Bayesian Networks (BN) have been used for decision making in software engineering for many years. We investigate the current status of BNs in predicting software quality in
three aspects: 1) techniques used for parameter learning, 2) techniques used for structure learning, and 3) type of variables that represent BN nodes. We performed a systematic
mapping study on 38 primary studies that employed BNs to predict software quality. The most popular technique for building the nal structure of BNs is the use of expert
knowledge with dierent inference algorithms. Variables in BNs are treated as categorical in more than 70% of studies. Compared to other domains, the usage of BNs is still very
limited due to high dependency on expert knowledge and tools.
Misirli, A. T. (University of Oulu), Bener, A. B. (Ryerson University). A mapping study on bayesian networks for software quality prediction. In Proceedings of the 3rd International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering