Application of Machine Learning in Software Quality: a Mini-review

The digital transformation underway in Sa-helian countries is accompanied by a growing interest in software engineering products in both the formal and informal sectors. The developed software mostly meet the needs of the customers, but it is not excluded that they suffer from compliance to the software quality standard. Thus, having intelligent systems that can assess whether important quality attributes are verified may be helpful. In this paper, we propose a mini-survey of different research works focusing on the improvement of software quality based on Machine Learning (ML) methods. The lessons learnt show that software quality management through ML methods is an active research field. Software defect prediction and maintainability prediction are problems that had been treated by ML methods. Datasets, software metrics and ability of ML algorithms to build such predictive models have been the main target of the studies.