@article {Elmidaoui2022202,
	title = {Towards a Taxonomy of Software Maintainability Predictors: A Detailed View},
	journal = {Lecture Notes in Networks and Systems},
	volume = {470 LNNS},
	year = {2022},
	note = {cited By 0},
	pages = {202-210},
	abstract = {To help practitioners and researchers choose the most suitable predictors when selecting from existing Software Product Maintainability Prediction (SPMP) models or designing new ones, a literature review of empirical studies on SPMP identified a large number of metrics or factors used as predictors of maintainability. However, there is a redundancy and ambiguity in both the naming and meaning of these predictors. To address this terminology issue, a one-level taxonomy of the SPMP predictors identified in the literature review have been proposed. This paper now proposes a more detailed two-level taxonomy where the first level refers to four categories, namely, software design, software size, quality attributes (or factors), and software process, the second to sub-categories, and predictors inventoried from empirical studies on SPMP. {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.},
	doi = {10.1007/978-3-031-04829-6_18},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130308935\&doi=10.1007\%2f978-3-031-04829-6_18\&partnerID=40\&md5=e8e2d1411e399bbdb041c3d9d26ccad6},
	author = {Elmidaoui, S. and Cheikhi, L. and Idri, A. and Abran, A.}
}
@article {Elmidaoui2019823,
	title = {Towards a Taxonomy of Software Maintainability Predictors},
	journal = {Advances in Intelligent Systems and Computing},
	volume = {930},
	year = {2019},
	note = {cited By 0},
	pages = {823-832},
	doi = {10.1007/978-3-030-16181-1_77},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85064883521\&doi=10.1007\%2f978-3-030-16181-1_77\&partnerID=40\&md5=0a2c124cf59cc02604b4d34b5ed98a5a},
	author = {Elmidaoui, S. and Cheikhi, L. and Idri, A.}
}
