Time series analysis of open-source software projects

ABSTRACT

Open-source software projects are characterized by their loose management property. Most of the activities of their developers are voluntary instead of mandatory. Compared to closed-source software projects, open-source projects are less dependent on external turbulence, but more on its own structure and operation mechanism. In this paper, we assume that the activities of open-source software projects are only dependent on time. We use time series analysis techniques to study the time dependence of open-source software activities. The activities of open-source Software projects are extracted from mailing lists, bug reports, and revision history. Three mailing list (Linux, FreeBSD, and Apache HTTP), two bug archives (Eclipse and Apache Software Foundation), and one revision history (Apache Software Foundation) are mined. Various time series analysis techniques are used. We find that some activities of some open-source projects are cyclic and seasonally dependent, some are cyclic but seasonally independent, and some are acyclic. We build regression models for cyclic activities and analyzed their model accuracy.

REFERENCES

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INDEX TERMS

General Terms:
Measurement

Keywords:
correlation, mailing lists, prediction, regression