@inproceedings{ab10e812c3834acdb53d82171efeb00a,
title = "Machine learning-based software quality prediction models: State of the art",
abstract = "Quantification of parameters affecting the software quality is one of the important aspects of research in the field of software engineering. In this paper, we present a comprehensive literature survey of prominent quality molding studies. The survey addresses two views: (1) quantification of parameters affecting the software quality; and (2) using machine learning techniques in predicting the software quality. The paper concludes that, model transparency is a common shortcoming to all the surveyed studies.",
keywords = "Software quality, machine learning, prediction model, quality assessment, transparency",
author = "Al-Jamimi, \{Hamdi A.\} and Moataz Ahmed",
year = "2013",
doi = "10.1109/ICISA.2013.6579473",
language = "English",
isbn = "9781479906031",
series = "2013 International Conference on Information Science and Applications, ICISA 2013",
booktitle = "2013 International Conference on Information Science and Applications, ICISA 2013",
}