A Research Survey on the Applications of Artificial Intelligence Techniques To Product Line ModellingPosted: March 8, 2013
Research Paper Published in ICCET 2013 International Conference on Computers and Emerging Technologies, organized by Shah Abdul Latif University, Khairpur, Pakistan. An Excerpt from the paper is here :-
Software Product Line (SPL) is one of the well known software reusability approaches; it is an advanced concept to manage a family of configurable units of software under one umbrella using a reconfigurable and reusable software architecture. A major problem in SPL is the selection of the relevant set of features, in order to configure some product throught the configurable units. Each unit can support a diverse set of features. Combining features from each unit is a manual activity that requires a large amount of manual deliberation between the system designers. This approach is quite unsophisticated, in that it leads to a loss of resources (time, money etc.). In the current days, there is a strong need to automate this process to ensure a streamlined feature selection process. In this paper, we present a concrete survey on how artificial intelligence techniques have been applied to address the feature selection dilemma. We review several state-of-the-art papers, which particularly target techniques based on knowledge-based and logical reasoning. Our survey reveals a dearth of the application of optimization techniques to the feature selection problem. Besides genetic algorithms, we propose to extend the state of the art through the application of four state-of-the-art optimization techniques, i.e., Particle Swarm Optimization, Artificial Bee Colony, Ant Colony Optimization and Hill Climbing. We are currently running experiments in this regard on a pilot SPL.