Detection and Impact Analyses of Feature Interactions

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A common strategy for dealing with the complexity of large software systems is to decompose the system into smaller sub-systems that can be tackled more easily. Feature-based decomposition is a type of functional decomposition, in which features are units of functionality that can be considered, developed, and evolved independently. Because features provide distinct functionalities, they represent distinct development tasks that can be added incrementally, performed by separate teams in parallel, or outsourced to third-party vendors. Features may be optional or even tariffable, thereby allowing for mass customization of products through product-lining. The downside of feature-based decomposition is unexpected feature interactions, in which the actions of one feature interfere with those of another, leading to conflicts, emergent functional behaviours, and possibly artificial contagion to other features and systems.****This project investigates four complementary analyses that enable efficient reasoning about feature interactions and feature evolution: (1) Lightweight static analyses that enable engineers to perform a system-wide analysis of all features, and identify potential feature interactions that can lead to safety hazards; (2) scalable dynamic analyses and (3) compositional code-level analyses that allow checking whether one feature implementation can be substituted for another without affecting the overall system behaviour; and (4) product-line analyses that enable engineers to analyze and verify multiple feature configurations simultaneously and efficiently, making it possible offer a larger selection of customized products to the public. The expected outcomes of the proposed work are a collection of computer-supported methods and techniques for analyzing potential and realized interactions among features expressed in different software-development artifacts. The tools will be evaluated with respect to their effectiveness in detecting interactions and their scalability to large software systems, and will be evaluated in part on software artifacts from our industrial partner.******