Software Engineering 2 A practical course in software engineering. Ekkart Kindler

Transcription

1 Software Engineering 2 A practical course in software engineering

2 Conclusion, Outlook, Discussion

3 Motivation 3

4 4

5 1. What did you learn? Objectives of this course: Basic skills in software engineering! 5

6 Software Engineering is much more than programming! listening and understanding! analytic and conceptual work! communication! a social process! acquiring new technologies! a discipline with proven concepts, methods, notations, and tools! and ever new technologies emerging! 6

7 Experience Software Engineering requires much experience! This experience can not be taught theoretically! will be provided in this course! tutorial project and (only) backed by the lectures 7

8 Issues How to make useful UML models Domain model OOA Implementation OOD Learn to use new technologies YOURSELF! Eclipse / Android / openhab / Jenkins / 8

9 Issues Get requirements straight Write a systems specification 9

10 Specifying Software Project Definition Requirements Specification rough detailed Systems specification Complete Models Implementation, Documentation Handbook what how 10

11 Specifying Software Project Definition Requirements Specification rough detailed Systems specification Complete Models Implementation, Documentation Handbook rough detailed 11

12 Specifying Software Project Definition Requirements Specification rough detailed Systems specification Complete Models Implementation, Documentation Handbook low cost high cost 12

13 Issues writing, talking, communicating, and organizing yourself work together version management (other/better tools) 13

14 Issues Quality Management Testing Reviews Many practical issues on programming and solving problems 14

15 Issues Integration and extension Integrating features in existing software (PlugIn Mechanisms, ) Developing parts in parallel (based on a common model) Separating concerns Stepwise extension (prototyping, agile) 15

16 Topics Software Specifications (incl. writing) Modelling & Meta modelling Quality mangament (incl. testing) Code generation Working together Management 16

17 Agile manifesto We are uncovering better ways of developing software by doing it and helping others do it. Through this work we have come to value: Individuals and interactions over processes and tools Working software over comprehensive documentation Customer collaboration over contract negotiation Responding to change over following a plan That is, while there is value in the items on the right, we value the items on the left more. Kent Beck et al

18 Agile Values Communication Simplicity Feedback Courage 18

19 Agile (fundamental) Principals Rapid feedback Assume Simplicity Incremental change Embracing change Quality work 19

20 Agile Practices (overview) On-site customer Small/short releases 2-3 week Planning game Coding standards Testing Continuous integration Pair programming Simple design Refactoring Collective ownership... 20

21 2. What did you not learn? 21

22 Technology issues MOF (Meta Object Facility) Software without Programming (EMF and more) / code generation technologies Other technology: other application servers, cloud, IoT, databases, service technologies, Analyse, validate, verify software, Other programming and modelling paradigms: e.g. Aspect Oriented Modelling... 22

23 Advanced Topics Just to give you some idea

24 Future technologies Modelling dynamic behaviour (and generating code from that) Get completely rid of programming?! Defining transformations 24

25 More details & experience Master courses Requirements Engineering (H.S) Systems integration (H.B.) Web Services (H.B.) Formal methods (A.H.) Advanced topics in SE (B.W.) Bachelor and master projects (last slides) 25

26 Coordinating Interactions The Event Coordination Notation

27 From lecture 1: Example 27

28 From lecture 1: Example From this (EMF) model for Petri nets: Generation of (Java) code for all classes methods for changing the Petri net loading and saving the Petri net as XML files ( XMI) PetriNet * Object 1 source Node 1 target Transition Place Arc * Token With this and some more GMF information: Generation of the Java code of a graphical complete editor (with many fancy features). No programming at all. Transition Place Arc Token 28

29 From lecture 1 PetriNet * Object 1 source Node 1 target Transition Place Arc * Token Manifest-Version: 1.0 Bundle-ManifestVersion: 2 Bundle-Name: %pluginname package PetriNets.impl; Bundle-SymbolicName: APetriNetEditorIn15Minutes.diagr Bundle-Version: qualifier public class PetriNetImpl extends EObjectImpl implements PetriNet { Bundle-ClassPath:. protected EList<PetriNets.Object> object; Bundle-Activator: PetriNets.diagram.part.PetriNetDiagr Bundle-Vendor: %providername protected PetriNetImpl() { Bundle-Localization: plugin super(); Export-Package: PetriNets.diagram.edit.parts, } PetriNets.diagram.part, PetriNets.diagram.providers protected EClass estaticclass() { Require-Bundle: org.eclipse.core.runtime, return PetriNetsPackage.Literals.PETRI_NET; org.eclipse.core.resources, } org.eclipse.core.expressions, org.eclipse.jface, public EList<PetriNets.Object> getobject() { org.eclipse.ui.ide, if (object == null) { org.eclipse.ui.views, object = new EObjectContainmentEList<PetriNets.Object>(Petri org.eclipse.ui.navigator, } org.eclipse.ui.navigator.resources, return object; org.eclipse.emf.ecore, } org.eclipse.emf.ecore.xmi, org.eclipse.emf.edit.ui, public NotificationChain einverseremove(internaleobject otherend, int org.eclipse.gmf.runtime.emf.core, switch (featureid) { org.eclipse.gmf.runtime.emf.commands.core, case PetriNetsPackage.PETRI_NET OBJECT: org.eclipse.gmf.runtime.emf.ui.properties, return ((InternalEList<?>)getObject()).basicRemove(otherEn org.eclipse.gmf.runtime.diagram.ui, } org.eclipse.gmf.runtime.diagram.ui.properties, return super.einverseremove(otherend, featureid, msgs); org.eclipse.gmf.runtime.diagram.ui.providers, } org.eclipse.gmf.runtime.diagram.ui.providers.ide, org.eclipse.gmf.runtime.diagram.ui.render, public Object eget(int featureid, boolean resolve, boolean coretype) { org.eclipse.gmf.runtime.diagram.ui.resources.ed switch (featureid) { org.eclipse.gmf.runtime.diagram.ui.resources.e case PetriNetsPackage.PETRI_NET OBJECT: APetriNetEditorIn15Minutes;visibility:=reexpor return getobject(); } return super.eget(featureid, resolve, coretype); Analysis Design Implementation Coding 29

30 e.g. a Petri net simulator? 30

31 2. The Event Coordination Notation Motivation Given some object oriented software with (or without) explicit domain model Model behaviour on top of it and make these models executable Model behaviour on a high level of abstraction (domain): coordination of behaviour Integrate behaviour models with structural models Integrate different structural models and manually written code (or code generated by different technologies) 31

32 2.1 Example: Vending machine Coin * * Slot Brewer Safe 1 * Control * * Output Panel * Coffee Tea 32

33 Instance: Object Diagram :Coin :Coin : Slot :Coffee :Coin : Safe :Control :Coffee :Output :Panel :Tea 33

34 Coordination Diagram GUI Coin insert GUI pass return_ Safe pass return_: ALL pass: 1 * * insert: 1 1 pass: 1 Slot insert return_ pass reset Panel GUI coffee GUI tea GUI cancel GUI reset: ALL pass: 1 * * coffee: 1 tea: 1 cancel: ALL Control coffee tea cancel pass reset coffee: 1 tea: 1 reset: ALL * Coffee Brewer coffee tea reset cup_in cup_in: 1 * Tea Output GUI cup_in GUI cup_out GUI 34

35 ... + Event declaration GUI Coin insert GUI pass return_ Safe pass return_: ALL pass: 1 * * insert: 1 1 pass: 1 Slot insert return_ pass reset Panel GUI coffee GUI tea GUI cancel GUI reset: ALL pass: 1 * * coffee: 1 tea: 1 cancel: ALL Control coffee tea cancel pass reset insert(coin coin, Slot slot) pass(coin coin, Slot slot) return(slot slot) reset_() coffee: 1 tea: 1 reset: ALL * Coffee Brewer coffee tea reset cup_in cup_in: 1 * Tea coffee() tea() cancel() cup_in() cup_out() Output GUI cup_in GUI cup_out GUI 35

36 Interactions :Coin :Coin :Coin pass : Safe pass pass: 1 pass: 1 : Slot pass :Panel coffee pass: 1 coffee: 1 :Control pass coffee coffee: 1 coffee: 1 :Coffee :Coffee coffee :Tea :Output 36

37 Interactions :Coin :Coin :Coin pass : Safe pass pass: 1 pass: 1 : Slot pass :Panel coffee pass: 1 coffee: 1 :Control pass coffee coffee: 1 :Coffee :Coffee coffee :Tea :Output 37

38 Another Interaction :Coin return :Coin :Coin return : Safe return: ALL return: ALL : Slot return reset :Panel cancel reset: ALL cancel: ALL :Control reset cancel reset: ALL reset: ALL reset: ALL :Coffee reset :Coffee reset :Tea reset :Output 38

39 Local behaviour: Coffee 39

40 Local behaviour: Coin 40

41 Local behaviour: Control pass coffee reset cancel 41

42 Local behaviour: Slot return reset 42

43 Interactions :Coin return :Coin :Coin return : Safe return: ALL return: ALL : Slot return reset :Panel cancel reset: ALL cancel: ALL :Control reset cancel reset: ALL reset: ALL reset: ALL :Coffee reset :Coffee reset :Tea reset :Output 43

44 2.2 ECNO: Basic Concepts ElementTypes (Classes) EventTypes with parameters insert(coin coin, Slot slot) Global Behaviour: Coordination annotations for references Event type Quantification (1 or ALL) Local behaviour: ECNO nets (or something else) Event binding (with parameter assignment) Condition Action Control coffee tea cancel pass reset coffee: 1 tea: 1 Brewer reset: ALL coffee tea reset cup_in 44

45 2.3 Extensions ECNO with its basic concepts has some limitations, which makes modelling things in an adequate way a bit painful. Sometimes, we want to extend event types later 45

46 Event Extension tea tea_blend tea_temp 46

47 2.4 Example2: Petri nets t remove add Transition t enabled: for ALL incoming Arcs a: for ONE source Place p of Arc a: find a token Fire Transition t: for ALL incoming Arcs a: for ONE source Place p of Arc a: find a token and remove it for ALL outgoing arcs a: for ONE target Place p of Arc a: add a new Token 47

48 Petri net: Abstract Syntax 48

49 Example2: Petri nets t remove add Transition t enabled: for ALL incoming Arcs a: for ONE source Place p of Arc a: find a token Fire Transition t: for ALL incoming Arcs a: for ONE source Place p of Arc a: find a token and remove it for ALL outgoing arcs a: for ONE target Place p of Arc a: add a new Token 49

50 ECNO Semantics of PN 50

51 Result t4 t1 t3 t2 51

52 Petri net simulator 52

53 3. Conclusion 53

54 Next Steps 54

55 MSc and BSc Projects

56 Topics / areas OpenHAB & CITIES equipping an experimental room at DTU with devices controlled by openhab equipping a school with devices for well-being collecting, analysing and visualizing data Flexible, configurable and generic data collection from all kinds of devices (e.g. Fitbit) health care energy science (SE-research) CITIES 56

57 ECNO Behaviour modelling: ECNO :Coin return :Coin :Coin return : Safe return: ALL return: ALL : Slot return reset :Panel cancel reset: ALL cancel: ALL :Control reset cancel reset: ALL reset: ALL reset: ALL :Coffee reset :Coffee reset :Tea reset :Output 57

58 ECNO Tool 58

59 ECNO Projects Improved IDE Integration & debugging Smooth database integration (cntd.) Case studies / larger examples (e.g. games) Semantics of ECNO in ECNO 59

60 epnk 60

61 Define a Petri Net Type Defining a new PN by a model? 61

62 Projects Usability, IDE integration and visualization A generic simulator and state space analysis tool... 62

63 Other topics Analysis and design of lighting in buildings Model-based Software Engineering Domain Specific Languages (DSL) Automating the SE process Tools support for development process 63

64 Internet of Things Lab: Setting up the smart home of the future Build a home automation system for heating, cooling and ventilation control

65 Goal of this Thesis Set up a smart home IoT lab Compare different monitoring technologies Compare actuators from different brands Integrate sensors and actuators into openhab Install and run: A gateway (Raspberry Pi) A Time Series Data Base (InfluxDB) A Data Analysis and Visualization software (Grafana) Providing an interface for model predictive control algorithms (Python, R) Providing an interface for building energy performance simulation software (Modelica, Dymola, IDA ice) 65

66 Set up of the IoT Lab Set up a IoT Lab, including (at least): Indoor Air Sensors: Temperature Relative Humidity CO2 Noise A Weather Station: Temperature Relative Humidity Actuators Smart Thermostatic Valves A Gateway 66