Using Bayesian Networks to estimate Strategic Indicators in the context of Rapid Software Development
Martí Manzano, Emília Mendes, Cristina Gómez, Claudia P. Ayala, Xavier Franch · 2018
Background: During Rapid Software Development, a large amount of project and development data can be collected from different and heterogeneous data sources. Aims: Design a methodology to process these data and turn it into relevant strategic indicators to help companies make meaningful decisions. Method: We adapt an existing methodology to create and estimate strategic indicators using Bayesian Networks in the context of Rapid Software Development, and applied it to a use case. Results: Applying the methodology in the use case, we create a model to predict product quality based on software factors and metrics, using companies' business knowledge and collected data. Conclusions: We proved the methodology's feasibility and obtained positive feedback from the company's use case.