Authors: Abram Hindle Michael W. Godfrey Richard C. Holt
Venue: ICSE 2011 33rd International Conference on Software Engineering (ICSE), pp. 968-971, 2011
Year: 2011
Abstract: Software development is difficult to model, particularly the noisy, non-stationary signals of changes per time unit, extracted from version control systems (VCSs). Currently researchers are utilizing timeseries analysis tools such as ARIMA to model these signals extracted from a project's VCS. Unfortunately current approaches are not very amenable to the underlying power-law distributions of this kind of signal. We propose modeling changes per time unit using multifractal analysis. This analysis can be used when a signal exhibits multi-scale self-similarity, as in the case of complex data drawn from power-law distributions. Specifically we utilize multifractal analysis to demonstrate that software development is multifractal, that is the signal is a fractal composed of multiple fractal dimensions along a range of Hurst exponents. Thus we show that software development has multi-scale self-similarity, that software development is multifractal. We also pose questions that we hope multifractal analysis can answer.
BibTeX:
@inproceedings{abramhindle2011maosdnt,
author = "Abram Hindle and Michael W. Godfrey and Richard C. Holt",
title = "Multifractal aspects of software development: NIER track",
year = "2011",
pages = "968-971",
booktitle = "Proceedings of 2011 33rd International Conference on Software Engineering (ICSE)"
}
Plain Text:
Abram Hindle, Michael W. Godfrey, and Richard C. Holt, "Multifractal aspects of software development: NIER track," 2011 33rd International Conference on Software Engineering (ICSE), pp. 968-971