Abstract Selective Specialization for Object-Oriented Languages

Dynamic dispatching is a major source of run-time overhead in object-oriented languages, due both to the direct cost of method lookup and to the redirect effect of preventing other optimization. To reduce this overhead, optimizing compilers for object-oriented languages anrdyze the classes of objects stored in program variables, with the goal of bounding the possible classes of message receivers enough so that the compiler can uniquely determine the target of a message send at compile time and replace the message send with a direct procedure call. Specialization is one important technique for improving the precision of this static class information: by compelling multiple versions of a method, each applicable to a subset of the possible argument classes of the method, more precise static information about the classes of the method’s arguments is obtained. Previous specialization strategies have not been selective about where this technique is applied, and therefore tended to significantly increase compile time and code space usage, particularly for large applications. In this paper, we present a more genertd framework. for speciahzation in object-oriented languages and describe a goaldirected specialization rdgorithm that makes selective decisions to apply specialization to those cases where it provides the highest benefit. Our results show that our algorithm improves the performance of a group of sizeable programs by 657. to 275 % while increasing compiled code space requirements by only 4~o to 10%. Moreover, when compared to the previous state-of-the-art specialization scheme, our algorithm improves performance by 11YO to 67 % while simultaneously reducing code space requirements by 65 % to 73%.