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1 - OOP

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1 - OOP

  1. 1. S.Ducasse 1 Stéphane Ducasse Stephane.Ducasse@univ-savoie.fr http://www.listic.univ-savoie.fr/~ducasse/ Object-Oriented Programming
  2. 2. S.Ducasse 2 License: CC-Attribution-ShareAlike 2.0 http://creativecommons.org/licenses/by-sa/2.0/
  3. 3. S.Ducasse 3 Outline • Context: Software MUST evolve • OOP Modeling • Objects • Classes • Inheritance
  4. 4. S.Ducasse 4 Continuous Development 17.4% Corrective (fixing reported errors) 18.2% Adaptive (new platforms or OS) 60.3% Perfective (new functionality) The bulk of the maintenance cost is due to new functionality ⇒even with better requirements, it is hard to predict new functions data from [Lien78a] 4.1% Other Relative Maintenance Effort Between 50% and 75% of global effort is spent on “maintenance” !
  5. 5. S.Ducasse 5 Lehman's Laws A classic study by Lehman and Belady [Lehm85a] identified several “laws” of system change. Continuing change A program that is used in a real-world environment must change, or become progressively less useful in that environment. Increasing complexity As a program evolves, it becomes more complex, and extra resources are needed to preserve and simplify its structure. Those laws are still applicable to brand new object-oriented applications 5
  6. 6. S.Ducasse 6 Software is living… • Early decisions may have been good at that time • But the context changes • Customers change • Technology changes • People change • Successful software MUST evolve
  7. 7. S.Ducasse 7 The Old Way • Computer system consists of data and programs. • Programs manipulate data. • Programs organized by • functional decomposition • dataflow • modules
  8. 8. S.Ducasse 8 OOP • Computer system consists of a set of objects. • Objects are responsible for knowing and doing certain things. • Objects collaborate to carry out their responsibilities. • Programs organized by classes, inheritance hierarchies and subsystems
  9. 9. S.Ducasse 9 Accidental vs. Essential Complexity • Assembly is perfect to write 8k programs! • But we need abstraction tools to model the complexity of the world • Object-oriented programming in only one way • Reactive languages, • Relational languages, • Logic Languages, … are others • OOP helps reducing the accidental complexity not the essential • Bad OO programs are also difficult to understand, extend, and maintain
  10. 10. S.Ducasse 10 Outline • Context: Software MUST evolve • OOP Modeling • Objects • Classes • Inheritance
  11. 11. S.Ducasse 11 What is an object, anyway? Programming language view An object-oriented system is characterized by data abstraction inheritance polymorphism by late-binding of procedure calls
  12. 12. S.Ducasse 12 Modeling All phases of software life-cycle are modeling analysis - modeling of problem design - modeling of solution implementation - making model run on a computer maintenance - fixing/extending your model
  13. 13. S.Ducasse 13 Modeling Claim: people model the world with "objects" objects and classes relationships between objects relationships between classes Advantages of object-oriented software development more natural - matches the way people think single notation - makes it easy to move between software phases
  14. 14. S.Ducasse 14 Objects and Relationships John is Mary's father. Mary is John's daughter. Bob is Mary's dog. Mary is Bob's owner. Ann is John's employer. John is Ann's employee.
  15. 15. S.Ducasse 15 Objects and Attributes John's name is "John Patrick O'Brian". John's age is 27. John's address is 987 N. Oak St, Champaign IL 61820 What about John's employer? John's wife? What is an attribute, and what is a relationship?
  16. 16. S.Ducasse 16 Objects and Behavior John goes on a trip. John makes reservations. John buys tickets. John travels by airplane. John checks into hotel.
  17. 17. S.Ducasse 17 What is really an object? • Anything we can talk about can be an object, including relationships ("the husband of the first party", "first- born son"). • What are we trying to model? • “Models should be as simple as possible, but no simpler”. • Models are dictated by domains
  18. 18. S.Ducasse 18 Some Examples • Things that we can manipulate or see: Book, BD • Things that we can conceptually see: Process, Mortgage, InsuranceContract, Socket, • Rôles: Mother,Teacher, • Drivers,Algorithms • Events and transactions • Library elements: Color,Window,Text, Dictionary, Date, Boolean.... • Organizations, processes
  19. 19. S.Ducasse 19 RoadMap • Context: Software MUST evolve • OOP Modeling • Objects • Classes • Inheritance
  20. 20. S.Ducasse 20 State + Behavior + Identity
  21. 21. S.Ducasse 21 State + Behavior + Identity • State: Objects it contains or refers to • Ex: point location • Behavior: an object understands a given set of messages • Identity: an object can be the same (of the same class) than another one but it has still a different identity (location in memory)
  22. 22. S.Ducasse 22 Object Data Messages Methods
  23. 23. S.Ducasse 23 • What: Messages – Specify what behavior objects are to perform – Details of how are left up to the receiver – State information only accessed via messages • How: Methods – Specify how operation is to be performed – Must have access to (contain or be passed) data – Need detailed knowledge of data – Can manipulate data directly Behavior + State + Control Data Methods Messages
  24. 24. S.Ducasse 24 Equality and Identity • I want to eat the pizza that you are eating • Equality: I want to eat the “same” kind of pizza • Identity: I eat your pizza
  25. 25. S.Ducasse 25 Encapsulation
  26. 26. S.Ducasse 26 Encapsulation • Object protects its data • We cannot access private data • Object protects its implementation choice • Clients use a public interface • Object can change its implementation
  27. 27. S.Ducasse 27 Object Summary Objects have an identity have attributes have behavior have relationships with other objects Objects protect their data offer services, protect their implementation
  28. 28. S.Ducasse 28 Roadmap • Context: Software MUST evolve • OOP Modeling • Objects • Classes • Inheritance
  29. 29. S.Ducasse 29 Classification • We naturally put objects into classes that have similar characteristics. • John is a man. • Mary is a woman. • Bob is a dog. • All women are people. • All people are mammals.
  30. 30. S.Ducasse 30 A Class generates Instances
  31. 31. S.Ducasse 31 Classes: Factory of Objects • Reuse behavior => Factor into class • Class:“Factory” object for creating new objects of the same kind • Template for objects that share common characteristics
  32. 32. S.Ducasse 32 Class: Mold of Objects • **Describe** state but not effective values of all the instances of the class – Position, width and length for rectangles • **Define** behavior of all instances of the class Rectangle>>area ^ width * height
  33. 33. S.Ducasse 33 Instances • A particular occurrence of an object defined by a class • Each instance has its own value for the instance variables • All instances of a class share the same methods 400@10 100 20 300@20 10 140
  34. 34. S.Ducasse 34 An example • Let’s control robots.... • http://smallwiki.unibe.ch/botsinc/
  35. 35. S.Ducasse 35 Instances Creation • Asking a class to create an instance • The Bot factory creates a new robot
  36. 36. S.Ducasse 36 Instance Interaction • We send messages to individual robots too
  37. 37. S.Ducasse 37 Instances are autonomous...
  38. 38. S.Ducasse 38 Instances vs. Classes • The class Bot does not understand go: 100 • The class Bot understand new to create new robots • aBot does not understand new • aBot understands robot messages such as turn:, go:, jump:, turnLeft:, color, lookLikeTriangle
  39. 39. S.Ducasse 39 Roadmap • Context: Software MUST evolve • OOP Modeling • Objects • Classes • Inheritance
  40. 40. S.Ducasse 40 How to Share Specification? • Do not want to rewrite everything! • Often times want small changes • Man are a specialization of People • OOP language offers inheritance to reuse or specialize classes • Class hierarchies for sharing of definitions • Each class defines or refines the definition of its ancestors
  41. 41. S.Ducasse 41 Inheritance • New classes • Can add state and behavior (ColoredRectangle) • Can specialize ancestor behavior (GoldenRectangle) • Can use ancestor’s behavior and state • Can hide ancestor’s behavior • Direct ancestor = superclass • Direct descendant = subclass
  42. 42. S.Ducasse 42 Comparable Quantity Hierarchy
  43. 43. S.Ducasse 43 Summary • Classes • **Describes** the attributes, and relationships of a set of objects • Define the behavior of a set of objects • Reuse, extend, specialize behavior from other classes • Subclasses/superclasses form graph of generalizations
  44. 44. S.Ducasse 44 Summary An object has a state, a behavior and a unique identity. The structure and behavior of similar objects is shared in their class Instances of a class and objects are terms that cn be exchanged Classes as organized in generalisation/specialisation hierarchy What is an instance? What is the difference between instantiation and inheritance?

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