![Clusters
IntSet = cluster is create, insert, delete, …
rep = array[int]](https://image.slidesharecdn.com/turing-09-5-100124125910-phpapp02/85/The-power-of-abstraction-32-320.jpg)
![Clusters
IntSet = cluster is create, insert, delete, …
rep = array[int]
create = proc ( ) returns (cvt)
return (rep$create( ))
end create](https://image.slidesharecdn.com/turing-09-5-100124125910-phpapp02/85/The-power-of-abstraction-33-320.jpg)
![Polymorphism
Set = cluster[T: type] is create, insert, …
end Set
Set[int] s := Set[int]$create( )
Set[int]$insert(s, 3)](https://image.slidesharecdn.com/turing-09-5-100124125910-phpapp02/85/The-power-of-abstraction-34-320.jpg)
![Polymorphism
Set = cluster[T: type] is create, insert, …
where T has equal: proctype(T, T)
returns (bool)](https://image.slidesharecdn.com/turing-09-5-100124125910-phpapp02/85/The-power-of-abstraction-35-320.jpg)
![Polymorphism
Set = cluster[T: type] is create, insert, …
where T has equal: proctype(T, T)
returns (bool)
rep = array[T]
insert = proc (x: cvt, e: T)
… if e = x[i] then …](https://image.slidesharecdn.com/turing-09-5-100124125910-phpapp02/85/The-power-of-abstraction-36-320.jpg)
![Exception Handling
choose = proc (x: cvt) returns (T)
signals (empty)
if rep$size() = 0 then signal empty
…
set[T]$ choose(s)
except when empty: …](https://image.slidesharecdn.com/turing-09-5-100124125910-phpapp02/85/The-power-of-abstraction-39-320.jpg)
![Iterators
sum: int := 0
for e: int in Set[int]$members(s) do
sum := sum + e
end](https://image.slidesharecdn.com/turing-09-5-100124125910-phpapp02/85/The-power-of-abstraction-44-320.jpg)
![Iterators
Set = cluster[T] is create, …, members, …
rep = array[T]
members = iter (x: cvt) yields (T)
for z: T in rep$elements(x) do
yield (z) end](https://image.slidesharecdn.com/turing-09-5-100124125910-phpapp02/85/The-power-of-abstraction-45-320.jpg)
The power of abstraction
- 1. The Power of Abstraction Barbara Liskov November 2009
- 2. Outline Inventing abstract data types CLU Type hierarchy What next
- 3. Data Abstraction Prehistory The Venus machine
- 5. Data Abstraction Prehistory The Venus machine The Venus operating system
- 6. Data Abstraction Prehistory The Venus machine The Venus operating system Programming methodology
- 7. Programming Methodology How should programs be designed? How should programs be structured?
- 8. The Landscape E. W. Dijkstra. Go To Statement Considered Harmful. Cacm, Mar. 1968
- 9. The Landscape N. Wirth. Program Development by Stepwise Refinement. Cacm, April 1971
- 10. The Landscape D. L. Parnas. Information Distribution Aspects of Design Methodology. IFIP Congress, 1971 “The connections between modules are the assumptions which the modules make about each other.”
- 11. Partitions B. Liskov. A Design Methodology for Reliable Software Systems. FJCC, Dec. 1972
- 12. Partitions op1 op2 op3 Partition state
- 13. From Partitions to ADTs How can these ideas be applied to building programs?
- 14. Idea Connect partitions to data types
- 15. Meeting in Savanah ACM Sigplan-Sigops interface meeting. April 1973. (Sigplan Notices, Sept. 1973) Started to work with Steve Zilles
- 16. The Landscape Extensible Languages S. Schuman and P. Jourrand. Definition Mechanisms in Extensible Programming Languages. AFIPS. 1967 R. Balzer. Dataless Programming. FJCC 1967
- 17. The Landscape O-J. Dahl and C.A.R. Hoare. Hierarchical Program Structures. Structured Programming, Academic Press, 1972
- 18. The Landscape J. H. Morris. Protection in Programming Languages. Cacm. Jan. 1973
- 19. The Landscape W. Wulf and M. Shaw. Global Variable Considered Harmful. Sigplan Notices. Feb. 1973.
- 20. Abstract Data Types B. Liskov and S. Zilles. Programming with Abstract Data Types. ACM Sigplan Conference on Very High Level Languages. April 1974
- 21. What that paper proposed Abstract data types A set of operations And a set of objects The operations provide the only way to use the objects
- 22. What that paper proposed Abstract data types Clusters with encapsulation Polymorphism Static type checking (we hoped) Exception handling
- 23. From ADTs to CLU Participants Russ Atkinson Craig Schaffert Alan Snyder
- 25. Why a Programming Language? Communicating to programmers Do ADTs work in practice? Getting a precise definition Achieving reasonable performance
- 26. Language Design Goals Expressive power, simplicity, performance, ease of use Minimality Uniformity Safety
- 27. Language Design Restrictions No concurrency No go tos No inheritance
- 28. Some Assumptions/Decisions Heap-based with garbage collection! No block structure! Separate compilation Static type checking
- 29. CLU Mechanisms Clusters Polymorphism Exception handling Iterators
- 30. Clusters IntSet = cluster is create, insert, delete, isIn, … end IntSet
- 31. Clusters IntSet = cluster is create, insert, delete, … end IntSet IntSet s := IntSet$create( ) IntSet$insert(s, 3)
- 32. Clusters IntSet = cluster is create, insert, delete, … rep = array[int]
- 33. Clusters IntSet = cluster is create, insert, delete, … rep = array[int] create = proc ( ) returns (cvt) return (rep$create( )) end create
- 34. Polymorphism Set = cluster[T: type] is create, insert, … end Set Set[int] s := Set[int]$create( ) Set[int]$insert(s, 3)
- 35. Polymorphism Set = cluster[T: type] is create, insert, … where T has equal: proctype(T, T) returns (bool)
- 36. Polymorphism Set = cluster[T: type] is create, insert, … where T has equal: proctype(T, T) returns (bool) rep = array[T] insert = proc (x: cvt, e: T) … if e = x[i] then …
- 37. Exception Handling J. Goodenough. Exception Handling: Issues and a Proposed Notation. Cacm, Dec. 1975 Termination vs. resumption How to specify handlers
- 38. Exception Handling choose = proc (x: cvt) returns (T) signals (empty) if rep$size() = 0 then signal empty …
- 39. Exception Handling choose = proc (x: cvt) returns (T) signals (empty) if rep$size() = 0 then signal empty … set[T]$ choose(s) except when empty: …
- 40. Exception Handling Handling Propagating Shouldn’t happen The failure exception Principles Accurate interfaces Avoid useless code
- 41. Iterators For all x in C do S
- 42. Iterators For all x in C do S Destroy the collection? Complicate the abstraction?
- 43. Visit to CMU Bill Wulf and Mary Shaw, Alphard Generators
- 44. Iterators sum: int := 0 for e: int in Set[int]$members(s) do sum := sum + e end
- 45. Iterators Set = cluster[T] is create, …, members, … rep = array[T] members = iter (x: cvt) yields (T) for z: T in rep$elements(x) do yield (z) end
- 46. After CLU Argus and distributed computing Type Hierarchy
- 47. The Landscape Inheritance was used for: Implementation Type hierarchy
- 48. Implementation Inheritance Violated encapsulation!
- 49. Type hierarchy Wasn’t well understood E.g., stacks vs. queues
- 50. The Liskov Substitution Principle (LSP) Objects of subtypes should behave like those of supertypes if used via supertype methods B. Liskov. Data abstraction and hierarchy. Sigplan notices, May 1988
- 51. Polymorphism where T has … vs. where T subtype of S Proofs happen at different times!
- 52. What Next? Modularity based on abstraction is the way things are done
- 53. Challenges New abstraction mechanisms? Massively Parallel Computers Internet Computer Storage and computation Semantics, reliability, availability, security
- 54. The Power of Abstraction Barbara Liskov October 2009