| Hi-index | 0.00 |
Software maintenance effort constitutes a major portion of the software lifecycle effort. Its estimation is vital for successful project planning and strategic resource allocation. In this paper, we conduct and report an industrial case study in this field. The data set was collected from an industrial software process management tool QONE (formerly SoftPM). The methodology proposed provides corresponding guidance for effort estimation in software evolutionary projects that employ use-cases in capturing maintenance requirements. And the model, constructed using the linear regression analysis and validated by the leave-one-out cross-validation, provides an effort prediction for the future maintenance of the project. The analysis results indicate that the methodology can be applied at an early stage of the project life cycle and provides a good tradeoff among simplicity, early-estimating and accuracy in one estimate.