Language characteristics

• uniformity of data structures
• documentation value
• reliability
• inheritance mechanisms
• efficiency
• memory management
• language complexity

Uniformity

Documentation value

The issue of producing documentation from C++ is still open. A number of tools exist (including a WEB-like system for C++ and a tool to produce manual pages from C++ header files) but no standard has yet emerged. Moreover, some people truly dislike the terseness of C/C++. Personally, I prefer the C/C++ syntax above the syntactical conventions of both Eiffel and Smalltalk, provided that it is used in a disciplined fashion.

Java programs may be documented using javadoc. The javadoc program may be regarded as the standard C++ has been waiting for, in vain.

Reliability

An important feature of Eiffel is that it supports assertions that may be validated at runtime. In combinations with exceptions, this provides a powerful feature for the development of reliable programs.

At the price of some additional coding (for example, to save the current state to enable the use of the old value), such assertions may be expressed by using the assert macros provided for C++.

In defense of C++, it is important to acknowledge that C++ offers adequate protection mechanisms to shield classes derived by inheritance from the implementation details of their ancestor classes. Neither Smalltalk nor Eiffel offer such protection.

Java was introduced as a more reliable variant of C++. Java's reliability comes partly from the shielded environment offered by the Java virtual machine, and partly from the absence of pointers and the availability of built-in garbage collection. Practical experience shows that for the average student/programmer Java is indeed substantially less error-prone than C++.

Inheritance

As far as the assertion mechanism offered by Eiffel is concerned,  [Meyer88] gives clear guidelines prescribing how to use assertions in derived classes. However, the Eiffel compiler offers no assistance in verifying whether these rules are followed. The same guidelines apply to the use of assertions in C++, naturally lacking compiler support as well.

The Java language offers only single (code) inheritance, but allows for multiple interface inheritance. The realization of (multiple) interfaces seems to be a fairly good substitute for multiple (implementation) inheritance.

Efficiency

The compilation of Eiffel programs can result in programs having adequate execution speed. However, in Eiffel dynamic binding takes place in principle for all methods. Yet a clever compiler can significantly reduce the number of indirections needed to execute a method.

In contrast to C++, in Eiffel all objects are created on the heap. The garbage collection needed to remove these objects may affect the execution speed of programs.

C++ has been designed with efficiency in mind. For instance, the availability of inline functions, and the possibility to allocate objects on the runtime stack (instead of on the heap), and the possibility to declare friend functions and classes that have direct access to the private instance variables of a class allow the programmer to squeeze out the last drop of efficiency. However, as a drawback, when higher level functionality is needed (as in automatic garbage collection) it must be explicitly programmed, and a similar price as when the functionality would have been provided by the system has to be paid. The only difference is that the programmer has a choice.

At the time of writing there does not exist a truly efficient implementation of the Java language. Significant improvements may be expected from the JIT (Just In Time) compilers that produce native code dynamically, employing techniques as originally developed for the Self language, discussed in section Self.

Language complexity

Eiffel contains few language elements that extend beyond object-oriented programming. In particular, Eiffel does not allow for overloading method names (according to signature) within a class. This may lead to unnecessarily elaborate method names. (The new version of Eiffel (Eiffel-3) does allow for overloading method names.)

Without doubt, C++ is generally regarded as a highly complex language. In particular, the rules governing the overloading of operators and functions are quite complicated. The confusion even extends to the various compiler suppliers, which is one of the reasons why C++ is still barely portable. Somewhat unfortunately, the rules for overloading and type conversion for C++ have to a large extent been determined by the need to remain compatible with C. Even experienced programmers need occasionally to experiment to find out what will happen.

According to  [BPS89], C++ is too large and contains too much of the syntax and semantics inherited from C. However, the validity of their motto small is beautiful is not as obvious as it seems. The motivations underlying the introduction of the various features incorporated in C++ are quite well explained in  [Stroustrup97]. The main problem, to my mind, in using C++ (or any of the object-oriented languages for that matter) lies in the area of design. We still have insufficient experience in using abstract data types to define a complete method and operator interface including its relation to other data types (that is its behavior under the various operators and type conversions that apply to a particular type). The problem is hence not only one of language design but of the design of abstract data types.

Java is certainly less complex than C++. For example, it offers no templates, no operator overloading and no type coercion operators. However, although Java is apparently easier to use, it is far less elegant than C++ when it comes to creating user-defined types. Class interfaces in Java are usually much more verbose than similar interfaces in C++. And, due to the absence of templates, type casts are necessary in many places. On the other hand, casts in Java are type safe.

object-oriented programming

Design dimensions of object-oriented languages

subsections:

• Object-based versus object-oriented
• Towards and orthogonal approach -- type extensions
• Multi-paradigms languages -- logic
• Active objects -- synchronous Java/C++

Object-oriented language design

• object: state + operations
• class: template for object creation
• inheritance: super/base and subclasses

  object-oriented = 
        objects + classes + inheritance 
  

data abstraction -- state accessible by operations

strong typing -- compile time checking

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slide: Object-based versus object-oriented

---

In this section we will look at the arguments presented in  [Wegner87] in somewhat more detail. Also, we will look at the viability of combining seemingly disparate paradigms (such as the logic programming paradigm) with the object-oriented language paradigm. In the sections that follow, we will discuss some alternatives and extensions to the object model.

Object-based versus object-oriented

\label{object-based} How would you characterize Ada83? See  [Barnes94]. Is Ada object-oriented? And Modula-2? See  [Wirth83]. The answer is no and no. And Ada9X and Modula-3? See  [Barnes94] and  [Card89]. The answer is yes and yes. In the past there has been some confusion as to when to characterize a language as {\em object-oriented}. For example,  [Booch86] characterizes Ada as object-oriented and motivates this by saying that Ada can be used as an implementation language in an object-oriented approach to program development. Clearly, Ada supports some notion of objects (which are defined as packages). However, although Ada supports objects and generic descriptions of objects (by generic packages), it does not support code sharing by inheritance. In a later work,  [Booch91] revises his original (faulty) opinion, in response to  [Wegner87], who proposed considering inheritance as an essential characteristic of object orientation. Similarly, despite the support that Modula-2 offers for defining (object-like) abstract data types, consisting of an interface specification and an implementation (which may be hidden), Modula-2 does not support the creation of derived (sub)types that share the behavior of their base (super)type. See also section adt-modules.

Classes versus types

Another confusion that frequently arises is due to the ill-defined relationship between the notion of a class and the notion of a type. The notion of types is already familiar from procedural programming languages such as Pascal and (in an ill-famed way) from C. The type of variables and functions may be profitably used to check for (syntactical) errors. Strong static type checking may prevent errors ranging from simple typos to using undefined (or wrongly defined) functions. The notion of a class originally has a more operational meaning. Operationally, a class is a template for object creation. In other words, a class is a description of the collection of its instances, that is the objects that are created using the class description as a recipe. Related to this notion of a class, inheritance was originally defined as a means to share (parts of) a description. Sharing by (inheritance) derivation is, pragmatically, very convenient. It provides a more controlled way of code sharing than, for example, the use of macros and file inclusion (as were popular in the C community). Since  [Wegner87] published his original analysis of the dimensions of object-oriented language design, the phrase {\em object-oriented} has been commonly understood as involving objects, classes and inheritance. This is the traditional object model as embodied by Smalltalk and, to a large extent, by Eiffel, C++ and Java. However, unlike Smalltalk, both Eiffel and C++ have also been strongly influenced by the abstract data type approach to programming. Consequently, in Eiffel and C++ classes have been identified with types and derivation by inheritance with subtyping. Unfortunately, derivation by inheritance need not necessarily result in the creation of proper subtypes, that is classes whose instances conform to the behavior specified by their base class. In effect, derived classes may be only distantly related to their base classes when inheritance is only used as a code sharing device. For example, a window manager class may inherit from a list container class (an idiom used in Meyer, 1988).

Towards an orthogonal approach -- type extensions

According to  [Wegner87], much of the confusion around the various features of object-oriented programming languages arises from the fact that these features are largely interdependent, as for instance the notion of object and class on the one hand, and the notion of class and inheritance on the other. To resolve this confusion,  [Wegner87] proposes a more orthogonal approach to characterize the various features of object-oriented languages, according to dimensions that are to a large extent independent. See slide 5-orthogonal.

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Orthogonal approach

• objects -- modular computing agents
• types -- expression classification
• delegation -- resource sharing
• abstraction -- interface specification

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slide: Orthogonal dimensions

---

The features that constitute an object-oriented programming language in an orthogonal way are, according to  [Wegner87]: objects, types, delegation and abstraction.

Objects

are in essence modular computing agents. They correspond to the need for encapsulation in design, that is the construction of modular units to which a principle of locality applies (due to combining data and operations). Object-oriented languages may, however, differ in the degree to which they support encapsulation. For example, in a distributed environment a high degree of encapsulation must be offered, prohibiting attempts to alter global variables (from within an object) or local instance variables (from without). Moreover, the runtime object support system must allow for what may best be called remote method invocation. As far as parallel activity is concerned, only a few languages provide constructs to define concurrently active objects. See section Active for a more detailed discussion. Whether objects support reactiveness, that is sufficient flexibility to respond safely to a message, depends largely upon (program) design.  [Meyer88], for instance, advocates a {\em shopping list approach} to designing the interface of an object, to allow for a high degree of (temporal) independence between method calls.

Types

may be understood as a mechanism for expression classification. From this perspective, Smalltalk may be regarded as having a dynamic typing system: dynamic, in the sense that the inability to evaluate an expression will lead to a runtime error. The existence of types obviates the need to have classes, since a type may be considered as a more abstract description of the behavior of an object. Furthermore, subclasses (as may be derived through inheritance) are more safely defined as subtypes in a polymorphic type system. See section flavors. At the opposite side of the type dimension we find the statically typed languages, which allow us to determine the type of the designation of a variable at compile-time. In that case, the runtime support system need not carry any type information, except a dispatch table to locate virtual functions.

Delegation

(in its most generic sense) is a mechanism for resource sharing. As has been shown in  [Lieber], delegation subsumes inheritance, since the resource sharing effected by inheritance may easily be mimicked by delegating messages to the object's ancestors by means of an appropriate dispatching mechanism. In a narrower sense, delegation is usually understood as a more dynamic mechanism that allows the redirection of control dynamically. In addition, languages supporting dynamic delegation (such as Self) do not sacrifice dynamic self-reference. This means that when the object executing a method refers to itself, the actual context will be the delegating object. See section prototypes for a more detailed discussion. In contrast, inheritance (as usually understood in the context of classes) is a far more static mechanism. Inheritance may be understood as (statically) copying the code from an ancestor class to the inheriting class (with perhaps some modifications), whereas delegation is truly dynamic in that messages are dispatched to objects that have a life-span independent of the dispatching object.

Abstraction

(although to some extent related to types) is a mechanism that may be independently applied to provide an interface specification for an object. For example, in the presence of active objects (that may execute in parallel) we may need to be able to restrict dynamically the interface of an object as specified by its type in order to maintain the object in a consistent state. Also for purely sequential objects we may impose a particular protocol of interaction (as may, for example, be expressed by a contract) to be able to guarantee correct behavior. Another important aspect of abstraction is protection. Object-oriented languages may provide (at least) two kinds of protection. First, a language may have facilities to protect the object from illegal access by a client (from without). This is effected by annotations such as private and protected. And secondly, a language may have facilities to protect the object (as it were from within) from illegal access through delegation (that is by instances of derived object classes). Most languages support the first kind of protection. Only few languages, among which are C++ and Java, support the second kind too. The independence of abstraction and typing may further be argued by pointing out that languages supporting strong typing need not enforce the use of abstract data types having a well-defined behavior.

Multi-paradigm languages -- logic

Object-oriented programming has evolved as a new and strong paradigm of programming. Has it? Of the languages mentioned, only Smalltalk has what may be considered a radically new language design (and to some extent also the language Self, that we will discuss in the next section). Most of the other languages, including Eiffel, C++ (and for that matter also CLOS and Oberon), may be considered as object-oriented extensions of already existing languages or, to put it more broadly, language paradigms. Most popular are, evidently, object-oriented extensions based on procedural language paradigms, closely followed by the (Lisp-based) extensions of the functional language paradigm. Less well-known are extensions based on the logic programming paradigm, of which DLP is my favorite example. In  [Wegner92], it is argued that the logic programming paradigm does not fit in with an object-oriented approach. I strongly disagree with this position. However, the arguments given in  [Wegner92] to defend it are worthwhile, in that they make explicit what desiderata we may impose on object-oriented languages. Remaining within the confines of a classical object model, the basic ingredients for an object-oriented extension of any language (paradigm) are: objects, classes and inheritance. Although the exact meaning of these notions is open for discussion, language designers seem to have no difficulty in applying these concepts to extend (or design) a programming language.

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Open systems

• reactive -- flexible (dynamic) choice of actions
• modular -- (static) scalability

Dimensions of modularity

• encapsulation boundary -- interface to client
• distribution boundary -- visibility from within objects
• concurrency boundary -- threads per object, synchronization

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slide: Dimensions of modularity

---

According to  [Wegner92], the principal argument against combining logic programming and object-oriented programming is that such a combination does not support the development of open systems without compromising the logical nature of logic programming. Openness may be considered as one of the prime goals of object orientation. See slide 5-open. A software system is said to be open if its behavior can be easily modified and extended.  [Wegner92] distinguishes between two mechanisms to achieve openness; dynamically through reactiveness, and statically through modularity. Reactiveness allows a program to choose dynamically between potential actions. For sequential object-oriented languages, late binding (that is, the dispatching mechanism underlying virtual function calls) is one of the mechanisms used to effect the dynamic selection of alternatives. Concurrent object-oriented languages usually offer an additional construct, in the form of a guard or accept statement, to determine dynamically which method call to answer. In both cases, the answer depends upon the nature of the object and (especially in the latter case) the state of the object (and its willingness to answer). Openness through modularity means that a system can safely be extended by adding (statically) new components. The issue of openness in the latter sense is immediately related to the notion of scalability, that is the degree to which a particular component can be safely embedded in a larger environment and extended to include new functionality. At first sight, classes and inheritance strongly contribute to achieving such (static) openness. However, there is more to modularity than the encapsulation provided by classes only. From a modeling perspective, encapsulation (as provided by objects and classes) is the basic mechanism to define the elements or entities of a model. The declarative nature of an object-oriented approach resides exactly in the opportunity to define such entities and their relations through inheritance. However, encapsulation (as typically understood in the context of a classical object model) only provides protection from illegal access from without. As such, it is a one-sided boundary. The other side, the extent to which the outside world is visible for the object (from within), may be called the distribution boundary. Many languages, including Smalltalk and C++, violate the distribution boundary by allowing the use of (class-wide) global variables. (See also section meta.) Evidently, this may lead to problems when objects reside on distinct processors, as may be the case in distributed systems. Typically, the message passing metaphor (commonly used to characterize the interaction between objects) contains the suggestion that objects may be physically distributed (across a network of processors). Also (because of the notion of encapsulation), objects are often regarded as autonomous entities, that in principle may have independent activity. However, most of the languages mentioned do not (immediately) fulfill the additional requirements needed for actual physical distribution or parallel (multi-threaded) activity.

Object-oriented logic programming

Logic programming is often characterized as relational programming, since it allows the exhaustive exploration of a search space defined by logical relations (for instance, by backtracking as in Prolog). The advantage of logic programming, from a modeling point of view, is that it allows us to specify in a logical manner (that is by logical clauses) the relations between the entities of a particular domain. A number of efforts to combine logic programming with object-oriented features have been undertaken, among which is the development of the language Vulcan. Vulcan is based on the Concurrent Prolog language and relies on a way of implementing objects as perpetual processes. Without going into detail, the idea (originally proposed in  [ST83]) is that an object may be implemented as a process defined by one or more (recursive) clauses. An object may accept messages in the form of a predicate call. The state of an object is maintained by parameters of the predicate, which are (possibly modified by the method call) passed to the recursive invocation of one of the clauses defining the object. To communicate, an object (defined as a process) waits until a client asks for the execution of a method. The clauses defining the object are then evaluated to check which one is appropriate for that particular method call. If there are multiple candidate clauses, one is selected and evaluated. The other candidate clauses are discarded. Since the clauses defining an object are recursive, after the evaluation of a method the object is ready to accept another message. The model of (object) interaction supported by Concurrent Prolog requires fine-grained concurrency, which is possible due to the side-effect free nature of logical clauses. However, to restrict the number of processes created during the evaluation of a goal, Concurrent Prolog enforces a committed choice between candidate clauses, thus throwing away alternative solutions.  [Wegner92] observes, rightly I think, that the notion of committed choice is in conflict with the relational nature of logic programming. Indeed, Concurrent Prolog absolves logical completeness in the form of backtracking, to remain within the confines of the process model adopted.  [Wegner92], however, goes a step further and states that reactiveness and backtracking are irreconcilable features. That these features may fruitfully be incorporated in a single language framework is demonstrated by the language DLP. However, to support backtracking and objects, a more elaborate process model is needed than the process model supported by Concurrent Prolog (which in a way identifies an object with a process). With such a model (sketched in appendix E), there seems to be no reason to be against the marriage of logic programming and object orientation.

Active objects -- synchronous Java/C++

When it comes to combining objects (the building blocks in an object-oriented approach) with processes (the building blocks in parallel computing), there are three approaches conceivable. See slide 6-o-conc.

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Object-based concurrency

• add processes -- synchronization
• multiple active objects -- rendezvous
• asynchronous communication -- message buffers

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slide: Objects and concurrency

---

One can simply add processes as an additional data type. Alternatively, one can introduce active objects, having activity of their own, or, one can employ asynchronous communication, allowing the client and server object to proceed independently.

Processes

The first, most straightforward approach, is to simply add processes as a primitive data type, allowing the creation of independent threads of processing. An example is Distributed Smalltalk (see Bennett, 1987). Another example is Java, which provides support for threads, synchronized methods and statements like wait and notify to protect re-entrant concurrent methods. The disadvantage of this approach, however, is that the programmer has full responsibility for the most difficult part of parallel programming, namely the synchronization between processes and the avoidance of common errors such as simultaneously assigning a value to a shared variable. Despite the fact that the literature, see  [Andrews], abounds with primitives supporting synchronization (such as semaphores, conditional sections and monitors), such an approach is error-prone and means a heavy burden on the shoulders of the application developer.

Active objects

A second, and in my view preferable, approach is to introduce explicitly a notion of active objects. Within this approach, parallelism is introduced by having multiple, simultaneously active objects. An example of a language supporting active objects is POOL, described in  [Am87]. Communication between active objects occurs by means of a (synchronous) rendezvous. To engage in a rendezvous, however, an active object must interrupt its own activity by means of an (Ada-like) accept statement (or answer statement as it is called in POOL), indicating that the object is willing to answer a message. The advantage of this approach is, clearly, that the encapsulation boundary of the object (its message interface) can conveniently be employed as a monitor-like mechanism to enforce mutual exclusion between method invocations. Despite the elegance of this solution, however, unifying objects and processes in active objects is not without problems. First, one has to decide whether to make all objects active or allow both passive and active objects. Logically, passive objects may be regarded as active objects that are eternally willing to answer every message listed in the interface description of the object. However, this generalization is not without penalty in terms of runtime efficiency. Secondly, a much more serious problem is that the message-answering semantics of active objects is distinctly different from the message-answering semantics of passive objects with respect to self-invocation. Namely, to answer a message, an active object must interrupt its own activity. Yet, if an active object (in the middle of answering a message) sends a message to itself, we have a situation of deadlock. Direct self-invocation, of course, can be easily detected, but indirect self-invocations require an analysis of the complete method invocation graph, which is generally not feasible.

Asynchronous communication

Deadlock may come about by synchronous (indirect) self-invocation. An immediate solution to this problem is provided by languages supporting asynchronous communication, which provide message buffers allowing the caller to proceed without waiting for an answer. Asynchronous message passing, however, radically deviates from the (synchronous) message passing supported by the traditional (passive) object model. This has the following consequences. First, for the programmer, it becomes impossible to know when a message will be dealt with and, consequently, when to expect an answer. Secondly, for the language implementor, allocating resources for storing incoming messages and deciding when to deal with messages waiting in a message buffer becomes a responsibility for which it is hard to find a general, yet efficient, solution. Active objects with asynchronous message passing constitute the so-called actor model, which has influenced several language designs. See  [Agha].

Synchronous C++/Java

In  [Petitpierre98], an extension of C++ is proposed that supports active objects, method calls by rendez vous and dynamic checks of synchronization conditions. The concurrency model supported by this language, which is called sC++, closely resembles the models supported by CCS, CSP and Ada.

An example of the declaration of an active object in sC++ is given in slide ex-active.

---

sC++

  active class S { 
  public: 
     m () { ... } 
  private: 
     @S () {  // pseudo-constructor
           select { 
              01 -> m(); // external call 
              instructions ...
           || 
              accept m;  // accept internal method
              instructions ... 
           ||
              waituntil (date); // time-out
              instructions ... 
           ||
              default           // default
              instructions ... 
           } 
      } 
  };
  

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slide: Synchronization conditions in sC++

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The synchronization conditions for instances of the class are specified in a select statement contained in a constructor-like method, which defines the active body of the object. Synchronization may take place in either (external) calls to another active object, internal methods that are specified as acceptable, or time-out conditions. When none of the synchronization conditions are met, a default action may take place. In addition to the synchronization conditions mentioned, a when guard-statement may occur in any of the clauses of select, to specify conditions on the state of the object or real-time constraints.

The sC++ language is implemented as an extension to the GNU C++ compiler. The sC++ runtime environment offers the possibility to validate a program by executing random walks, which is a powerful way to check the various synchronization conditions. The model of active objects supported by sC++ has also been realized as a Java library, see  [Petitpierre99]. There is currently, however, no preprocessor or compiler for Java supporting synchronous active objects.

As argumented in  [Petitpierre98], one of the advantages of synchronous active objects is that they allow us to do away with event-loops and callbacks. Another, perhaps more important, advantage is that the model bears a close relationship with formal models of concurrency as embodied by CCS and CSP, which opens opportunities for the verification and validation of concurrent object-oriented programs. In conclusion, in my opinion, the active object model discussed deserves to become a standard for both C++ and Java, not because it unifies the concurrency model for these languages, which is for example also done by JThreads++ described in  [JThreads], but because it offers a high level of abstraction suitable for concurrent object-oriented software engineering.

object-oriented programming

[] readme course preface 1 2 3 4 5 6 7 8 9 10 11 12 appendix lectures resources

Prototypes -- delegation versus inheritance

subsections:

• Alternative forms of sharing
• Implementation techniques -- Self

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The classical object model (which is constituted by classes, objects and inheritance) not only has its theoretical weaknesses (as outlined in the previous section) but has also been criticized from a more pragmatic perspective because of its inflexibility when it comes to developing systems. Code sharing has been mentioned as one of the advantages of inheritance (as it allows incremental development). However, alternative (read more flexible) forms of sharing have been proposed, employing prototypes and delegation instead of inheritance.

Alternative forms of sharing

A class provides a generic description of one or more objects, its instances. From a formal point of view, classes are related to types, and hence a class may be said to correspond to the set of instances that may be generated from it. This viewpoint leads to some anomalies, as in the case of abstract classes that at best correspond to partially defined sets. As another problem, in the context of inheritance, behavioral compatibility may be hard to arrive at, and hence the notion of subtype (which roughly corresponds with the subset relation) may be too restrictive. In practice, we may further encounter one-of-a-kind objects, for which it is simply cumbersome to construct an independent class. In a by now classical paper,  [Lieber] proposes the use of prototypes instead of classes. The notion of prototypes (or exemplars) has been used in cognitive psychology to explain the incremental nature of concept learning. As  [Lieber] notes, the philosophical distinction between prototypes (which provide a representative example of an object) and classes (which characterize a set of similar objects) may have important pragmatical consequences as it concerns the incremental definition of (hierarchies of) related objects. First, it is (claims Lieberman, 1986) more natural to start from a concrete example than to start from an abstract characterization as given by a class. And secondly, sharing information between prototypes and clones (that is, modified copies) thereof is far more flexible than the rather static means of sharing code as supported by the class inheritance mechanism. Code sharing by inheritance may be characterized as creation time sharing, which in this respect is similar to creating a copy of the object by cloning. In addition, prototypes may also support lifetime resource sharing by means of delegation. In principle, delegation is nothing but the forwarding of a message. However, in contrast to the forwarding mechanism as described in sections delegation-in-Java and hush-idioms, delegation in the context of prototypes does not change implicit self-reference to the forwarding object. In other words, when delegating a message to a parent object, the context of answering the message remains the same, as if the forwarding object answers the request directly. See slide 5-prototypes.

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Prototypes -- exemplars

• cloning -- creation time sharing
• delegation -- lifetime sharing

---

slide: Prototypes

---

An almost classical example used to illustrate prototypical programming is the example of a turtle object that delegates its request to move itself to a pen object (which has x and y coordinate attributes and a move method). The flexibility of delegation becomes apparent when we define a number of turtle objects by cloning the pen object and adding an y coordinate private to each turtle. In contrast to derivation by inheritance, the x coordinate of the pen object is shared dynamically. When changing the value of x in one of the turtle objects, all the turtle objects will be affected. Evidently, this allows considerable (and sometimes unwished for) flexibility. However, for applications (such as multimedia systems) such flexibility may be desirable.

Design issues

Strictly speaking, prototype-based delegation is not stronger than forwarding in languages supporting classes and inheritance. In  [Dony], a taxonomy of prototype-based languages is given. (This taxonomy has been partly implemented in Smalltalk. The implementation, however, employs so-called class-variables, which are not unproblematic themselves. See section meta.) One of the principal advantages of prototype-based languages is that they offer a consistent yet simple model of programming, consisting of objects, cloning and delegation. Yet, when designing a prototype-based language, a number of design decisions must be made (as reflected in the taxonomy given in Dony {\it et al.}, 1992). These issues concern the representation of the state of an object, how objects are created and the way in which delegation is handled. See slide 5-proto.

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State

• slots -- parents
• variables and methods

Creation

• shallow cloning
• deep cloning

Delegation

• implicit delegation
• explicit delegation

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slide: Prototypes -- state, creation, delegation

---

The basic prototype model only features slots which may store either a value or a piece of code that may be executed as a method. Alternatively, a distinction may be made between variables and methods. In both cases, late binding must be employed to access a value. In contrast, instance variable bindings in class-based languages are usually resolved statically. When creating a new object by cloning an existing object, we have the choice between deep copying and shallow copying. Only shallow copying, however, allows lifetime sharing (since deep copying results in a replica at creation time). Shallow copying is thus the obvious choice. Finally, delegation is usually handled implicitly, for instance by means of a special parent slot, indicating the ancestor of the object (which may be changed dynamically). Alternatively, it may be required to indicate delegation explicitly for each method. This gives a programmer more flexibility since it allows an object to have multiple ancestors, but at the price of an increase in notational complexity. Explicit delegation, by the way, most closely resembles the use of forwarding in class-based systems. One of the, as yet, unresolved problems of delegation-based computing is how to deal with what  [Dony] call split objects. An object may (internally) consist of a large number of (smaller) objects that are linked to each other by the delegation relation. It is not clear how to address such a complex object as a single entity. Also, the existence of a large number of small objects that communicate by message passing may impose severe performance penalties.

Implementation techniques -- Self

A major concern of software developers is (often) the runtime efficiency of the system developed. An order of magnitude difference in execution speed may, indeed, mean the difference between acceptance and rejection.

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Improving performance

• special-purpose hardware
• hybrid languages
• static typing
• dynamic compilation

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slide: Improving performance

---

There are a number of ways in which to improve on the runtime efficiency of programs, including object-oriented programs. For example,  [Ungar92] mention the reliance on special-purpose hardware (which thus far has been rapidly overtaken by new general-purpose processor technology), the use of hybrid languages (which are considered error-prone), static typing (which for object-oriented programming provides only a partial solution) and dynamic compilation (which has been successfully applied for Self). See slide 5-opt. As for the use of hybrid languages, of which C++ is an example, the apparent impurity of such an approach may (to my mind) even be beneficial in some cases. However, the programmer is required to deal more explicitly with the implementation features of the language than may be desirable. In general, both with respect to reliability and efficiency, statically typed languages have a distinct advantage over dynamically typed (interpreted) languages. Yet, for the purpose of fast prototyping, interpreted languages (like Smalltalk) offer an advantage in terms of development time and flexibility. Moreover, the use of (polymorphic) virtual functions and dynamic binding necessitate additional dynamic runtime support (that is not needed in strictly procedural languages). Clever compilation reduces the overhead (even in the case of multiple inheritance) to one or two additional indirections.

Dynamic compilation

The language Self is quite pure and simple in design. It supports objects with slots (that may contain both values and code, representing methods), shallow cloning, and implicit delegation (via a designated parent slot). Moreover, the developers of Self have introduced a number of techniques to improve the efficiency of prototype-based computing.

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Self -- prototypes

• - objects, cloning, delegation

Dynamic compilation -- type information

• customized compilation
• message inlining
• lazy compilation
• message splitting

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slide: Dynamic compilation -- Self

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The optimization techniques are based on dynamic compilation, a technique that resembles the partial evaluation techniques employed in functional and logic programming. Dynamic compilation employs the type information gathered during the computation to improve the efficiency of message passing.

Whenever a method is repeatedly invoked, the address of the recipient object may be backpatched in the caller. In some cases, even the result may be inlined to replace the request. Both techniques make it appear that message passing takes place, but at a much lower price. More complicated techniques, involving lazy compilation (by delaying the compilation of infrequently visited code) and message splitting (involving a dataflow analysis and the reduction of redundancies) may be applied to achieve more optimal results.

Benchmark tests have indicated a significant improvement in execution speed (up to 60% of optimized C code) for cases where type information could be dynamically obtained. The reader is referred to  [Ungar92] for further details.

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Meta-level architectures

Another weakness of the classical object model (or perhaps one of its strengths) is that the concept of a class easily lends itself to being overloaded with additional meanings and features such as class variables and metaclasses. These notions lead to extensions to the original class/instance scheme that are hard to unify in a single elegant framework. In this section we will study a proposal based on a reflexive relation between classes and objects. Depending on one's perspective, a class may either be regarded as a kind of abstract data type (specifying the operational interface of its object instances) or, more pragmatically, as a template for object creation (that is, a means to generate new instances).

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The class concept

• abstract data type -- interface description
• object generator -- template for creation
• repository -- for sharing resources
• object -- instance of a metaclass

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slide: The concept of class

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In addition, however, in a number of systems A class may be used as a repository for sharing class-wide resources. For example, the Smalltalk language allows the definition of class variables that are accessible to all instances of the class. See slide 5-class.

Class variables

Clearly, the use of class variables violates what we have called the distribution boundary in section multi-paradigm, since it allows objects to reach out of their encapsulation borders. Class variables may also be employed in C++ and Java by defining data members as static. Apart from class variables, Smalltalk also supports the notion of class methods, which may be regarded as routines having the class and its instances as their scope. Class methods in Smalltalk are typically used for the creation and initialization of new instances of the class for which they are defined. In C++ and Java, creation and initialization is taken care of by the constructor(s) of a class, together with the (system supplied) new operator. Class methods, in C++ and Java, take the form of static member functions that are like ordinary functions (apart from their restricted scope and their calling syntax, which is of the form $class::member(...)$ in C++ and $class.member(...)$ in Java). Contrary to classes in C++ and Java, classes in Smalltalk have a functionality similar to that of objects. Classes in Smalltalk provide encapsulation (encompassing class variables and class methods) and message passing (for example for the creation and initialization of new instances). To account for this object-like behavior, the designers of Smalltalk have introduced the notion of metaclass of which a class is an instance.

Metaclasses

In the classical object model, two relations play a role when describing the architectural properties of a system. The first relation is the instance relation to indicate that an object O is an instance of a class C. The second (equally important) relation is the inheritance relation, which indicates that a class C is a subclass (or derived from) a given (ancestor) class P. When adopting the philosophy everything is an object together with the idea that each object is an instance of a class (as the developers of Smalltalk did), we evidently get into problems when we try to explain the nature (and existence) of a class.

To be an object, a class itself must be an instance of a class (which for convenience we will call a metaclass). Take, for example, the class Point. This class must be an instance of a (meta)class (say Class) which in its turn must be an instance of a (meta) class (say MetaClass), and so on. Clearly, following the instance relation leads to an infinite regress. Hence, we must postulate some system-defined MetaClass (at a certain level) from which to instantiate the (metaclasses of) actual classes such as Point.

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slide: Meta architectures

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The figure in slide meta-architecture(a) is a (more or less) accurate rendering of the solution provided by Smalltalk. We may add additional flexibility by allowing user-defined metaclasses that may refine the behavior of the system-defined metaclass Class. This is the solution chosen for Loops, see  [LOOPS]. Thus far we have traced the instance relation which leads (following the reversed arrows) from top to bottom, from metaclasses to actual object instances. As pictured in the diagram (a) above, the inheritance relation (followed in the same manner) goes in exactly the opposite direction, having the class Object at the root of the inheritance hierarchy. For example, the class Point (while being an instance of the metaclass Class) is derived by inheritance from the class Object. Similarly, the (meta)class Class itself inherits from the class Object, and in its turn the system-defined metaclass MetaClass inherits from Class. As for the user-defined metaclasses, these may be thought of as inheriting from the system-defined metaclass Class. Apart from being slightly confusing, Smalltalk's meta-architecture is rather inelegant due to the magic (that is system-defined) number of meta levels. In the following, we will study a means to overcome this inelegancy.

Reflection

 [Cointe87] proposes an architecture that unifies the notions of object, class and metaclass, while allowing metaclasses to be defined at an arbitrary level. The key to this solution lies in the postulates characterizing the behavior of an object-oriented system given in slide 5-postulates.

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Postulates -- class-based languages

• everything is an object
• every object belongs to a class
• every class inherits from the class Object
• class variables of an object are instance variables of its class

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slide: Class-based languages -- postulates

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The first three postulates are quite straightforward. They agree with the assumptions underlying Smalltalk. The last postulate, however, stating that a class variable of an object must be an instance variable of the objects class (taken as an object), imposes a constraint of a self-recurrent or reflexive nature. This recurrence is pictured in slide meta-architecture(b), which displays the object Class as an instance of itself (that is the class Class). In other respects, the diagram is similar to the diagram depicting the (meta) architecture of Smalltalk and Loops. To indicate how such a reflective relation may be implemented,  [Cointe87] introduces a representation of objects involving the attributes name (to indicate the class of the object), supers (to indicate its ancestor(s)), iv (to list the instance variables of the object) and methods (to store the methods belonging to the object). In this scheme of representation, the system-defined metaclass Class is precisely the object reflecting its own structure in the values of its attributes, as depicted above. Every instance of Class may assign values to its instance variables (contained in iv) that are appropriate to the instances that will be created from it. In general, a metaclass is an object having at least the attributes of Class (and possibly more). See slide 5-reflex-class.

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Reflective definition of Class

   name         Class
   supers      (Object)
   iv     (name supers iv methods)
   methods      (new ...)
  

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slide: A reflective definition of Class

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Using this scheme, an arbitrary towering of metaclasses may be placed on top of concrete classes, thus allowing the software developer to squeeze out the last bit of differential programming. Elegant indeed, although it is doubtful whether many programmers will endeavor upon such a route. A nice example of employing (customized) metaclasses, however, is given in  [Malenfant89], where metaclasses are used to define the functionality of distribution and communication primitives employed by concrete classes.

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Summary

object-oriented programming

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This chapter presented an overview of object-oriented programming languages. We discussed the heritage of Simula and the various areas of research and development the ideas introduced by Simula has generated.

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The object paradigm

1

• notion of object -- viewpoints
• classification -- object extensions

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slide: Section 5.1: The object paradigm

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An overview of existing object-oriented languages was given in section 1 and we noted the prominence of hybrid languages derived from Lisp and C.

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Comparing Smalltalk, Eiffel, C++ and Java

2

• criteria -- libraries, environments, language characteristics
• comparison -- language characteristics

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slide: Section 5.2: Comparing Smalltalk, Eiffel, C++ and Java

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In section 2, we looked at a comparison of Smalltalk, Eiffel, C++ and Java, including criteria such as the availability of libraries, programming environments and language characteristics.

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Design dimensions of object-oriented languages

3

• {\em object-oriented} -- object-based + inheritance
• orthogonal dimensions -- objects, types, delegation, abstraction
• open systems -- dimensions of modularity

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slide: Section 5.3: Design dimensions of object-oriented languages

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In section 3, we discussed the design dimensions of object-oriented languages and characterized an orthogonal set of dimensions consisting of objects, types, delegation and abstraction. We also discussed the notion of open systems and multi-paradigm languages combining logic programming with object-oriented features.

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Prototypes -- delegation versus inheritance

4

• prototypes -- cloning and delegation
• performance -- dynamic compilation

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slide: Section 5.4: Prototypes -- delegation versus inheritance

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In section 4, we dealt with classless prototype-based languages, supporting dynamic delegation instead of inheritance. We also discussed performance issues and observed that dynamic compilation based on runtime type information may achieve good results.

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Meta-level architectures

5

• class -- the concept of class
• meta architecture -- subclass and instance hierarchy
• reflection -- postulates

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slide: Section 5.5: Meta-level architectures

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Finally, in section 5, we reflected on the concept of class and discussed a reflective architecture unifying the interpretation of a class as an object, capable of answering messages, and as a description of the properties of its instances.

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Questions

1. What are the basic characteristics of object-oriented languages?
2. How would you classify object-oriented languages? Name a few representatives of each category.
3. What do you consider to be the major characteristic of the object model supported by C++? Explain.
4. Why would you need friends?
5. How would you characterize the difference between object-based and object-oriented?
6. Along what orthogonal dimensions would you design an object-oriented language? Explain.
7. Give a characterisation of active objects. In what situations may active objects be advantageous?
8. How would you characterize prototype-based languages?
9. What are the differences between inheritance and delegation? Does C++ support delegation? Explain. And Java?
10. How would you characterize the concept of a class?
11. Can you sketch the meta architecture of Smalltalk?
12. How would you phrase the postulates underlying class-based languages? Can you give a reflective version of these postulates?

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Further reading

A concise treatment of programming languages is given in  [BG94]. For a collection of papers on object-oriented concepts, see  [KL89]. Further, you may want to consult  [Wegner87], which contains the original presentation of the discussion concerning the distinction between {\em object-based} and {\em object-oriented}. Concurrency is studied in  [AWY93]. For Java, read the original white paper,  [Java]. An interesting extension of C++ is described in  [Petitpierre98]. At the corresponding web site, ltiwww.epfl.ch/sCxx , there is much additional material. Finally, for an account of the design and evolution of C++, read  [Stroustrup97]. For more information on C++, visit www.accu.org , and for Java, www.javasoft.com .

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(C) Æliens 04/09/2009

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