Agile teams juggle multiple tasks so professionals are often assigned to
multiple projects, especially in service organizations that monitor and
maintain a large suite of software for a large user base. If we could predict
changes in project conditions changes, then managers could better adjust the
staff allocated to those projects.This paper builds such a predictor using data
from 832 open source and proprietary applications. Using a time series analysis
of the last 4 months of issues, we can forecast how many bug reports and
enhancement requests will be generated next month. The forecasts made in this
way only require a frequency count of this issue reports (and do not require an
historical record of bugs found in the project). That is, this kind of
predictive model is very easy to deploy within a project. We hence strongly
recommend this method for forecasting future issues, enhancements, and bugs in
a project.Comment: Accepted to 2018 International Conference on Software Engineering, at
the software engineering in practice track. 10 pages, 10 figure