Predicting Likelihood of Requirement Implementation within the Planned Iteration: An Empirical Study at IBM

@article{Dehghan2017PredictingLO,
  title={Predicting Likelihood of Requirement Implementation within the Planned Iteration: An Empirical Study at IBM},
  author={Ali Dehghan and Adam Neal and Kelly Blincoe and Johan Lin{\aa}ker and Daniela E. Damian},
  journal={2017 IEEE/ACM 14th International Conference on Mining Software Repositories (MSR)},
  year={2017},
  pages={124-134}
}
There has been a significant interest in the estimation of time and effort in fixing defects among both software practitioners and researchers over the past two decades. However, most of the focus has been on prediction of time and effort in resolving bugs, without much regard to predicting time needed to complete high-level requirements, a critical step in release planning. In this paper, we describe a mixed-method empirical study on three large IBM projects in which we developed and evaluated… CONTINUE READING

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  • Using our industrial partner's interest in high precision over recall, we then adopted a cost sensitive learning method and maximized precision of predictions (ranging from 0.8 to 0.97) while maintaining an acceptable recall.

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