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Abstract
One of the critical activities in software development is Requirements Selection, which is to find an optimal subset of the software requirements (features) with the highest value for a given budget. The values of the requirements, however, may depend on one another. Such Value Dependencies have not been considered by the existing requirements selection methods, leading to user dissatisfaction and loss of value and reputation in software projects. To mitigate this, we propose Dependency-Aware Requirements Selection (DARS) as an expert system, which explicitly accounts for value dependencies in software projects. At the heart of DARS is an Integer Linear Programming (ILP) model that reduces the risk of value loss by considering value dependencies among the requirements. These value dependencies are identified from the preferences of the users for the requirements. The validly of DARS is verified by studying a real-world software project as well as carrying out simulations. O