Abstract
Global Software Development (GSD) projects comprise several critical cost drivers that affect the overall project cost and budget overhead. Thus, there is a need to amplify the existing model in GSD context to reduce the risks associated with cost overhead. Motivated by this, the current work aims at amplifying the existing algorithmic model with GSD cost drivers to get efficient estimates in the context of GSD. To achieve the targeted research objective, current state-of-the-art cost estimation techniques and GSD models are reported. Furthermore, the current study has proposed a conceptual framework to amplify the algorithmic COCOMO-II model in the GSD domain to accommodate additional cost drivers empirically validated by a systematic review and industrial practitioners. The main phases of amplification include identifying cost drivers, categorizing cost drivers, forming metrics, assignment of values, and finally altering the base model equation. Moreover, the proposed conceptual model's effectiveness is validated through expert judgment, case studies, and Magnitude of Relative Estimates (MRE). The obtained estimates are efficient, quantified, and cover additional GSD aspects than the existing models; hence we could overcome the GSD project's overall risk by implementing the model. Finally, the results indicate that the model needs further calibration and validation.
Highlights
As technology advances, the globalization of software companies increases
Software industries are moving towards Global Software Development (GSD) to provide a cost-effective software solution
We have identified the Critical Cost Drivers (CCDs) of GSD and amplified the model
Summary
The globalization of software companies increases. Software industries are moving towards Global Software Development (GSD) to provide a cost-effective software solution. The prior studies predict that the number of GSD projects will increase over time. The primary purpose of adopting GSD is the low labor cost, whereas it provides many other advantages like time to market and access to vast skills through virtual teams [3]. One of the main reasons behind the failure of GSD projects is the lack of consideration of the additional cost drivers of GSD. As in GSD, the development is carried out through remote locations with high geographic, cultural, and time zone differences. The existing work lacks in considering the additional cost drivers of GSD. Current research focuses on providing a GSD-specific cost estimation model based on the additional cost drivers of GSD to provide more accurate and.
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