Seminar Model Driven Software Engineering What is it? Topics Requirements Schedule Contact

„Model-based Software Development“, A famous painting by René Magritte

„Model-based Software Development“, Systems versus Modells The image (model) captures important properties and lets us reason about  appeareance  functions  usability  etc But with an image (model) we cannot smoke. isModelOf A system A model conformsTo

„Model-based Software Development“, Modells Represent Views of a System Termite population in France The System Models France 1453 French cheese map Railroads in France

„Model-based Software Development“, Metamodels explain Models How do we know what a map tells us? The „Legend“ explains the used symbols  „Bicycle Lane“ …… The „Legend“ is the „metamodel“ of the map  Metamodels model the language of models  Elements & their legal use  syntax  Meaning of elements  semantics

„Model-based Software Development“, Meta-Models The „Image of an image of an image“ is a meta-metamodel  One could go on like this forever… The „image of an image of a pipe“ is a modell of a model – a metamodell  It captures aspects of images  Frame, contents, label, … The „image of a pipe“ is a model of the system  It captures aspects of pipes  Shape, colour,... The pipe is real – a system. modelOf

„Model-based Software Development“, The UML Metamodell ClassAttribute * 1 A UML-Model Spy Name : String The (Meta-)Modell-Pyramid M2M2 M1M1 Meta-Object-Facility Class Association source destination M3M3 conforms to A System („the real world“) MOF (Meta-Object-Facility) (model of UML metamodels) UML Metamodel (Model of UML models) UML Model (Model of a system) M0M0 My Name is... conforms to M0M0 M1M1 M2M2 M3M3

„Model-based Software Development“, Domain Specific Language (DSL) Domain  An are of knowldege with tightly interrelated concepts  Examples: Genetics, flight control, data base management, … DSL – Domain Specific Language  Approach: The Concepts of a domain are defined by a metamodel  Advantages compared to general purpose language  Higher abstraction level  Easier understanding by domain experts  Automated mapping to lower abstraction levels  Examples  Representation of database schema by ER diagramm (grafical DSL)  Representation of database schema by DDL script (textual DSL) MOF – Meta Object Facility  Model based language for defining meta models  Master form (unique metametamodell MMM)

„Model-based Software Development“, Concrete Syntax versus Abstract Syntax package demo; class C { int m(int i) { m(i); } var method C parent param type name type parent int i parent var access name i int m name m parent call block method class name demo name package 1 4 parent param(4, 3, ‘i'‚ int) method(3, 2, 'm', int,[4]) class(2, 1, 'C') package(1, 0, 'demo') block(5, 3, [6]) call(6, 5, null, 3 ) ident(7, 6, 4 )

„Model-based Software Development“, package(1, 0, 'demo'). ● Describes the structure of the input or output of a system ◆ Textual ◆ Graphical ● Specified by a grammar ◆ Textual → EBNF ◆ Graphical → Graph grammar ● Describes the structure of the internal representation (= the model) ◆ Objects ◆ Clauses ◆ Relations ● Specified by a meta-model ◆ See previous slides Concrete Syntax versus Abstract Syntax package demo;

„Model-based Software Development“, Families of Model Transformation Concrete Syntax (textual / grafical) Abstract Syntax (internal) Text-to-model Model-to-text Model-to-model

„Model-based Software Development“ Summer semester 2016 –– Core MDSE Topics

„Model-based Software Development“, Eclipse Modeling Framework ECORE as the basis of tool interoperability Transformation rules use the meta-models Tools use ECORE to understand the meta-models Meta-model of Source Model Source Model Meta-model of Target Model Target Model conforms to Transformation Rules ECORE conforms to

„Model-based Software Development“, Xtext: Define your own DSL! ● 1. Define the grammar of your language

„Model-based Software Development“, Xtext: Define your own DSL! ● 2. Automatically generate ◆ a parser ◆ an internal model ◆ a complete IDE for the new language

„Model-based Software Development“, Xtext: Customize your DSL! ● Configure the code generation workflow ◆ Workflow language (MWE2) ◆ Dependency injection (Google Guice) ◆ Continuous Integration (Maven) ● Customize ◆ Semantic checking ◆ Error reporting ◆ Outline ◆ Formatting ◆ Autocompletion

„Model-based Software Development“, Xtend: Model to Model Transformation ● Full programing language ● Java made easy ◆ Less boilerplate code ◆ Type inference ◆ … ● You can work on the model otherwise, but Xtrend makes it much easier

„Model-based Software Development“, Xtend: Model to text transformation ● Template language embedded into Xtend Literal output (fully formatted, no need for System.out.println(„…“) Start template End template Embedded code Reference to an attribute of the currently processed model element

„Model-based Software Development“, Viatra: Graph-based Model to Model Transformation ● Graph-based transformations

„Model-based Software Development“, ATL: Hybrid model-to-model transformation ● Declarative … …and operational

„Model-based Software Development“ Summer semester 2016 –– Application Topics

„Model-based Software Development“, Propositionalization ● What is Machine Learning? ◆ Learning models from observations ◆ E.g detect spam s, predict whether printing machine will fail ●O ften transformations to simple feature vectors ◆ Feature vector example: (sunny, 23.2 degrees Celsius, windy) ◆ Real world: often complex relationships e.g. social graphs of persons, complex interactions in machines Task : ● Look at transformation techniques from MDSE perspective and present comparative analysis with (dis-)advantages

„Model-based Software Development“, Propositionalization ● References: Ristoski, Petar, and Heiko Paulheim. "A comparison of propositionalization strategies for creating features from linked open data." Linked Data for Knowledge Discovery (2014): 6. Kramer, S., Lavrac, N., Flach, P.: Propositionalisation approaches to Relational Data Mining. In Dzeroski, S., Larac, N., eds.: Relational Data Mining. Springer, Berlin (2001) 262–291 Maier, Marc, et al. "Flattening network data for causal discovery: What could go wrong?." Workshop on Information in Networks

„Model-based Software Development“, Machine Learning ● Modelling: Each type of classifier is a model, which follows certain properties and learns a particular task. e.g. –Decision Trees –Neural Networks –Rule based Learners ● Task 1: Look at learning algorithms from MDSE perspective and present an analysis of models ● Task 2: Look at a machine learning tool e.g. WEKA, and present a comparative analysis of learning models from MDSE perspective

„Model-based Software Development“, Kernel based Learning ● Modelling layer : ● There are some classifiers called kernel based classifiers. ● They require data to be transformed in a particular manner. i.e. ð low dimensions ð linearly separable. ● Task: Explore different kernel techniques from MDSE perspective and present analysis of kernel based modelling methods

„Model-based Software Development“, Kernel based Learning References : lBishop, Christopher M. "Model-based machine learning." Philosophical Transactions of the Royal Society of London A: Mathematical, Physical and Engineering Sciences (2013): lhttp://research.microsoft.com/en-us/um/people/cmbishop/downloads/Bishop- MBML-2012.pdfhttp://research.microsoft.com/en-us/um/people/cmbishop/downloads/Bishop- MBML-2012.pdf models.html models.html

„Model-based Software Development“, Model based Optimization ● Given a complex optimization problem, the task is to find the values of parameters that optimize the problem. e.g. ð Data packet routing, ð Shortest path  Function optimization ● There are different methods to model a solution to such problem. ● Mathematical Modelling –Gradient Descent ● Algorithmic Modelling –Genetic Algorithm ● Task : Explore any one type of such optimization algorithms with MDSE perspective and highlight the underlying modelling techniques

„Model-based Software Development“, Model based Optimization References :  df df  %20Survey%20of%20model- based%20methods%20for%20global%20optimization.pdf %20Survey%20of%20model- based%20methods%20for%20global%20optimization.pdf