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/*
TREE - MUTATOR . hpp - flexible binding to map generic tree changing operations
Copyright ( C ) Lumiera . org
2015 , Hermann Vosseler < Ichthyostega @ web . de >
This program is free software ; you can redistribute it and / or
modify it under the terms of the GNU General Public License as
published by the Free Software Foundation ; either version 2 of
the License , or ( at your option ) any later version .
This program is distributed in the hope that it will be useful ,
but WITHOUT ANY WARRANTY ; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE . See the
GNU General Public License for more details .
You should have received a copy of the GNU General Public License
along with this program ; if not , write to the Free Software
Foundation , Inc . , 675 Mass Ave , Cambridge , MA 0213 9 , USA .
*/
/** @file tree-mutator.hpp
* * Customisable intermediary to abstract generic tree mutation operations .
* * This is the foundation for generic treatment of tree altering operations ,
* * and especially to handling of changes ( diff ) to hierarchical data structures .
* * The goal is to represent a standard set of conceptual operations working on
* * arbitrary data structures , without the need for these data structures to
* * comply to any interface or base type . Rather , we allow each instance to
* * define binding closures , which allows to tap into any internal data
* * representation , without any need of disclosure . The only assumption is
* * that the data to be treated is \ em hierarchical and \ em object - like ,
* * i . e . it has ( named ) attributes and it may have a collection of children .
* * If necessary , typing constraints can be integrated through symbolic
* * representation of types as chained identifiers . ( path dependent types ) .
* *
* * The interface implemented by the TreeMutator is shaped such as to support
* * the primitives of Lumiera ' s tree \ link diff - language . hpp diff handling language . \ endlink
* * By default , each of these primitives is implemented as a \ c NOP - - but each operation
* * can be replaced by a binding closure , which allows to invoke arbitrary code in the
* * context of the given object ' s implementation internals .
* *
* * @ see generic - tree - mutator - test . cpp
* * @ see DiffDetector
* *
*/
# ifndef LIB_DIFF_TREE_MUTATOR_H
# define LIB_DIFF_TREE_MUTATOR_H
# include "lib/error.hpp"
# include "lib/symbol.hpp"
//#include "lib/util.hpp"
//#include "lib/format-string.hpp"
# include <functional>
# include <string>
//#include <vector>
//#include <map>
namespace lib {
namespace diff {
namespace error = lumiera : : error ;
//using util::_Fmt;
using lib : : Literal ;
using std : : function ;
using std : : string ;
namespace {
settle on a concrete implementation approach based on inheritance chain
After some reconsideration, I decide to stick to the approach with the closures,
but to use a metaprotramming technique to build an inheritance chain.
While I can not decide on the real world impact of storing all those closures,
in theory this approach should enable the compiler to remove all of the
storage overhead. Since, when storing the result into an auto variable
right within scope (as demonstrated in the test), the compiler
sees the concrete type and might be able to boil down the actual
generated virtual function implementations, thereby inlining the
given closures.
Whereas, on the other hand, if we'd go the obvious conventional route
and place the closures into a Map allocated on the stack, I wouldn't
expect the compiler to do data flow analysis to prove this allocation
is not necessary and inline it away.
NOTE: there is now guarantee this inlining trick will ever work.
And, moreover, we don't know anything regarding the runtime effect.
The whole picture is way more involved as it might seem at first sight.
Even if we go the completely conventional route and require every
participating object to supply an implementation of some kind of
"Serializable" interface, we'll end up with a (hand written!)
implementation class for each participating setup, which takes
up space in the code segment of the executable. While the closure
based approach chosen here, consumes data segment (or heap) space
per instance for the functors (or function pointers) representing
the closures, plus code segment space for the closures, but the
latter with a way higher potential for inlining, since the closure
code and the generated virtual functions are necessarily emitted
within the same compilation unit and within a local (inline, not
publickly exposed) scope.
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template < class PAR >
class Builder ;
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////////TODO only preliminary....
typedef Literal ID ;
typedef struct { } Attribute ;
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}
/**
* Customisable intermediary to abstract
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* mutating operations on arbitrary , hierarchical object - like data .
* The TreeMutator exposes two distinct interfaces
* - the \ em operation API - - similar to what a container exposes - -
* is the entirety of abstract operations that can be done to the
* subsumed , tree like target structure
* - the \ em binding API allows to link some or all of these generic
* activities to concrete manipulations known within target scope .
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*/
class TreeMutator
{
public :
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/* ==== operation API ==== */
settle on a concrete implementation approach based on inheritance chain
After some reconsideration, I decide to stick to the approach with the closures,
but to use a metaprotramming technique to build an inheritance chain.
While I can not decide on the real world impact of storing all those closures,
in theory this approach should enable the compiler to remove all of the
storage overhead. Since, when storing the result into an auto variable
right within scope (as demonstrated in the test), the compiler
sees the concrete type and might be able to boil down the actual
generated virtual function implementations, thereby inlining the
given closures.
Whereas, on the other hand, if we'd go the obvious conventional route
and place the closures into a Map allocated on the stack, I wouldn't
expect the compiler to do data flow analysis to prove this allocation
is not necessary and inline it away.
NOTE: there is now guarantee this inlining trick will ever work.
And, moreover, we don't know anything regarding the runtime effect.
The whole picture is way more involved as it might seem at first sight.
Even if we go the completely conventional route and require every
participating object to supply an implementation of some kind of
"Serializable" interface, we'll end up with a (hand written!)
implementation class for each participating setup, which takes
up space in the code segment of the executable. While the closure
based approach chosen here, consumes data segment (or heap) space
per instance for the functors (or function pointers) representing
the closures, plus code segment space for the closures, but the
latter with a way higher potential for inlining, since the closure
code and the generated virtual functions are necessarily emitted
within the same compilation unit and within a local (inline, not
publickly exposed) scope.
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virtual void
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insertChild ( ID id )
{
UNIMPLEMENTED ( " establish new child node at current position " ) ;
}
settle on a concrete implementation approach based on inheritance chain
After some reconsideration, I decide to stick to the approach with the closures,
but to use a metaprotramming technique to build an inheritance chain.
While I can not decide on the real world impact of storing all those closures,
in theory this approach should enable the compiler to remove all of the
storage overhead. Since, when storing the result into an auto variable
right within scope (as demonstrated in the test), the compiler
sees the concrete type and might be able to boil down the actual
generated virtual function implementations, thereby inlining the
given closures.
Whereas, on the other hand, if we'd go the obvious conventional route
and place the closures into a Map allocated on the stack, I wouldn't
expect the compiler to do data flow analysis to prove this allocation
is not necessary and inline it away.
NOTE: there is now guarantee this inlining trick will ever work.
And, moreover, we don't know anything regarding the runtime effect.
The whole picture is way more involved as it might seem at first sight.
Even if we go the completely conventional route and require every
participating object to supply an implementation of some kind of
"Serializable" interface, we'll end up with a (hand written!)
implementation class for each participating setup, which takes
up space in the code segment of the executable. While the closure
based approach chosen here, consumes data segment (or heap) space
per instance for the functors (or function pointers) representing
the closures, plus code segment space for the closures, but the
latter with a way higher potential for inlining, since the closure
code and the generated virtual functions are necessarily emitted
within the same compilation unit and within a local (inline, not
publickly exposed) scope.
2015-04-05 18:26:49 +02:00
virtual void
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deleteChild ( ID id )
{
UNIMPLEMENTED ( " destroy child node at current position " ) ;
}
settle on a concrete implementation approach based on inheritance chain
After some reconsideration, I decide to stick to the approach with the closures,
but to use a metaprotramming technique to build an inheritance chain.
While I can not decide on the real world impact of storing all those closures,
in theory this approach should enable the compiler to remove all of the
storage overhead. Since, when storing the result into an auto variable
right within scope (as demonstrated in the test), the compiler
sees the concrete type and might be able to boil down the actual
generated virtual function implementations, thereby inlining the
given closures.
Whereas, on the other hand, if we'd go the obvious conventional route
and place the closures into a Map allocated on the stack, I wouldn't
expect the compiler to do data flow analysis to prove this allocation
is not necessary and inline it away.
NOTE: there is now guarantee this inlining trick will ever work.
And, moreover, we don't know anything regarding the runtime effect.
The whole picture is way more involved as it might seem at first sight.
Even if we go the completely conventional route and require every
participating object to supply an implementation of some kind of
"Serializable" interface, we'll end up with a (hand written!)
implementation class for each participating setup, which takes
up space in the code segment of the executable. While the closure
based approach chosen here, consumes data segment (or heap) space
per instance for the functors (or function pointers) representing
the closures, plus code segment space for the closures, but the
latter with a way higher potential for inlining, since the closure
code and the generated virtual functions are necessarily emitted
within the same compilation unit and within a local (inline, not
publickly exposed) scope.
2015-04-05 18:26:49 +02:00
virtual void
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findChild ( ID id )
{
UNIMPLEMENTED ( " look ahead, find and retrieve denoted child to be relocated at current position " ) ;
}
settle on a concrete implementation approach based on inheritance chain
After some reconsideration, I decide to stick to the approach with the closures,
but to use a metaprotramming technique to build an inheritance chain.
While I can not decide on the real world impact of storing all those closures,
in theory this approach should enable the compiler to remove all of the
storage overhead. Since, when storing the result into an auto variable
right within scope (as demonstrated in the test), the compiler
sees the concrete type and might be able to boil down the actual
generated virtual function implementations, thereby inlining the
given closures.
Whereas, on the other hand, if we'd go the obvious conventional route
and place the closures into a Map allocated on the stack, I wouldn't
expect the compiler to do data flow analysis to prove this allocation
is not necessary and inline it away.
NOTE: there is now guarantee this inlining trick will ever work.
And, moreover, we don't know anything regarding the runtime effect.
The whole picture is way more involved as it might seem at first sight.
Even if we go the completely conventional route and require every
participating object to supply an implementation of some kind of
"Serializable" interface, we'll end up with a (hand written!)
implementation class for each participating setup, which takes
up space in the code segment of the executable. While the closure
based approach chosen here, consumes data segment (or heap) space
per instance for the functors (or function pointers) representing
the closures, plus code segment space for the closures, but the
latter with a way higher potential for inlining, since the closure
code and the generated virtual functions are necessarily emitted
within the same compilation unit and within a local (inline, not
publickly exposed) scope.
2015-04-05 18:26:49 +02:00
virtual TreeMutator &
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mutateChild ( ID id )
{
UNIMPLEMENTED ( " expose a recursive TreeMutator to transform the denoted child " ) ;
}
settle on a concrete implementation approach based on inheritance chain
After some reconsideration, I decide to stick to the approach with the closures,
but to use a metaprotramming technique to build an inheritance chain.
While I can not decide on the real world impact of storing all those closures,
in theory this approach should enable the compiler to remove all of the
storage overhead. Since, when storing the result into an auto variable
right within scope (as demonstrated in the test), the compiler
sees the concrete type and might be able to boil down the actual
generated virtual function implementations, thereby inlining the
given closures.
Whereas, on the other hand, if we'd go the obvious conventional route
and place the closures into a Map allocated on the stack, I wouldn't
expect the compiler to do data flow analysis to prove this allocation
is not necessary and inline it away.
NOTE: there is now guarantee this inlining trick will ever work.
And, moreover, we don't know anything regarding the runtime effect.
The whole picture is way more involved as it might seem at first sight.
Even if we go the completely conventional route and require every
participating object to supply an implementation of some kind of
"Serializable" interface, we'll end up with a (hand written!)
implementation class for each participating setup, which takes
up space in the code segment of the executable. While the closure
based approach chosen here, consumes data segment (or heap) space
per instance for the functors (or function pointers) representing
the closures, plus code segment space for the closures, but the
latter with a way higher potential for inlining, since the closure
code and the generated virtual functions are necessarily emitted
within the same compilation unit and within a local (inline, not
publickly exposed) scope.
2015-04-05 18:26:49 +02:00
virtual void
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setAttribute ( ID id , Attribute newValue )
{
settle on a concrete implementation approach based on inheritance chain
After some reconsideration, I decide to stick to the approach with the closures,
but to use a metaprotramming technique to build an inheritance chain.
While I can not decide on the real world impact of storing all those closures,
in theory this approach should enable the compiler to remove all of the
storage overhead. Since, when storing the result into an auto variable
right within scope (as demonstrated in the test), the compiler
sees the concrete type and might be able to boil down the actual
generated virtual function implementations, thereby inlining the
given closures.
Whereas, on the other hand, if we'd go the obvious conventional route
and place the closures into a Map allocated on the stack, I wouldn't
expect the compiler to do data flow analysis to prove this allocation
is not necessary and inline it away.
NOTE: there is now guarantee this inlining trick will ever work.
And, moreover, we don't know anything regarding the runtime effect.
The whole picture is way more involved as it might seem at first sight.
Even if we go the completely conventional route and require every
participating object to supply an implementation of some kind of
"Serializable" interface, we'll end up with a (hand written!)
implementation class for each participating setup, which takes
up space in the code segment of the executable. While the closure
based approach chosen here, consumes data segment (or heap) space
per instance for the functors (or function pointers) representing
the closures, plus code segment space for the closures, but the
latter with a way higher potential for inlining, since the closure
code and the generated virtual functions are necessarily emitted
within the same compilation unit and within a local (inline, not
publickly exposed) scope.
2015-04-05 18:26:49 +02:00
std : : cout < < " Empty Base Impl: apply a value change to the named attribute " < < std : : endl ; ////////////////TODO empty implementation should be NOP
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}
settle on a concrete implementation approach based on inheritance chain
After some reconsideration, I decide to stick to the approach with the closures,
but to use a metaprotramming technique to build an inheritance chain.
While I can not decide on the real world impact of storing all those closures,
in theory this approach should enable the compiler to remove all of the
storage overhead. Since, when storing the result into an auto variable
right within scope (as demonstrated in the test), the compiler
sees the concrete type and might be able to boil down the actual
generated virtual function implementations, thereby inlining the
given closures.
Whereas, on the other hand, if we'd go the obvious conventional route
and place the closures into a Map allocated on the stack, I wouldn't
expect the compiler to do data flow analysis to prove this allocation
is not necessary and inline it away.
NOTE: there is now guarantee this inlining trick will ever work.
And, moreover, we don't know anything regarding the runtime effect.
The whole picture is way more involved as it might seem at first sight.
Even if we go the completely conventional route and require every
participating object to supply an implementation of some kind of
"Serializable" interface, we'll end up with a (hand written!)
implementation class for each participating setup, which takes
up space in the code segment of the executable. While the closure
based approach chosen here, consumes data segment (or heap) space
per instance for the functors (or function pointers) representing
the closures, plus code segment space for the closures, but the
latter with a way higher potential for inlining, since the closure
code and the generated virtual functions are necessarily emitted
within the same compilation unit and within a local (inline, not
publickly exposed) scope.
2015-04-05 18:26:49 +02:00
/**
* start building a custom adapted tree mutator ,
* where the operations are tied by closures or
* wrappers into the current implementation context .
*/
static Builder < TreeMutator > build ( ) ;
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} ;
settle on a concrete implementation approach based on inheritance chain
After some reconsideration, I decide to stick to the approach with the closures,
but to use a metaprotramming technique to build an inheritance chain.
While I can not decide on the real world impact of storing all those closures,
in theory this approach should enable the compiler to remove all of the
storage overhead. Since, when storing the result into an auto variable
right within scope (as demonstrated in the test), the compiler
sees the concrete type and might be able to boil down the actual
generated virtual function implementations, thereby inlining the
given closures.
Whereas, on the other hand, if we'd go the obvious conventional route
and place the closures into a Map allocated on the stack, I wouldn't
expect the compiler to do data flow analysis to prove this allocation
is not necessary and inline it away.
NOTE: there is now guarantee this inlining trick will ever work.
And, moreover, we don't know anything regarding the runtime effect.
The whole picture is way more involved as it might seem at first sight.
Even if we go the completely conventional route and require every
participating object to supply an implementation of some kind of
"Serializable" interface, we'll end up with a (hand written!)
implementation class for each participating setup, which takes
up space in the code segment of the executable. While the closure
based approach chosen here, consumes data segment (or heap) space
per instance for the functors (or function pointers) representing
the closures, plus code segment space for the closures, but the
latter with a way higher potential for inlining, since the closure
code and the generated virtual functions are necessarily emitted
within the same compilation unit and within a local (inline, not
publickly exposed) scope.
2015-04-05 18:26:49 +02:00
namespace {
template < class PAR >
struct ChangeOperation
: PAR
{
function < void ( string ) > change_ ;
virtual void
setAttribute ( ID id , Attribute newValue )
{
PAR : : setAttribute ( id , newValue ) ; ////////////////////TODO only as a check to verify the class chaining. Of course we do *not* want to call the inherited implementeation
string dummy ( " blubb " ) ;
change_ ( dummy ) ;
}
ChangeOperation ( function < void ( string ) > clo , PAR const & chain )
: PAR ( chain )
, change_ ( clo )
{ }
} ;
template < class PAR >
struct Builder
: PAR
{
using Chain = ChangeOperation < PAR > ;
Builder ( PAR par )
: PAR ( par )
{ }
/* ==== binding API ==== */
Builder < Chain >
change ( Literal attributeID , function < void ( string ) > closure )
{
return Builder < Chain > ( Chain ( closure , * this ) ) ;
}
} ;
}
2015-04-02 03:30:20 +02:00
settle on a concrete implementation approach based on inheritance chain
After some reconsideration, I decide to stick to the approach with the closures,
but to use a metaprotramming technique to build an inheritance chain.
While I can not decide on the real world impact of storing all those closures,
in theory this approach should enable the compiler to remove all of the
storage overhead. Since, when storing the result into an auto variable
right within scope (as demonstrated in the test), the compiler
sees the concrete type and might be able to boil down the actual
generated virtual function implementations, thereby inlining the
given closures.
Whereas, on the other hand, if we'd go the obvious conventional route
and place the closures into a Map allocated on the stack, I wouldn't
expect the compiler to do data flow analysis to prove this allocation
is not necessary and inline it away.
NOTE: there is now guarantee this inlining trick will ever work.
And, moreover, we don't know anything regarding the runtime effect.
The whole picture is way more involved as it might seem at first sight.
Even if we go the completely conventional route and require every
participating object to supply an implementation of some kind of
"Serializable" interface, we'll end up with a (hand written!)
implementation class for each participating setup, which takes
up space in the code segment of the executable. While the closure
based approach chosen here, consumes data segment (or heap) space
per instance for the functors (or function pointers) representing
the closures, plus code segment space for the closures, but the
latter with a way higher potential for inlining, since the closure
code and the generated virtual functions are necessarily emitted
within the same compilation unit and within a local (inline, not
publickly exposed) scope.
2015-04-05 18:26:49 +02:00
Builder < TreeMutator >
TreeMutator : : build ( )
{
return Builder < TreeMutator > ( TreeMutator ( ) ) ;
}
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} } // namespace lib::diff
# endif /*LIB_DIFF_TREE_MUTATOR_H*/