Using knowledge in model-based software development

1. Using knowledge in model-based software development Enn Tyugu Institute of Cybernetics of Tallinn University of Technology

2. Why another SW technology? • Software engineering (SE), being often a part of the development of high-tech products, still lacks high-tech tools for its own usage. Much manual and routine work has to be performed in order to get a software product. • Software development is a knowledge-intensive process, but knowledge usage is little supported by the technology.

3. Spiral: Req. spec. Design Testing Implementaion Agile (XP): Model-Based: Req. & architecture Domain engineering Impl. Impl. Impl. Impl. Application engineering Testing SW technologies Waterfall: Reqirements spec. Design Implementation Testing

4. Model-Based SW Technology Domain engineeringSoftware assets Application engineeringApplication (Domain knowledge acquisition) (Domain knowledge application)

5. Software assets Software assets are the reusable resources used in application engineering: • Domain specific language (textual and visual) • Domain specific SW components • Domain specific models

6. History • Simula • FGCS and Prolog • Knowledge-based system projects • Using metamodels

7. Best of existing MBSE • Simulation tools: Simulink, ... • NASA ISS SW technology • Visual modeling tools: EMF, MetaEdit, ... • UML-based methods

8. Using metamodels This approach includes the usage of UML-based models and metamodels. It concentrates either on • research of transformation rules for transforming an initial specification (a model) into another model or an executable code • or development of rules that represent the operational semantics that enables one immediately to perform the required computations.

9. Dynamic metamodeling example Semantics Definition Syntax Definition Operational rules Semantic metamodeling Graph transformation rules semantic mapping Metamodel Runtime metamodel typed over conforms to conforms to conforms to Expression conforms to Transition System Model States Gregor Engels

10. What is needed? • Knowledge representation and handling methods • Easy access to conventional programming tools -- a general purpose programming environment • DSL implementation tools • DSL application environment

11. What is critical? • Using knowledge for getting automatically a program (or computations) out of available material (from the assets) that are specs, components, models, ... . • If this is achieved, then • the program will be bug-free with respect to its specification (model and goal) • considerable amount of routine work (coding) will be avoided • maintenance and amendment of programs will be easy. Cooke, D. E., Barry, M., Lowry, M., Green, C. NASA’s Exploration Agenda and Capability Engineering. IEEE Computer, vol 39, no. 1,2006.

12. Requirements for development • A crucial part of the model-based software development is automation of the usage of software assets in the application engineering phase. If we consider the result of the application engineering just as a program, then we can say that an efficient program synthesis method that uses the knowledge must be available. • A tool developed in this way should be supported by a software technology that must have sufficient advantages compared to the existing and widely used ones. (Consider all efforts already invested in the development of various software technologies, e.g. the UML-based ones.) • To become a generally applicable technology, model-based software development must provide at least the same programming support as the existing general purpose frameworks (Java, .NET etc.) give us.

13. Ideas for development 1 • A way to achieve this is to develop a framework that merges knowledge-based technique with general purpose programming. • One can imagine building a knowledge-based tool on top of Java by extending the Java language, for example, just with comments that include the knowledge usable by the tool. Doing this, one should carefully preserve all Java possibilities for program development.

14. Ideas for development 2 • A tool can be useful only if it adds essential features to the existing platform. These features could be: visual development of models (specifications), user friendly knowledge representation means, easy debugging of large knowledge-based software components, automatic composition of large programs from specifications (models). • Knowledge-based part and procedural part of the system may have separate name spaces. Only method names of classes should be used in the KB part of a class. • All Java types (including reference types) should be available in the KB part.

15. im mod arg re Example domain Let us take an electrical engineering domain – alternating current cicuits as an example. Domain analysis gives us the following required concepts: • Complex numbers mod 2 = re 2 + im 2 mod * sin(arg) = im • Complex values of current i, voltage u, impedance z and conductivity g that will depend on frequency f or cicular velocity ω, where ω = 2 π f. • Elements of circuits: branch, resistor, capacitor, inductivity • Fragments of circuits: series and parallel connection of subcircuits (branches) • Some instrumetation components: frequency characteristics,...

16. The first concept description We need a knowledge representation language convenient for engineers, i.e a language that that includes equations. Here is an example of this language. import java.util.*; class Complex {/*@ specification Complex { double re, im, arg, mod; mod^2 = re^2 + im^2; mod * sin(arg) = im;} @*/ }

17. More concepts class Branch { /*@ specification Branch { Complex z, i, u, g; double f; u.mod = i.mod * z.mod; u.arg = i.arg + z.arg; g.mod * z.mod = 1; g.arg + z.arg = 0; const double PI = Math.PI; }@*/ } class Resistor extends Branch { /*@ specification Resistor super Branch double r; z.re = r; z.im = 0; }@*/ } class Capacitor extends Branch { /*@ specification Capacitor super Branch { double omega, C; g.re = 0; g.im = omega * C; omega = 2 * PI * f; }@*/ } class Inductor extends Branch { /*@ specification Inductor super Branch double omega, L; z.re = 0; z.im = omega * L; omega = 2 * PI * f; }@*/ }

18. Fragments of circuits class Par extends Branch { /*@ specification Par super Branch { Branch x1, x2; g.re = x1.g.re + x2.g.re; g.im = x1.g.im + x2.g.im; u = x1.u; u = x2.u; f = x1.f; f = x2.f; }@*/ } class Ser extends Branch { /*@ specification Ser super Branch { Branch x1, x2; z.re = x1.z.re + x2.z.re; z.im = x1.z.im + x2.z.im; i = x1.i; i = x2.i; f = x1.f; f = x2.f; }@*/ }

19. A real program component public class Process { /*@ specification Process { double inp, out; void res; double min, step, max; Port port; alias draw = (*.drawing_ready); [ inp -> out, draw ], min, step, max -> res {proc_run}; }@*/ public void proc_run(Subtask st, double start, double step, double finish) { try { for (double i = start; i <= finish; i+=step ) { Object[] out = st.run( new Object[]{i}); } } catch (Exception e) { e.printStackTrace(); } } }

20. The circuits DSL port in out

21. A model

22. Solving a problem

23. Automatic program construction Structural synthesis of programs (SSP) is a way to get programs completely automatically from equations and Java methods. It uses reasonably simple model specifications, where component specifications (si,1si,2…si,ki(Ui,1(si,1)Ui,2(si,2) …Ui,ki(si,ki)  Vi(i(si,1,si,2,…si,ki))) ) 1≤i≤mu1u2…uk(X1(u1)X2(u2) …Xk(uk)  Y(F(u1,u2,…uk, 1, 2,… m))) are represented in a simpler (propositional) form (Ui Vi{i})  (X Y{F})or quite often evenX Y{F} 1≤i≤m See: P. Grigorenko, E. Tyugu. Higher-Order Attribute Semantics of Flat DeclarativeLanguages. Computing and Informatics. v.28, No. 2, 2010; E. Tyugu. Grigori Mints and Computer Science. In: S. Feferman, W. Sieg, V. Kreinovich, V. Lipschitz, Ruy de Queiroz (Eds.) Proofs, Categories and Computations: Essays in honor of Grigori Mints. Dov Gabbay’s College Publications, 2010.

24. Benchmarking of the synthesizer (Y1&G1 A1)  B1, (A1 (B1&G1&Z1))  X1, Y1&X1&U1 A, Z1↔ B2, Y1↔ U2, ... (Yn&Gn An)  Bn, (An (Bn&Gn&Zn))  Xn, Yn&Xn&Un An, Zn-1↔ Bn, Yn-1↔ Un, U1&Zn├ B1; where n >1 P. Grigorenko. Higher-order attribute semantics of flat languages. Ph. D. TUT, 2010.

25. The technology Project ontology (1) Domain engineering Code components (classes) (2) Components (4) Visual rerpesentation (3) Application engineering Specification (scheme or text) (6) Requirements (5) Automatic steps Logical formulae (7) Algorithm (8) Executable code (9)

26. The domain engineering technology • Problem(s) analysis, use cases • Domain analysis: • Domain concepts • Domain ontology, incl. inheritance and part-of relations between the concepts • Problems-related concepts • List of components • Computational content of components.

27. The tool: CoCoViLa CoCoViLa is a software tool for model-based software development with a visual language support that performs automatic synthesis of programs from logical specifications. It is tightly integrated with Java: it is written in Java, uses advanced features of Java, and it supports programming of new software components in Java almost without restrictions. http://www.cs.ioc.ee/cocovila

28. Support of domain and application engineering CoCoViLa consists of two runnables: Class Editor and Scheme Editor. • The Class Editor is a tool for domain engineering, it is used for implementing visual languages for different problem domains. • TheScheme Editor is a tool for application engineering -- drawing schemes, compiling and running programs defined byscheme and a goal.

29. Rich components A component “Boiler”: Boiler.gif B ... .xml Boiler.java BoilerDaemon.java

30. Rich component(metaclass, visual class) Rich component is a description of a domain-specific concept used fordescribing models. It is a class, extended with information needed for automatic usage of theclass, and also for visual handling of instances of the class. It is therefore also called visualclass. A rich component may have four parts: • visual part – its image, pop-up window etc. • specification (a logical part) • program component • daemon (a permanently running thread).

31. Package Package is a collection of rich components and schemes related to an application domain,collected in a package folder and supplied with a package description file in xmlformat. A package supported by the Scheme Editor is an implementation of a domain-specific language.

32. Specification language 1) Declaration of variables type id,id,...; The type is a primitive type, a class, or a metaclass. Examples: int i,step; Boiler b; 2) Binding a = b; Binding is an equality, where a, b are variables. 3) Equation Example: x = 2* y*sin(alpha);

33. Specification language continued 3) Axiom precondition -> variable{name-of-method} Example: x,y -> z{P} This axiom specifies that a method P can be used for calculating z int P(int a, int b) {…} 4) Alias alias name = (list of names); Examples: alias state = (*.state); alias in = (x1, x2);

34. A real application: security exprt system J. Kivimaa, A. Ojamaa, E. Tyugu. Managing Evolving Security Situations. MILCOM 2009: Unclassified Proceedings, October 18-21, 2009, Boston, MA. Piscataway, NJ: IEEE, 2009, 1 - 7.

35. Appliaction: simulation in mechatronics Grosschmidt, G.; Harf, M. (2009). COCO-SIM - Object-oriented Multi-pole Modelling and Simulation Environment for Fluid Power Systems. Part 1: Fundamentals. International Journal of Fluid Power, Vol. 10, No. 2, 2009, pp. 91 - 100. Part 2: Modelling and simulation of hydraulic-mechanical load- sensing system. International Journal of Fluid Power, Vol. 10, No. 3, 2009, pp. 71 - 85

36. Application: composition of services R. Maigre, P. Küngas, M. Matskin, E. Tyugu. Handling Large Web Services Models in a Federated Governmental Information System. Proc. 3-rd International Conference on Internet and Web Applications and Services. IEEE Computer Society & CPS, 2008, p. 626 – 631