a new meta model relationship Capturing meta concept rationale and elicitation question

14. method extended to include step for capturing precedence New precedence links

15. Taking notes, adding meta modeling “design” goals Research notes.Note can also be attached to meta modeling constructs Note: meta modeling goals are related to meta model constructs Precedence links allows for change impact analysis Meta model “design” goals

16. Meta-Edit+ vs. Concept-base / Telos Meta-Edit+ limitation. –Unlike Concept-Base only two meta-levels, no cross-meta level support (“w-strata”). Flattening the meta-space creates duplication of concept data. Can’t link method steps to meta constructs to be instantiate. Cant provide adequate knowledge-capturing & parameterization support (needs more meta levels). –Might also need some sort of scripting support (available in concept base?). Meta-Edit+ strengths. –Easy to use graphical user interface for quick prototyping iterations. –Dynamic user-interface generation based on meta-construct definitions. –Easy to use graphical notation definition support including hierarchical decompositions and “explosions.” –Runs on Windows (and Linux) platform.

17. Conclusion Tool requirements for research into conceptual meta-modeling Prototyping support –Prototype emergent i* meta model & modeling method with research data to learn about meta-model expressive abilities and limitations –Executable modeling method Research traceability support –Capture & refine “modeling theory”, research objectives as knowledge of domain increases –Link theory & objectives to emerging meta model –Link emergent meta model to research data Research process support –Capture research issues, goals & notes as they arise –Link issues & notes to meta model, modeling diagrams and/or research data Documentation support –Use research data as examples for modeling examples & tutorials

18. Future methodology work How to relate intentional meta model to “classes” & “instances” of software system product & process models –How do actors, goals, design Options etc. relate to UML type of concepts Architecture type of concepts etc.. –extending GRL work Rework research method and tool support within concept-base / Telos environment