The aim of this paper is to investigate if it is possible to build accurate Bayesian net models for software development effort and quality prediction under two assumptions for model generation: (1) no expert knowledge is incorporated, (2) only small local qualitative data is used. Models generated in this study provide predictions with medium level of accuracy, yet still keeping the literature average. Thus, they can be used to make only rough estimations at the early software development stage. However, they can be a useful base for detailed models incorporating expert knowledge and tailored for individual needs.
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