Software Product Lines are a strategic long-term investment and must evolve to meet new requirements over many years. In previous work, we have shown a model-driven approach (called EvoPL [21]) for planning and managing long-term evolution of product lines. It allows specifying historic and planned future evolution in terms of changes on feature model level. It provides benefits like abstraction, efficiency through automation, and the capability to perform analysis based on models.In this paper, we argue that specifying changes alone is beneficial but not sufficient. This is because for strategic evolution planning "decision drivers" like goals, requirements, and rationale are essential information as well.Hence, we propose a modeling approach that represents such decision drivers and their interrelationships. The approach is based on concepts from literature (e.g., QOC and goal-oriented requirements engineering) and combines and extends them to address the specific needs of model-driven long-term evolution management. Beyond the basic usage for documentation, the suggested models can be used for systematic future planning and tool-supported analysis, e.g., to evaluate the consistency of planned evolutionary changes.

In order to increase the level of efficiency and automation, we propose a conceptual model and corresponding tool support to plan and manage the systematic evolution of softwareintensive systems, in particular software product lines (SPL). We support planning on a high abstraction level using decision-making concepts like goals, options, criteria, and rationale. We extend earlier work by broadening the scope in two dimensions: 1) in time, supporting continuous planning over long periods of time and many releases, and 2) in space, supporting traces from high-level decisions down to the implementation. We present a metamodel which allows to represent these concepts, corresponding prototypical tool support, and a first example case using data extracted from an open-source project, Eclipse SWT.

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