Multiple dispatching provides increased expressive power over single dispatching by guiding method lookup using the values of all arguments instead of only the receiver. However, existing languages with multiple dispatching do not encourage the dataabstraction-oriented programming style that is encouraged by traditional single-dispatching languages; instead existing multiple-dispatching languages tend to foster a functionoriented programming style organized around generic functions. We propose an alternative view of multiple dispatching that is intended to promote a data-abstraction-oriented programming style. Instead of viewing a multi-method as “outside ” of all objects, we view a multi-method as “inside ” the objects for which the multi-method applies (on which it dispatches). Because objects are closely connected to the multi-methods implementing their operations, the internals of an object can be encapsulated by being accessible only to the closely-connected multi-methods. We are exploring this object-oriented view of multimethods in the context of a new programming language named Cecil.

Object-oriented programming languages promise to improve programmer productivity by supporting abstract data types, inheritance, and message passing directly within the language. Unfortunately, traditional implementations of object-oriented language features, particularly message passing, have been much slower than traditional implementations of their non-object-oriented counterparts: the fastest existing implementation of Smalltalk-80 runs at only a tenth the speed of an optimizing C implementation. The dearth of suitable implementation technology has forced most object-oriented languages to be designed as hybrids with traditional non-object-oriented languages, complicating the languages and making programs harder to extend and reuse. This dissertation describes a collection of implementation techniques that can improve the run-time performance of object-oriented languages, in hopes of reducing the need for hybrid languages and encouraging wider spread of purely object-oriented langu...

. Predicate classes are a new linguistic construct designed to complement normal classes in objectoriented languages. Like a normal class, a predicate class has a set of superclasses, methods, and instance variables. However, unlike a normal class, an object is automatically an instance of a predicate class whenever it satisfies a predicate expression associated with the predicate class. The predicate expression can test the value or state of the object, thus supporting a form of implicit property-based classification that augments the explicit type-based classification provided by normal classes. By associating methods with predicate classes, method lookup can depend not only on the dynamic class of an argument but also on its dynamic value or state. If an object is modified, the property-based classification of an object can change over time, implementing shifts in major behavior modes of the object. A version of predicate classes has been designed and implemented in the context of t...

Cecil is a new purely object-oriented language intended to support rapid construction of highquality, extensible software. Cecil combines multi-methods with a classless object model, object-based encapsulation, and optional static type checking. Cecil's static type system distinguishes between subtyping and code inheritance, but Cecil enables these two graphs to be described with a single set of declarations, optimizing the common case where the two graphs are parallel. Cecil includes a fairly flexible form of parameterization, including both explicitly parameterized objects, types, and methods and implicitly parameterized methods related to the polymorphic functions commonly found in functional languages. By making type declarations optional, Cecil aims to support mixed exploratory and production programming styles. This document describes the design of the Cecil language as of March, 1993. It mixes the specification of the language with discussions of design issues and explanations of...

Object-oriented programming languages confer many benefits, including abstraction, which lets the programmer hide the details of an object’s implementation from the object’s clients. Unfortunately, crossing abstraction boundaries often incurs a substantial run-time overhead in the form of frequent procedure calls. Thus, pervasive use of abstraction, while desirable from a design standpoint, may be impractical when it leads to inefficient programs. Aggressive compiler optimizations can reduce the overhead of abstraction. However, the long compilation times introduced by optimizing compilers delay the programming environment‘s responses to changes in the program. Furthermore, optimization also conflicts with source-level debugging. Thus, programmers are caught on the horns of two dilemmas: they have to choose between abstraction and efficiency, and between responsive programming environments and efficiency. This dissertation shows how to reconcile these seemingly contradictory goals by performing optimizations lazily. Four new techniques work together to achieve high performance and high responsiveness: • Type feedback achieves high performance by allowing the compiler to inline message sends based on information extracted from the runtime system. On average, programs run 1.5 times faster than the previous SELF system; compared to a commercial Smalltalk implementation, two medium-sized benchmarks run about three times faster. This level of performance is obtained with a compiler that is both simpler and faster than previous SELF compilers. • Adaptive optimization achieves high responsiveness without sacrificing performance by using a fast nonoptimizing compiler to generate initial code while automatically recompiling heavily used parts of the program with an optimizing compiler. On a previous-generation workstation like the SPARCstation-2, fewer than 200 pauses exceeded 200 ms during a 50-minute interaction, and 21 pauses exceeded one second. On a currentgeneration workstation, only 13 pauses exceed 400 ms. • Dynamic deoptimization shields the programmer from the complexity of debugging optimized code by transparently recreating non-optimized code as needed. No matter whether a program is optimized or not, it can always be stopped, inspected, and single-stepped. Compared to previous approaches, deoptimization allows more debugging while placing fewer restrictions on the optimizations that can be performed. • Polymorphic inline caching generates type-case sequences on-the-fly to speed up messages sent from the same call site to several different types of object. More significantly, they collect concrete type information for the optimizing compiler. With better performance yet good interactive behavior, these techniques make exploratory programming possible both for pure object-oriented languages and for application domains requiring higher ultimate performance, reconciling exploratory programming, ubiquitous abstraction, and high performance.

Moderne softwaresystemen zijn dikwijls zo complex dat ze niet slechts één probleem oplossen maar zich toespitsen op het oplossen van fundamenteel verschillende deelproblemen. De ervaring van de laatste decennia leert ons dat niet alle programmeerproblemen op expressieve wijze met eenzelfde taal opgelost kunnen worden. Programmeurs zijn productiever wanneer zij de taal gebruiken die het best geschikt is voor het oplossen van het probleem dat zich voordoet. Maar in het grotere geheel van een softwaresysteem zullen deze delen die in verschillende talen ontwikkeld zijn, uiteindelijk moeten samenwerken. Om die reden zijn er verschillende technieken ontwikkeld om zulke taalinteroperabiliteit te bekomen. Sommige van deze technieken zijn ontwikkeld om de betrokken talen zo nauw mogelijk met elkaar te laten samenwerken, zodat eigenschappen van de ene taal op een transparante manier in de andere taal gebruikt kunnen worden, zodanig dat zij in een taalsymbiose verkeren. Programmeertalen worden onderverdeeld in programmeerparadigma’s,

Classes are problematic in pervasive computing --- systems we call "processor clouds" --- where computers appear and disappear dynamically in a network. Problems with classes are mainly due to the dynamically distributed nature of these systems. The root cause of the problems is that the classinstance relationship is implicit. Two main manifestations are: state sharing vs. distribution conflicts, and inefficiencies caused by the binding of classes and their transitive closure to objects. The latter is worse in the case of statically typed languages.