Multi-model Environment Generation and Tailoring Model for Software Process Improvement

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Abstract

Software development organizations take great risks when are faced with process improvement projects and the inclusion of best practices. Such risks include the selection of a standard, framework or model for the improvement process. Some organizations decide to integrate best practices from different sources to be non-dependent on a particular model, framework or standard. However, the integration of different models is an additional challenge since the complexity of the implementation increases as best practices come from different natures. Hence, we propose a model to generate and customize a multi-model environment for software process improvement. We intend to reduce the complexity of combining agile and traditional frameworks by generating a frameworks integration catalog, which, from heuristics, graphically represents the possible paths to follow for the process improvement project. We use design-based science for this research because of its focus on problem analysis in real-world environments. In this way, we can consolidate the model to customize and generate a multi-model environment for the implementation of best practices of different nature during an improvement process. We also define a proposal of organizational profiles, which will allow us to validate the model in a business case in future work.

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APA

Gasca-Hurtado, G. P., Londoño, J. A. H., & Muñoz, M. (2020). Multi-model Environment Generation and Tailoring Model for Software Process Improvement. In Advances in Intelligent Systems and Computing (Vol. 1159 AISC, pp. 620–630). Springer. https://doi.org/10.1007/978-3-030-45688-7_62

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