Design and use of software architectures: adopting and evolving a product-line approach
Design and use of software architectures: adopting and evolving a product-line approach
Applications of SHOP and SHOP2
IEEE Intelligent Systems
Software Product Lines in Action: The Best Industrial Practice in Product Line Engineering
Software Product Lines in Action: The Best Industrial Practice in Product Line Engineering
Selecting highly optimal architectural feature sets with Filtered Cartesian Flattening
Journal of Systems and Software
SHOP: simple hierarchical ordered planner
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Automated reasoning for multi-step feature model configuration problems
Proceedings of the 13th International Software Product Line Conference
Integrating Preferences into Goal Models for Requirements Engineering
RE '10 Proceedings of the 2010 18th IEEE International Requirements Engineering Conference
Automated reasoning on feature models
CAiSE'05 Proceedings of the 17th international conference on Advanced Information Systems Engineering
Towards product configuration taking into account quality concerns
Proceedings of the 16th International Software Product Line Conference - Volume 2
Light-weight software product lines for small and medium-sized enterprises (SMEs)
CASCON '13 Proceedings of the 2013 Conference of the Center for Advanced Studies on Collaborative Research
Hi-index | 0.00 |
In Software Product Line Engineering, concrete products of a family can be generated through a configuration process over a feature model. The configuration process selects features from the feature model according to the stakeholders' requirements. Selecting the right set of features for one product from all the available features in the feature model is a cumbersome task because 1) the stakeholders may have diverse business concerns and limited resources that they can spend on a product and 2) features may have negative and positive contributions on different business concern. Many configurations techniques have been proposed to facilitate software developers' tasks through automated product derivation. However, most of the current proposals for automatic configuration are not devised to cope with business oriented requirements and stakeholders' resource limitations. We propose a framework, which employs an artificial intelligence planning technique to automatically select suitable features that satisfy the stakeholders' business concerns and resource limitations. We also provide tooling support to facilitate the use of our framework.