An Integrated Approach for Identifying Relevant Factors Influencing Software Development Productivity
This addresses the challenge of selecting relevant factors for productivity improvement in software organizations, though it appears incremental as it builds on existing data- and expert-based methods.
The paper tackled the problem of identifying key factors affecting software development productivity by proposing an integrated method combining data analysis and expert judgment, which improved effort estimation accuracy and precision compared to individual approaches.
Managing software development productivity and effort are key issues in software organizations. Identifying the most relevant factors influencing project performance is essential for implementing business strategies by selecting and adjusting proper improvement activities. There is, however, a large number of potential influencing factors. This paper proposes a novel approach for identifying the most relevant factors influencing software development productivity. The method elicits relevant factors by integrating data analysis and expert judgment approaches by means of a multi-criteria decision support technique. Empirical evaluation of the method in an industrial context has indicated that it delivers a different set of factors compared to individual data- and expert-based factor selection methods. Moreover, application of the integrated method significantly improves the performance of effort estimation in terms of accuracy and precision. Finally, the study did not replicate the observation of similar investigations regarding improved estimation performance on the factor sets reduced by a data-based selection method.