From Procedures, Objects, Actors, Components, Services, to Agents -- A Comparative Analysis of the History and Evolution of Programming Abstractions
Jean-Pierre Briot
TL;DR
This work presents a historical and conceptual comparison of programming abstractions from procedures and objects to agents, within a three-axis framework: action selection, coupling flexibility, and abstraction level. It contrasts static, early invocation models with dynamic, autonomous coordination found in services and multi-agent systems, emphasizing late binding, explicit connectors, and knowledge-based design. By detailing reification, interoperability languages, and organizational design, the paper shows how abstractions advance toward self-adaptive, configurable architectures. The contribution is a unified lens for reasoning about future programming abstractions and for enabling cross-model reuse in distributed, autonomous software systems.
Abstract
The objective of this chapter is to propose some retrospective analysis of the evolution of programming abstractions, from {\em procedures}, {\em objects}, {\em actors}, {\em components}, {\em services}, up to {\em agents}, %have some compare concepts of software component and of agent (and multi-agent system), %The method chosen is to by replacing them within a general historical perspective. Some common referential with three axes/dimensions is chosen: {\em action selection} at the level of one entity, {\em coupling flexibility} between entities, and {\em abstraction level}. We indeed may observe some continuous quest for higher flexibility (through notions such as {\em late binding}, or {\em reification} of {\em connections}) and higher level of {\em abstraction}. Concepts of components, services and agents have some common objectives (notably, {\em software modularity and reconfigurability}), with multi-agent systems raising further concepts of {\em autonomy} and {\em coordination}. notably through the notion of {\em auto-organization} and the use of {\em knowledge}. We hope that this analysis helps at highlighting some of the basic forces motivating the progress of programming abstractions and therefore that it may provide some seeds for the reflection about future programming abstractions.
