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CSEP505: Programming Languages
Lecture 9: Finish Concurrency; Start OOP
Dan Grossman
Winter 2009
Where are we
• Thread creation
• Communication via shared memory
– Synchronization with join, locks
• Message passing a la Concurrent ML
– Very elegant
– First done for Standard ML, but available in several
functional languages
– Can wrap synchronization abstractions to make new ones
– In my opinion, quite under-appreciated
• Back to shared memory for software transactions
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CSE P505 Winter 2009 Dan Grossman
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The basics
(* event.mli; Caml’s version of CML *)
type ’a channel (* messages passed on channels *)
val new_channel : unit -> ’a channel
type ’a event
val send
:
val receive :
val sync
:
(* when sync’ed on, get an ’a *)
’a channel -> ’a -> unit event
’a channel -> ’a event
’a event -> ’a
• Send and receive return “events” immediately
• Sync blocks until “the event happens”
• Separating these is key in a few slides
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Simple version
Helper functions to define blocking sending/receiving
• Message sent when 1 thread sends, another receives
• One will block waiting for the other
let sendNow ch a = sync (send ch a) (* block *)
let recvNow ch = sync (receive ch) (* block *)
Note: In SML, the CML book, etc:
send
= sendEvt
receive = recvEvt
sendNow = send
recvNow = recv
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Example
Make a thread to handle changes to a bank account
• mkAcct returns 2 channels for talking to the thread
• More elegant/functional approach: loop-carried state
type action = Put of float | Get of float
type acct = action channel * float channel
let mkAcct () =
let inCh = new_channel() in
let outCh = new_channel() in
let bal
= ref 0.0
in (* state *)
let rec loop () =
(match recvNow inCh with (* blocks *)
Put f -> bal := !bal +. f;
| Get f -> bal := !bal -. f);(*allows overdraw*)
sendNow outCh !bal; loop ()
in Thread.create loop (); (inCh,outCh)
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CSE P505 Winter 2009 Dan Grossman
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Example, continued
get and put functions use the channels
let get acct f =
let inCh,outCh =
sendNow inCh (Get
let put acct f =
let inCh,outCh =
sendNow inCh (Put
acct in
f); recvNow outCh
acct in
f); recvNow outCh
Outside the module, don’t see threads or channels!!
– Cannot break the communication protocol
type acct
val mkAcct : unit -> acct
val get : acct->float->float
val put : acct->float->float
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CSE P505 Winter 2009 Dan Grossman
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Key points
• We put the entire communication protocol behind an abstraction
• The infinite-loop-as-server idiom works well
– And naturally prevents races
– Multiple requests implicitly queued by CML implementation
• Don’t think of threads like you’re used to
– “Very lightweight”
• Asynchronous = spawn a thread to do synchronous
– System should easily support 100,000 threads
– Cost about as much space as an object plus “current stack”
• Quite similar to “actors” in OOP
– Cost no time when blocked on a channel
– Real example: A GUI where each widget is a thread
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Simpler example
• A stream is an infinite set of values
– Don’t compute them until asked
– Again we could hide the channels and thread
let squares = new_channel()
let rec loop i =
sendNow squares (i*i);
loop (i+1)
let _ = Thread.create loop 1
let one = recvNow squares
let four = recvNow squares
let nine = recvNow squares
…
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So far
• sendNow and recvNow allow synchronous message passing
• Abstraction lets us hide concurrency behind interfaces
• But these block until the rendezvous, which is insufficient for
many important communication patterns
• Example: add : int channel -> int channel -> int
– Must choose which to receive first; hurting performance or
causing deadlock if other is ready earlier
• Example: or : bool channel -> bool channel -> bool
– Cannot short-circuit
• This is why we split out sync and have other primitives
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The cool stuff
type ’a event
val send
:
val receive :
val sync
:
val choose
val wrap
(* when sync’ed on, get an ’a *)
’a channel -> ’a -> unit event
’a channel -> ’a event
’a event -> ’a
: ’a event list -> ’a event
: ’a event -> (’a -> ’b) -> ’b event
• choose: when synchronized on, block until 1 of the events occurs
• wrap: An event with the function as post-processing
– Can wrap as many times as you want
• Note: Skipping a couple other key primitives (e.g., for timeouts)
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“And from or”
• Choose seems great for “until one happens”
• But a little coding trick gets you “until all happen”
• Code below returns answer on a third channel
let add in1 in2 out =
let ans = sync(choose[
wrap (receive in1)
(fun i -> sync (receive in2) + i);
wrap (receive in2)
(fun i -> sync (receive in1) + i)])
in
sync (send out ans)
• 1st hw5 problem a more straightforward use of choose/wrap
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Another example
let or in1 in2 =
let ans = sync(choose[
wrap (receive in1)
(fun b -> b || sync (receive in2));
wrap (receive in2)
(fun b -> b || sync (receive in1))])
in
sync (send out ans)
• Not blocking in the case of inclusive or would take a little more
cleverness
– Spawn a thread to receive the second input (and ignore it)
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Circuits
If you’re an electrical engineer:
• send and receive are ends of a gate
• wrap is combinational logic connected to a gate
• choose is a multiplexer (no control over which)
So after you wire something up, you sync to say “wait for
communication from the outside”
And the abstract interfaces are related to circuits composing
If you’re a UNIX hacker:
• UNIX select is “sync of choose”
• A pain that they can’t be separated – want to nest chooses
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Remaining comments
• The ability to build bigger events from smaller ones is very
powerful
• Synchronous message passing, well, synchronizes
• Key by-design limitation is that CML supports only point-to-point
communication
• By the way, Caml’s implementation of CML itself is in terms of
queues and locks
– Works okay on a uniprocessor
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Where are we
• Thread creation
• Communication via shared memory
– Synchronization with join, locks
• Message passing a la Concurrent ML
• Back to shared memory for software transactions
– And an important digression to memory-consistency models
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Atomic
An easier-to-use and harder-to-implement primitive
void deposit(int x){
synchronized(this){
int tmp = balance;
tmp += x;
balance = tmp;
}}
void deposit(int x){
atomic {
int tmp = balance;
tmp += x;
balance = tmp;
}}
lock acquire/release
(behave as if)
no interleaved computation
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Syntax irrelevant / Versus TM
• In a language with higher-order functions, no need for a new
statement form
– atomic : (unit -> ‘a) -> ‘a
– “Just a library” to the parser/type-checker
– But not just a library to the compiler and run-time system
• Atomic blocks vs. transactional memory (TM)
– One high-level language construct vs. one way to implement
– Neither necessarily needs the other (though common)
– TM: Start, sequence of r/w, end
• Implicit conflict detection, abort, restart, atomic commit
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Viewpoints
Software transactions good for:
• Software engineering (easier to avoid races & deadlocks)
• Performance (optimistic “no conflict” without locks)
Why are they good:
• Get parallelism unless there are actual run-time memory conflicts
– As easy as coarse-grained locks but parallelism of fine-grained
• Push to language implementation conflict detection/recovery
– Much like garbage collection: convenient but has costs
Shameless plug: The Transactional Memory / Garbage
Collection Analogy (OOPSLA 07)
• Hope to talk about at end of next week, time permitting
– TM-based implementations super cool, but not this course
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Solving “tough” problems
synchronized length() {…}
synchronized getChars(…) {…}
synchronized append(StringBuffer sb) {
int len = sb.length();
if(this.count + len > this.value.length)
this.expand(…);
sb.getChars(0,len,this.value,this.count);
…
}
• Trivial to write append correctly in an atomic world
– Even if previous version didn’t “expect” an append method
– And get all the parallelism you can reasonably expect
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Another tough problem
Operations on a double-ended queue
void enqueue_left(Object)
void enqueue_right(Object)
Object dequeue_left()
Object dequeue_right()
Correctness
– Behave like a queue, even when ≤ 2 elements
– Dequeuers wait if necessary, but can’t “get lost”
Parallelism
– Access both ends in parallel, except when ≤ 1 elements
(because ends overlap)
Example thanks to Maurice Herlihy
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Good luck with that…
• One lock?
– No parallelism
• Locks at each end?
– Deadlock potential
– Gets very complicated, etc.
• Waking blocked dequeuers?
– Harder than it looks
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Actual Solution
• A clean solution to this apparent “homework problem” would be
a publishable result(!)
– In fact it was: [Michael & Scott, PODC 96]
• So locks and condition variables are not a “natural methodology”
for this problem
• Implementation with transactions is trivial
– Wrap 4 operations written sequentially in atomic
• With retry for dequeuing from empty queue
– Correct and parallel
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Not a panacea
• Over-sellers say barely-technically-accurate things like
“deadlock is impossible”
– Really…
class Lock {
bool b = false;
void acquire() {
while(true) {
while(b) /*spin*/;
atomic {
if(b) continue;
b = true;
return; }
}
}
void release() {
b = false;
}
}
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Not a panacea
Problems “we’re workin’ on”
• Abort/retry interacts poorly with “launch missiles”
• Many software TM implementations provide a weaker and
under-specificed semantics when there are transactional/nontransactional data races (a long and crucial story)
• Memory-consistency model questions remain and may be
worse than with locks…
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Memory models
• A memory-consistency model (or just memory model) for a
shared-memory language specifies “what write(s) a read can see.”
• The gold standard is sequential consistency (Lamport):
“the results of any execution is the same as if the operations
of all the processors were executed in some sequential order,
and the operations of each individual process appear in this
sequences in the order specified by its program”
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Abusing SC
Assuming sequential consistency (SC), assert below cannot fail
– Despite data races
initially x=0, y=0
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x = 1;
r = y;
y = 1;
s = x;
assert(s>=r);
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You don’t get SC
• Modern imperative and OO languages do not promise SC
– (If they say anything at all)
– The hardware makes it prohibitively expensive
– Renders unsound almost every compiler optimization
• Example: common-subexpression elimination
initially a=0, b=0
x = a+b;
y = a;
z = a+b;
assert(z>=y);
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b = 1;
a = 1;
CSE P505 Winter 2009 Dan Grossman
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Relaxed != Nothing
• But (especially in a safe language), have to promise something
– When is code “correctly synchronized”?
– What can the implementation do if the code is not “correctly
synchronized”?
• The definitions are very complicated and programmers can
usually ignore them, but do not assume SC
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Real languages
• Java: If every sequentially consistent execution of program P is
data-race free, then every execution of program P is equivalent
to some sequentially consistent execution
– Not the definition; a theorem about the definition
– Actual definition balances need of programmers, compilers,
and hardware
• Not defined in terms of “allowed optimizations”
• Even bad code can’t corrupt the SecurityManager
• C++ (proposed): Roughly, any data race is as undefined as an
array-bounds error. No such thing as a benign data race and no
guarantees if you have one. (In practice, programmers will
assume things, like they do with casts.)
• Many other languages: Eerie silence
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Synchronization and ordering
• In relaxed memory models, synchronization operations typically
impose ordering constraints
– Example: this code cannot violate the assertion
initially x=0, y=0
x = 1;
sync(lk){}
y = 1;
r = y;
sync(lk){}
s = x;
assert(s>=r);
• Recent research papers on what ordering constraints atomic
blocks impose
– Is an empty atomic block a no-op?
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Onto OOP
Now let’s talk about object-oriented programming
• What’s different from what we have been doing
– Boils down to one important thing
• How do we define it (will stay informal)
• Supporting extensibility
• Several other “advanced” topics
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OOP the sales pitch
OOP lets you:
1. Build extensible software concisely
2. Exploit an intuitive analogy between interaction of physical
entities and interaction of software pieces
It also:
• Raises tricky semantic and style issues that require careful
investigation
• Is more complicated than functions
– Does not necessarily mean it’s worse
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So what is it?
OOP “looks like this”, but what is the essence
class Pt1 extends Object {
int x;
int get_x() { x }
unit set_x(int y) { self.x = y }
int distance(Pt1 p) { p.get_x() – self.get_x() }
constructor() { x = 0 }
}
class Pt2 extends Pt1 {
int y;
int get_y() { y }
int get_x() { 34 + super.get_x() }
constructor() { super(); y = 0 }
}
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Class-based OOP
In (pure) class-based OOP:
1. Everything is an object
2. Objects communicate via message (handled by methods)
3. Objects have their own state
4. Every object is an instance of a class
5. A class describes its instances’ behavior
Why is this approach such a popular way to structure software?...
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OOP can mean many things
• An ADT (private fields)
• Inheritance: method/field extension, method override
• Implicit self/this
• Dynamic dispatch
• Subtyping
• All the above in one (class) definition
Design question: Better to have small orthogonal features or one
“do it all” feature?
Anyway, let’s consider how “unique to OO” each is…
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OO for ADTs
Object/class members (fields, methods, constructors) often have
visibilities
What code can invoke a member/access a field?
• Methods of the same object?
• Methods defined in same class?
• Methods defined in a subclass?
• Methods in another “boundary” (package, assembly, friend, …)
• Methods defined anywhere?
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Subtyping for hiding
• As seen before, can use upcasts to “hide” members
– Modulo downcasts
– Modulo binary-method problems
• With just classes, upcasting is limited
• With interfaces, can be more selective
interface I { int distance(Pt1 p); }
class Pt1 extends Object {
…
I f() { self }
…
}
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Records of functions
If OOP = functions + private state, we already have it
– But it’s more (e.g., inheritance)
type pt1 = {get_x
: unit -> int;
set_x
: int -> unit;
distance : pt1 -> int}
let pt1_constructor () =
let x = ref 0 in
let rec self = {
get_x
= (fun() -> !x);
set_x
= (fun y -> x := y);
distance = (fun p -> p.get_x() +self.get_x())
} in
self
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Subtyping
Most class-based OO languages purposely “confuse” classes & types
• If C is a class, then C is a type
• If C extends D (via declaration) then C ≤ D
• Subtyping is reflexive and transitive
Novel subtyping?
• New members in C just width subtyping
• “Nominal” (by name) instead of structural
• What about override…
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Subtyping, continued
• If C extends D, overriding m, what do we need:
– Arguments contravariant (assume less)
– Result covariant (provide more)
• Many “real” languages are more restrictive
– Often in favor of static overloading
• Some languages try to be more flexible
– At expense of run-time checks/casts
Good we studied this in a simpler setting
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Inheritance & override
Subclasses:
• inherit superclass’s members
• can override methods
• can use super calls
Can we code this up in Caml?
• No because of field-name reuse and lack of subtyping
– But ignoring that we can get close…
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Almost OOP?
let pt1_constructor () =
let x = ref 0 in
let rec self = {
get_x
= (fun() -> !x);
set_x
= (fun y -> x := y);
distance = (fun p -> p.get_x()+self.get_x())
} in self
(* note: field reuse precludes type-checking *)
let pt2_constructor () = (* extends Pt1 *)
let r = pt1_constructor () in
let y = ref 0 in
let rec self = {
get_x
= (fun() -> 34 + r.get_x());
set_x
= r.set_x;
distance = r.distance;
get_y
= (fun() -> !y);
} in self
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Problems
Small problems:
• Have to change pt2_constructor whenever
pt1_constructor changes
• But OOPs have tons of “fragile base class” issues too
– Motivates C#’s version support
• No direct access to “private fields” of superclass
Big problem:
• Distance method in a pt2 doesn’t behave how it does in OOP
• We do not have late-binding of self (i.e., dynamic dispatch)
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The essence
Claim: Class-based objects are:
• So-so ADTs
• Same-old record and function subtyping
• Some syntactic sugar for extension and override
• A fundamentally different rule for what self maps to in the
environment
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More on late-binding
Late-binding, dynamic-dispatch, and open-recursion all related
issues (nearly synonyms)
Simplest example I know:
let c1 () =
let rec r = {
even = (fun i -> i=0 || r.odd (i-1));
odd = (fun i -> i<>0 && r.even (i-1))
} in r
let c2 () =
let r1 = c1() in
let rec r = {
even = r1.even; (* still O(n) *)
odd = (fun i -> i % 2 == 1)
} in r
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CSE P505 Winter 2009 Dan Grossman
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More on late-binding
Late-binding, dynamic-dispatch, and open-recursion all related
issues (nearly synonyms)
Simples example I know:
class C1 {
int even(int i) { i=0 || odd (i-1)) }
int odd(int i) { i!=0 && even (i-1)) }
}
class C2 {
/* even is now O(1) */
int odd(int i) {i % 2 == 1}
}
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The big debate
Open recursion:
• Code reuse: improve even by just changing odd
• Superclass has to do less extensibility planning
Closed recursion:
• Code abuse: break even by just breaking odd
• Superclass has to do more abstraction planning
Reality: Both have proved very useful; should probably just argue
over “the right default”
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Our plan
• Dynamic dispatch is the essence of OOP
• How can we define/implement dynamic dispatch?
– Basics, not super-optimized versions (see P501)
• How do we use/misuse overriding?
• Why are subtyping and subclassing separate concepts worth
keeping separate?
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Defining dispatch
Methods “compile down” to functions taking self as an extra
argument
– Just need self bound to “the right thing”
Approach #1:
• Each object has 1 “code pointer” per method
• For new C() where C extends D:
– Start with code pointers for D (recursive definition!)
– If C adds m, add code pointer for m
– If C overrides m, change code pointer for m
• self bound to the (whole) object in method body
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Defining dispatch
Methods “compile down” to functions taking self as an extra
argument
– Just need self bound to “the right thing”
Approach #2:
• Each object has 1 run-time tag
• For new C() where C extends D:
– Tag is C
• self bound to the object
• Method call to m reads tag, looks up (tag,m) in a global table
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Which approach?
• The two approaches are very similar
– Just trade space for time via indirection
• vtable pointers are a fast encoding of approach #2
• This “definition” is low-level, but with overriding simpler models
are probably wrong
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Our plan
• Dynamic dispatch is the essence of OOP
• How can we define/implement dynamic dispatch?
– Basics, not super-optimized versions (see P501)
• How do we use/misuse overriding?
– Functional vs. OO extensibility
• Why are subtyping and subclassing separate concepts worth
keeping separate?
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Overriding and hierarchy design
• Subclass writer decides what to override to modify behavior
– Often-claimed, unchecked style issue: overriding should
specialize behavior
• But superclass writer typically knows what will be overridden
• Leads to notion of abstract methods (must-override)
– Classes w/ abstract methods can’t be instantiated
– Does not add expressiveness
– Adds a static check
– C++ calls this “pure virtual”
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Overriding for extensibility
class Exp { // a PL example; constructors omitted
abstract Exp interp(Env);
abstract Typ typecheck(Ctxt);
abstract Int toInt();
}
class IntExp extends Exp {
Int i;
Value interp(Env e) { self }
Typ typecheck(Ctxt c) { new IntTyp() }
Int toInt() { i }
}
class AddExp extends Exp {
Exp e1; Exp e2;
Value interp(Env e) {
new IntExp(e1.interp(e).toInt().add(
e2.interp(e).toInt())) }
Int toInt() { throw new BadCall() }
// typecheck on next page
}
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Example cont’d
• We did addition with “pure objects”
– Int has a binary add method
• To do AddExp::typecheck the same way, assume equals is
defined appropriately (structural on Typ):
Type typecheck(Ctxt c) {
e1.typecheck(c).equals(new IntTyp()).ifThenElse(
e2.typecheck(c).equals(new IntTyp()).ifThenElse(
(fun () -> new IntTyp()),
(fun () -> throw new TypeError())),
(fun () -> throw new TypeError()))
}
• Pure “OOP” avoids instanceof IntTyp and if-statements
– (see Smalltalk for syntactic sugar)
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More extension
• Now suppose we want MultExp
– No change to existing code, unlike ML!
– In ML, can “prepare” with “Else of ‘a” constructor
• Now suppose we want a toString method
– Must change all existing classes, unlike ML!
– In OOP, can “prepare” with a “Visitor pattern”
• Extensibility has many dimensions – most require forethought!
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The Grid
• You know it’s an important idea if I take the time to draw a
picture 
interp
typecheck
toString
…
IntExp
Code
Code
Code
Code
AddExp
Code
Code
Code
Code
MultExp
Code
Code
Code
Code
1 new class
…
Code
Code
Code
Code
1 new function
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Back to MultExp
• Even in OOP, MultExp is easy to add, but you’ll copy the
typecheck method of AddExp
• Or maybe AddExp extends MultExp, but it’s a kludge
• Or maybe refactor into BinaryExp with subclasses AddExp
and MultExp
– So much for not changing existing code
– Awfully heavyweight approach to a helper function
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Our plan
• Dynamic dispatch is the essence of OOP
• How can we define/implement dynamic dispatch?
– Basics, not super-optimized versions (see P501)
• How do we use/misuse overriding?
– Functional vs. OO extensibility
• Why are subtyping and subclassing separate concepts worth
keeping separate?
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Subtyping vs. subclassing
• Often convenient confusion: C a subtype of D if and only if C a
subclass of D
• But more subtypes are sound
– If A has every field and method that B has (at appropriate
types), then subsume B to A
– Interfaces help, but require explicit annotation
• And fewer subtypes could allow more code reuse…
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Non-subtyping example
Pt2 ≤ Pt1 is unsound here:
class Pt1 extends Object {
int x;
int get_x() { x }
bool compare(Pt1 p){ p.get_x() == self.get_x() }
}
class Pt2 extends Pt1 {
int y;
int get_y() { y }
bool compare(Pt2 p) { // override
p.get_x() == self.get_x()
&& p.get_y() == self.get_y() }
}
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What happened
• Could inherit code without being a subtype
• Cannot always do this
– what if get_x called self.compare with a Pt1
Possible solutions:
– Re-typecheck get_x in subclass
– Use a really fancy type system
– Don’t override compare
• Moral: Not suggesting “subclassing not subtyping” is useful, but
the concepts of inheritance and subtyping are orthogonal
5 March 2009
CSE P505 Winter 2009 Dan Grossman
62
Now what?
• That’s basic class-based OOP
– Note: Not all OOPLs use classes
(Javascript, Self, Cecil, …)
• Now some “fancy” stuff
– Typechecking
– Multiple inheritance; multiple interfaces
– Static overloading
– Multimethods
– Revenge of bounded polymorphism
5 March 2009
CSE P505 Winter 2009 Dan Grossman
63
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