Model-based dynamic cost estimation and tracking method for agile software development

Abstract

In this paper, we present a software cost estimation model for agile development which can help estimate concrete development costs for the desired features of a product and track the project progress dynamically. In general, existing cost estimation methods for agile developments used a story point. Because it is relative value, the estimation results tend to be easily fluctuated by the small variation of the baseline story point. For tracking project’s progress, the velocity was measured to check the progress and was used to make plan for the iteration and the releases of the project. The proposed method in this paper provides the systematic estimation and dynamic tracking methodology for agile projects. To estimate the effort of a project development, function points are used in addition to the story point. The function points are determined based on the user stories of desired features of the product. We adopt the Kalman filter algorithm for tracking project progress. The remaining function points at a certain point during the project are modeled as the state space model for the Kalman filter. The daily variation of the function point is observed and inputted to the Kalman Filter for providing concrete estimation and velocity. Moreover we validate the better performance of our model by comparing with traditional methods through a case study.