Learning from Software Project Histories - Predictive Studies Based on Mining Software Repositories
Abstract
In software project planning project managers have to keep track of several things simultaneously including the estimation of the consequences of decisions about, e.g., the team constellation. The application of machine learning techniques to predict possible outcomes is a widespread research topic in software engineering. In this paper, we summarize our work in the field of learning from project history.
Cite
Text
Honsel et al. "Learning from Software Project Histories - Predictive Studies Based on Mining Software Repositories." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2016. doi:10.1007/978-3-319-46131-1_32Markdown
[Honsel et al. "Learning from Software Project Histories - Predictive Studies Based on Mining Software Repositories." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2016.](https://mlanthology.org/ecmlpkdd/2016/honsel2016ecmlpkdd-learning/) doi:10.1007/978-3-319-46131-1_32BibTeX
@inproceedings{honsel2016ecmlpkdd-learning,
title = {{Learning from Software Project Histories - Predictive Studies Based on Mining Software Repositories}},
author = {Honsel, Verena and Herbold, Steffen and Grabowski, Jens},
booktitle = {European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
year = {2016},
pages = {267-270},
doi = {10.1007/978-3-319-46131-1_32},
url = {https://mlanthology.org/ecmlpkdd/2016/honsel2016ecmlpkdd-learning/}
}