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Models, Modelling , MBSE

Models, Modelling , MBSE. Professor John Hosking, Dean of Engineering and Computer Science. Part 1 General Concepts. Models and modelling. Formalisation language syntax/semantics Scope of applicability Insight Execution Prediction. v = u + at v 2 = u 2 + 2as s = ut + ½at 2.

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Models, Modelling , MBSE

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  1. Models, Modelling, MBSE Professor John Hosking, Dean of Engineering and Computer Science

  2. Part 1 General Concepts

  3. Models and modelling Formalisation language syntax/semantics Scope of applicability Insight Execution Prediction v = u + at v2 = u2 + 2as s = ut + ½at2

  4. Models and modelling Formalisation language syntax/semantics Scope of applicability Insight Execution Prediction CH4 + 2 O2 -> CO2 + 2 H2O

  5. Models and modelling Formalisation language syntax/semantics Scope of applicability Insight Execution Prediction

  6. Models and modelling Formalisation language syntax/semantics Scope of applicability Insight Execution Prediction

  7. Models and Engineering • Engineering is about modelling • Including Software Engineering • Much of the engineering process is about taking a specification and turning it into design model(s) • Using theory, methodology, evidence based best practice • Models are tested • scope of applicability • compliance to specification • Models are used to specify detailed construction • Construction overseen by engineers • true for SE?

  8. Modelling and Software Engineering “The growing complexity of software is the motivation behind work on industrializing software development. In particular, current research in the area of model driven engineering (MDE) is primarily concerned with reducing the gap between problem and software implementation domains through the use of technologies that support systematic transformation of problem-level abstractions to software implementations.” France and Rumpe,2007, Model-driven Development of Complex Software: A Research Roadmap, FOSE’07

  9. MDE is about Communication Model Problem Domain Implementation Domain Req Model Analysis Model Design Models Design Model Problem Domain Implementation Domain Test Models Test Models What modelling language(s)? How are they designed to be effective? How are they implemented?

  10. MDE is about Viewpoints Req Model Analysis Model Design Models Design Model Problem Domain Implementation Domain Test Models Test Models Separation of concerns Consistency management Hidden dependencies

  11. MDE is about Automation Auto/semi-auto transform Performance? Deadlocks? Transform Model Anti Patterns? Req Model Analysis Model Design Models Design Model Problem Domain Implementation Domain Test Models Self Consistent? Code Smells? Test Models Transform specn? Traceability links? Consistency? Versioning? Analysis tool scope? Limitations? Usability? Specification/implmn Coverage?

  12. MDE Challenges “… we consider the problem of developing MDE technologies that automate significant portions of the software lifecycle to be a wicked problem. A wicked problem has multiple dimensions that are related in complex ways and thus cannot be solved by cobbling solutions to the different problem dimensions.” France and Rumpe,2007, Model-driven Development of Complex Software: A Research Roadmap, FOSE’07

  13. MDE and Formal Methods • Why not just use formal specification techniques? • FSTs typically limited in scope • Eg only work for some viewpoints • Tradeoff in expressability and ability to mechanically analyse • Hence use FSTs to analyse subset of models • Eg Z models for data and operation viewpoints • “Model checking” for state transition viewpoints • Petri nets for control flow viewpoint

  14. Development versus Runtime Models • Most MDE initiatives have focused on development models • Abstractions above code • Runtime models present abstractions of executing systems • How to use to manage and modify executing software • Adaptive systems – monitor behaviour (eg performance) and adapt (eg add extra servers)

  15. Some major MDE initiatives • Model Driven Architecture (MDA) - OMG • Three viewpoints: computation independent, platform independent and platform dependent • MOF, UML, QVT • Very rich set of modelling languages lost of complexity • Example of “extensible general purpose modelling language” approach • Software factories – Microsoft • Many small domain specific viewpoints linked by transforms • Small lightweight modelling languages • Heavy emphasis on reuse of knowledge • Example of “domain specific modelling language” approach

  16. Pros and cons Extensible GPML + “Standard” models + Model interchange + Analysis tool interchange + Build it once • Complex languages • Not client friendly • Extension mechanisms complicate things Domain Specific MLs + Client friendly + Simple languages + Simpler tooling • Build it often • Smaller user base => higher maintenance cost • DSL Babel challenge

  17. Model Driven Systems Engineering • Extends from Software Engineering to Systems Engineering • Typically Extensible GPML based • Heavy emphasis on standardisation • Not surprising • Egs • SysML • Function Blocks (more for embedded systems) • BIM/IFC (for integrated design of buildings)

  18. SysML • OMG driven (UML standards developers) • Extends/restricts UML (ie GPML approach) • New viewpoints • Requirements, Parametric views • Supports V&V, gap analysis • Eliminates some software centric viewpoints • Only uses 7 of UML 2’s 13 diagrams • Replaces “classes” with “blocks”

  19. IEC 61499 Function Blocks • From Control community • Pushes Block concept in SysML further • Gaining popularity in embedded systems community • Arguably more implmnoriented than SysML • See Vyatkin review paper • Argues for combining

  20. BIM IFC • Building information modelling • Integrates viewpoints of multiple professionals working on constructing/maintaining buildings • Engineers, PMs, architects, builders, plumbers, … • Aims to revolutionise building construction • Current state of the art – much manual rentry of data • Significant opportunity for error • BIM aims for standardised interoperability • Industry Foundation Classes • Base set of classes defining the multiple viewpoints • EXPRESS modelling language extensible GPML approach • Much work done – much to do

  21. Part 2: Examples of MDE Projects from my research

  22. Some areas of contribution • Meta-tools for simply implementing graphical modelling languages (domain specific visual languages – DSVLs) • Performance estimation tools • Model transformation tools • EXPRESS modelling environment • Requirements extraction tools A few examples follow

  23. How to build a Domain Specific Visual Modelling Language (DSVL)? • Design the DSVL formalism • Domain modelling, Physics of Notations, Cognitive Dimensions of Notations, … • Design and implement an editing environment & possibly a code generator • Icons and connectors, domain model, views on domain model, behaviour under user interaction, code generator, simulator, … • Lots of programming OR use a meta-tool

  24. Meta-tool • Tool to help build other software tools • In this case a tool to specify a DSVL and its modelling environment and which generates the environment • It typically uses several DSVLs to make specification easy Tool designer Tool end user uses specifies/generates uses specifies/generates Meta tool DSVL Modelling tool Other possibly executable models

  25. Pounamu 2003 JViews 1997 Ispel 1991 JComposer 1998 Marama 2007 … Kea 1989 MViews 1993 My group’s meta-tool research work • Have developed a series of frameworks and meta tools for DSVL specification Design Tools Engineering, Software Frameworks for constructing multi-view multi-notation environments Meta tools for specifying & constructing multi-view multi-notation environments Java + Web Services Eclipse + Java Prolog Java Plus lots of applications developed using the frameworks & meta tools

  26. Tool Specification using Marama GeneratedModelling Tool • Domain model • EER • OCL • Icons &Connectors • Views • Icons/connectors • Model elements • Mappings • Behaviour • Constraints • Layout About a day to specify and implement a basic modelling tool

  27. Marama notes • Marama is an example of a model driven toolset itself • New DSVL expressed using a variety of graphical models expressing different viewpoints then DSVL environment auto generated from those models • Supports DSML approaches • Easy to design and implement small modelling languages • A research tool • Lacks lots of features you’d want in a production toolset • But has been hardened and used in industrial projects (for large European banks) by Sofismo, a Swiss MDE consultancy company

  28. Performance estimation – MaramaMTE • Example of a model analysis tool • Implemented using Marama • Given a software architecture how well will the implemented system work? • MaramaMTE supports • Modelling software architectures for service oriented systems • Modelling of workload models • Generation of testbed able to be exercised using workload model; generates workload testbench • Assumes inter-component comms cost less than computation cost • Deployment of testbed and workload testbench onto real hardware • Runs system – generates performance stats

  29. MaramaMTE End user interaction spec Architecture spec

  30. Results visualisation

  31. Requirements extraction – MaramaAI • Takes textual requirements in the form of scenario descriptions • Auto-extracts Essential Use Cases • Abstracted interaction models • Supports English and Malay! • Matches the derived EUCs against known EUC patterns • Looking for errors/missing features/etc • Generates mock user interfaces for RE to confirm requirements with client • Round trip engineering • Maintains consistency between the various viewpoints

  32. Example EUC

  33. Extraction and mapping Map to the EUC diagram categorising “select option” interaction as a “user intention” 2 3 1 “select voter registration option (1)” is mapped to a particular abstract interaction – “select option (2)”

  34. Matching to EUC best practice pattern

  35. Map to interaction model and mock UI

  36. Summary • Models and their importance in Science and Engineering • MDE basics • Issues with MDE and examples of initiatives • MD Systems Engineering • Meta tools for quickly specifying and implementing DSVLs and their environments • A couple of model analysis and transformation tool examples

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