Modeling and Selection of Interdependent Software Requirements using Fuzzy Graphs
This work addresses software requirement selection for project managers by considering interdependent requirements, though it is incremental as it builds on existing models by incorporating dependency strengths.
The paper tackles the problem of selecting software requirements by developing a cost-value optimization model that accounts for value-related dependencies and their varying strengths, which existing models ignore, and validates it through simulations and a real-world project.
Software requirement selection is to find an optimal set of requirements that gives the highest value for a release of software while keeping the cost within the budget. However, value-related dependencies among software requirements may impact the value of an optimal set. Moreover, value-related dependencies can be of varying strengths. Hence, it is important to consider both the existence and the strengths of value-related dependencies during a requirement selection. The existing selection models however, either assume that software requirements are independent or they ignore strengths of requirement dependencies. This paper presents a cost-value optimization model that considers the impacts of value-related requirement dependencies on the value of selected requirements (optimal set). We have exploited algebraic structure of fuzzy graphs for modeling value-related requirement dependencies and their strengths. Validity and practicality of the work are verified through carrying out several simulations and studying a real world software project.