Graduate Talks

 

PhD Presentation

Cosmin Oancea

Parametric Polymorphism for Software Component Architectures

 

Date:
Time:
Place:
Supervisor:
Thesis Examiners:

Extra-Departmental
Examiner:
External Examiner:
Tuesday, November 01, 2005
9:30 a.m.
Middlesex College, Room 320
Dr. Stephen Watt
Dr. Hanan Lutfiyya
Dr. Marc Moreno Maza

Martin Mueser (Applied Mathematics)
Nigel Horspool (Univ. of Victoria)

 

Abstract:

Parametric polymorphism has become a common feature of mainstream programming languages, but software component architectures have lagged behind and do not support this feature. The immediate consequence is that applications cannot naturally combine the functionality exposed by various parameterized modules, if it happens that the implementation language differs. This significant problem surfaced first and most acutely in the computer algebra community, where parametric polymorphism is heavily used for the specification and enforcement of the algebraic interfaces and in the implementation of algorithms that work over various coefficient rings or fields. Complex, specialized mathematical libraries, servicing disjoint areas are implemented in various languages and therefore they cannot yet work together to attack increasingly difficult problems. This thesis examines the problem of accommodating parametric polymorphism, and related optimizations in a multi-language, distributed setting. We report on a first experiment, where we developed the Alma framework that allows Aldor libraries to extend Maple in a effective and natural way, and constitutes a new approach to structuring computer algebra systems. The motivation for this experiment are twofold: First, we are interested in understanding the issues that arise in matching the compile-time parametric polymorphism of Aldor's dependent types with the dynamic parametric polymorphism of Maple's module-producing functions, and in matching the Aldor's strongly type system with Maple's dynamically typed system. Second, we are interested in the practical problem of using Aldor as an extension mechanism for the popular Maple computer algebra system. The details of generics, templates or functors, as they are variously called, differ significantly in different programming languages. We investigated how to resolve different binding times and parametric polymorphism semantics in a range of representative programming languages, and identified a common ground that can be suitably mapped to different language bindings. We explore the possibility of a systematic solution for parametric polymorphism, that should encompass many languages in a simple way. We present a generic component architecture extension that provides support for parameterized components, and can be easily adapted to work on top of various software component architectures in use today: CORBA, JNI, DCOM. We have implemented and tested our extension on top of CORBA. We present Generic Interface Definition Language (GIDL), an extension to CORBA-IDL, supporting generic types, and our language bindings for C++, Java, and Aldor. We describe our implementation of GIDL, consisting of a GIDL to IDL compiler and tools for generating linkage code under the language bindings. GIDL captures a very general notion of parametric polymorphism such that it can meaningfully be supported by various languages, and has the power to model the structure and semantics of system's components. To test the effectiveness of our model for generics, we have investigated how to expose C++'s STL and Aldor's BasicMath libraries to a multi-language environment, and discuss our mappings in the context of automatic library interface generation. Our work in the context of exposing generic libraries to a multi-language, potentially distributed environment has revealed several performance issues. First, as different components are separately compiled, the traditional compiler optimizations, such as inlining and parallelization, will fail to perform aggressively. Second, the overhead introduced by the inter-process communication stalls can be quite significant. Finally, this thesis explores speculative optimizations in the attempt to speed up the application performance in distributed environments.

 

 

 

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