Authors: Abram Hindle Michael W. Godfrey Richard C. Holt
Venue: ICSE 2009 31st International Conference on Software Engineering - Companion Volume, pp. 295-298, 2009
Year: 2009
Abstract: Within the field of software repository mining, it is common practice to extract change-events from source control systems and then abstract these events to allow for different analyses. One approach is to apply time-series analysis by aggregating these events into signals. Time-series analysis requires that researchers specify a period of study; usually ldquonaturalrdquo periods such as days, months, and years are chosen. As yet there has been no research to validate that these assumptions are reasonable. We address this by applying Fourier analysis to discover the ldquonaturalrdquo periodicities of software development. Fourier analysis can detect and determine the periodicity of repeating events. Fourier transforms represent signals as linear combinations of sine-waves that suggest how much activity occurs at certain frequencies. If behaviors of different frequencies are mixed into one signal, they can be separated. Thus Fourier transforms can help us identify significant development process sub-signals within software projects.
BibTeX:
@inproceedings{abramhindle2009mrafaoce,
author = "Abram Hindle and Michael W. Godfrey and Richard C. Holt",
title = "Mining recurrent activities: Fourier analysis of change events",
year = "2009",
pages = "295-298",
booktitle = "Proceedings of 2009 31st International Conference on Software Engineering - Companion Volume
"
}
Plain Text:
Abram Hindle, Michael W. Godfrey, and Richard C. Holt, "Mining recurrent activities: Fourier analysis of change events," 2009 31st International Conference on Software Engineering - Companion Volume, pp. 295-298