Multifractal Aspects of Software Development
| dc.contributor.author | Hindle, Abram | |
| dc.contributor.author | Godfrey, M.M. | |
| dc.contributor.author | Holt, R.C. | |
| dc.date.accessioned | 2025-05-01T02:06:29Z | |
| dc.date.available | 2025-05-01T02:06:29Z | |
| dc.date.issued | 2011 | |
| dc.description | 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. | |
| dc.identifier.doi | https://doi.org/10.7939/r3-hgn0-2q09 | |
| dc.language.iso | en | |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | multifractal | |
| dc.subject | fractal | |
| dc.subject | version control | |
| dc.subject | wavelets | |
| dc.subject | power-law | |
| dc.title | Multifractal Aspects of Software Development | |
| dc.type | http://purl.org/coar/resource_type/R60J-J5BD | |
| ual.jupiterAccess | http://terms.library.ualberta.ca/public |
Files
Original bundle
1 - 1 of 1
Loading...
- Name:
- hindle2011ICSENIER-Multifractal.pdf
- Size:
- 1.1 MB
- Format:
- Adobe Portable Document Format