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Evolutionary robust optimization for software product line scoping: An explorative study

, and . Computer Languages, Systems & Structures, 47 (2): 189-210 (2017)

Abstract

Background: Software product line (SPL) scoping is an important phase when planning for product line adoption. An SPL scope specifies: (1) the extent of the domain supported by the product line, (2) portfolio of products in the product line and (3) list of assets to be developed for reuse across the family of products. Issue: SPL scope planning is usually based on estimates about the state of the market and the engineering capabilities of the development team. One challenge with these estimates is that there are inaccuracies due to uncertainty in the environment or accuracy of measurement. This may result in issues ranging from suboptimal plans to infeasible plans. Objective: To address the above, we propose to include uncertainty as part of the SPL scoping model. Plans developed in consideration of uncertainty would be more robust against possible fluctuations in estimates. Approach: In this paper, a method to incorporate uncertainty in scoping optimization and its application to generate robust solutions is proposed. We capture uncertainty as part of the formulation and model scoping optimization as a multi-objective problem with profit and stability as fitness functions. Profit stability and feasibility stability are considered to represent stability concerns. Results: Results show that, compared to other scope optimization approaches, both performance stability and feasibility stability are improved while maintaining near optimal performance for profit objective. Also, generated results consist of solutions with trade-offs between profit and stability, providing the decision maker with enhanced decision support. Conclusion: Multi-objective optimization with stability consideration for SPL scoping provides project managers with a robust and flexible way to address uncertainty in the process of SPL scoping.

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