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Inicio  /  Information  /  Vol: 14 Par: 2 (2023)  /  Artículo
ARTÍCULO
TITULO

A Comprehensive Taxonomy for Prediction Models in Software Engineering

Xinli Yang    
Jingjing Liu and Denghui Zhang    

Resumen

Applying prediction models to software engineering is an interesting research area. There have been many related studies which leverage prediction models to achieve good performance in various software engineering tasks. With more and more researches in software engineering leverage prediction models, there is a need to sort out related studies, aiming to summarize which software engineering tasks prediction models can apply to and how to better leverage prediction models in these tasks. This article conducts a comprehensive taxonomy on prediction models applied to software engineering. We review 136 papers from top conference proceedings and journals in the last decade and summarize 11 research topics prediction models can apply to. Based on the papers, we conclude several big challenges and directions. We believe that the comprehensive taxonomy will help us understand the research area deeper and infer several useful and practical implications.

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