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Time Series Trends in Software Evolution

Jukka Ruohonen, Sami Hyrynsalmi, Ville Leppänen, Time Series Trends in Software Evolution. Journal of Software: Evolution and Process 27(12), 990–1015, 2015.

http://dx.doi.org/10.1002/smr.1755

Abstract:

Background
The laws of software evolution were formulated to describe time series trends in software over time.

Objective
Building on econometrics, the paper relates the laws theoretically to the concept of stationarity. The theoretical argumentation builds on the fact that in a stationary time series, the mean and variance remain constant. The concept is further elaborated with different statistical types of time series trends. These provide the objective for the empirical experiment that evaluates whether software size measures in a typical software evolution dataset are stationary.

Method
The time series analysis is based on conventional statistical tests for the evaluation of stationarity.

Results
The empirical dataset contains time series extracted from the version control systems used in Vaadin and Tomcat between circa 2006 and 2013. The results establish that the observed time series are neither stationary nor follow simple mathematical functions that would translate into stationarity.

Conclusion
The testing framework presented in the paper allows evaluating the stationarity of software evolution time series. The results can be interpreted theoretically against the laws of software evolution. These methodological and theoretical contributions improve the foundations of predictive time series modeling of software evolution problems. Copyright © 2015 John Wiley & Sons, Ltd.

BibTeX entry:

@ARTICLE{jRuHyLe16a,
  title = {Time Series Trends in Software Evolution},
  author = {Ruohonen, Jukka and Hyrynsalmi, Sami and Leppänen, Ville},
  journal = {Journal of Software: Evolution and Process},
  volume = {27},
  number = {12},
  publisher = {John Wiley & Sons, Inc.},
  pages = {990–1015},
  year = {2015},
  keywords = {software evolution;time series analysis;stationarity;unit roots;dynamic regression},
  ISSN = {2047-7473},
}

Belongs to TUCS Research Unit(s): Software Development Laboratory (SwDev)

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