Experience-based model-driven improvement management with combined data sources from industry and academia

Experience-based improvement using various modeling techniques is an important issue in software engineering. Many approaches have been proposed and applied in both industry and academia, e.g., case studies, pilot projects, controlled experiments, assessments, expert opinion polls, experience bases, goal-oriented measurement, process modeling, statistical modeling, data mining, and simulation. Although these approaches can be combined and organized according to the principles of the quality improvement paradigm (QIP) and the associated experience factory (EF) concepts, there are serious problems with: a) effective and efficient integration of the various approaches; and, b) the exchange of experience and data between industry and academia. In particular, the second problem strongly limits opportunities for joint research efforts and cross-organizational synergy. Based upon lessons learned from large-scale European joint research initiatives involving both industry and academia, this paper proposes the vision of an integrated software process improvement framework that facilitates solutions to the problems mentioned above.