Runtime adaptive systems are able to dynamically transform their internal structure, and hence their behavior, in response to internal or external changes. Such transformations provide the basis for new functionalities or improvements of the non-functional properties that match operational requirements and standards. Software Product Line Engineering (SPLE) has introduced several models and mechanisms for variability modeling and management. Dynamic software product lines (DSPL) engineering exploits the knowledge acquired in SPLE to develop systems that can be context-aware, post-deployment recon¯gurable, or runtime adaptive. This paper focuses on DSPL engineering approaches for developing runtime adaptive systems and proposes a framework for classifying and comparing these approaches from two distinct perspectives: adaptation properties and adaptation realization. These two perspectives are linked together by a series of guidelines that help to select a suitable adaptation realization approach based on desired adaptation types.

No abstract

No abstract

In the software product line configuration process, certain features are selected based on the stakeholders' needs and preferences regarding the available functional and quality properties. This book chapter presents how a product configuration can be modeled as a decision process and how an optimal strategy representing the stakeholders' desirable configuration can be found. In the decision process model of product configuration, the product is configured by making decisions at a number of decision points. The decisions at each of these decision points contribute to functional and quality attributes of the final product. In order to find an optimal strategy for the decision process, a utility-based approach can be adopted, through which, the strategy with the highest utility is selected as the optimal strategy. In order to define utility for each strategy, a multi-attribute utility function is defined over functional and quality properties of a configured product and a utility elicitation process is then introduced for finding this utility function. The utility elicitation process works based on asking gamble queries over functional and quality requirement from the stakeholder. Using this utility function, the optimal strategy and therefore optimal product configuration is determined.

No abstract