A Commutative Model Composition Operator to Support Software Adaptation

Abstract

The adaptive software paradigm supports the definition of software systems that are continuously adapted at run-time. An adaptation activates multiple features in the system, according to the current execution context (e.g., CPU consumption, available bandwidth). However, the underlying approaches used to implement adaptation are ordered, i.e., the order in which a set of features are turned on or off matters. Assuming feature definition as etched in stone, the identification of the right sequence is a difficult and time-consuming problem. We propose here a composition operator that intrinsically supports the commutativity of adaptations. Using this operator, one can minimize the number of ordered compositions in a system. It relies on an action-based approach, as this representation can support preexisting composition operators as well as our contribution in an uniform way. This approach is validated on the Service-Oriented Architecture domain, and is implemented using first-order logic.

Incremental and Commutative Composition of State-Machine Models of Features

“…Other approaches such as DFC [13] and fSMV [14] use composition order to specify intended feature interactions, and this can result in unintended behaviour overrides. Commutative composition has been proposed in other SPL development paradigms such as in delta-modelling [15], aspectoriented programming [16] and action-based approaches [17]. In the feature-oriented software development paradigm, many existing approaches typically sacrifice commutativity for the sake of modelling intended interactions.…”

Towards Modelling Acceptance Tests as a Support for Software Measurement

“…According to the iterative and feature-driven approach emphasized by the DevOps paradigm, we define a product p ∈ P as the composition (⊕) of products increments δ i ∈ ∆ (i.e., features) to the empty product (∅ ∈ P) [27].…”

A delta‐oriented approach to support the safe reuse of black‐box code rewriters

“…As shown in the previous section, using this operator leads to scheduling issues, as it implies strong assumptions on the functions being commutative. We build here our contribution on top of two research results: PRAXIS and a parallel composition operator . These two approaches share in common the fact that instead of working on a model (here an AST), they rely on the sequence of elementary actions used to build it.…”