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Software evolution and time series volatility: An empirical exploration

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Details

Original languageEnglish
Title of host publication14th International Workshop on Principles of Software Evolution, IWPSE 2015 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages56-65
Number of pages10
Volume30-Aug-2015
ISBN (Electronic)9781450338165
DOIs
Publication statusPublished - 30 Aug 2015
Publication typeA4 Article in a conference publication
Event14th International Workshop on Principles of Software Evolution, IWPSE 2015 - Bergamo, Italy
Duration: 30 Aug 2015 → …

Conference

Conference14th International Workshop on Principles of Software Evolution, IWPSE 2015
CountryItaly
CityBergamo
Period30/08/15 → …

Abstract

The paper presents the first empirical study to examine econometric time series volatility modeling in the software evolution context. The econometric volatility concept is related to the conditional variance of a time series rather than the conditional mean targeted in conventional regression analysis. The software evolution context is motivated by relating these variance characteristics to the proximity of operating system releases, the theoretical hypothesis being that volatile characteristics increase nearby new milestone releases. The empirical experiment is done with a case study of FreeBSD. The analysis is carried out with 12 time series related to bug tracking, development activity, and communication. A historical period from 1995 to 2011 is covered under a daily sampling frequency. According to the results the time series dataset contains visible volatility characteristics, but these cannot be explained by the time windows around the six observed major FreeBSD releases. The paper consequently contributes to the software evolution research field with new methodological ideas, as well as with both positive and negative empirical results.

Keywords

  • ARIMA, Code churn, Conditional variance, FreeBSD, GARCH, Software evolution, Time series analysis, Volatility