An Algorithmic-Based Change Effort Estimation Model for Software Development

Software development mostly adopts two kinds of methodologies; Traditional and Agile. In both methodologies, software changes are inevitable due to the dynamic nature of the software development project itself. One of the factors that influences the effectiveness of the change acceptance decision is the accuracy of the change effort estimation. There are two current models that have been widely used to estimate change effort which are algorithmic and non-algorithmic models. The algorithmic model is known for its formal and structural way of estimation and best suited for Traditional methodology. While non-algorithmic model is widely adopted for Agile methodology of software projects due to its easiness and requires less work in term of effort predictability. Nevertheless, none of the existing change effort estimation models are proven to suit both, Traditional and Agile methodology. Thus, this paper proposes an algorithmic-based change effort estimation model that uses change impact analysis method which is applicable for both Traditional and Agile methodologies. The proposed model uses a current selected change impact analysis method for software development phase which is the SDP-CIAF (Software Development Phase-Change Impact Analysis Framework). The proposed model is evaluated through an extensive experimental validation using case scenarios of six real Traditional and Agile methodologies software projects. The evaluation results confirmed the applicability for both Traditional and Agile methodologies.

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