Abstract
Software maintainability prediction has gained more attention in the last decade. Several studies have conducted empirical studies to look for models to predict software maintainability more accurately. In a previous work, a systematic mapping study (SMS) was performed in this context and a set of metrics used as predictors of software maintainability has been identified. But, unfortunately those metrics are not organized in a structured way. Moreover, some authors may raise the same metric with the same meaning, but with different wordings. Hence, it becomes a necessity to unify all the metrics in a taxonomy that will help researchers build maintainability models in an easy way. The proposed taxonomy is 3 levels with categories, subcategories and metrics. We expect that the use of this taxonomy by researchers can help us identify other options to both propose a more useful taxonomy and to perform its evaluation.
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Elmidaoui, S., Cheikhi, L., Idri, A. (2019). Towards a Taxonomy of Software Maintainability Predictors. In: Rocha, Á., Adeli, H., Reis, L., Costanzo, S. (eds) New Knowledge in Information Systems and Technologies. WorldCIST'19 2019. Advances in Intelligent Systems and Computing, vol 930. Springer, Cham. https://doi.org/10.1007/978-3-030-16181-1_77
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