TY - GEN
T1 - A study of performance variations in the Mozilla Firefox web browser
AU - Larres, Jan
AU - Potanin, Alex
AU - Hirose, Yuichi
N1 - Publisher Copyright:
© 2013, Australian Computer Society, Inc.
PY - 2013/1/29
Y1 - 2013/1/29
N2 - In order to evaluate software performance and find regressions, many developers use automated performance tests. However, the test results often contain a certain amount of noise that is not caused by actual performance changes in the programs. They are instead caused by external factors like operating system decisions or unexpected non-determinisms inside the programs. This makes interpreting the test results difficult since results that differ from previous results cannot easily be attributed to either genuine changes or noise. In this paper we present an analysis of a subset of the various factors that are likely to contribute to this noise using the Mozilla Firefox browser as an example. In addition we present a statistical technique for identifying outliers in Mozilla's automatic testing framework. Our results show that a significant amount of noise is caused by memory randomization and other external factors, that there is variance in Firefox internals that does not seem to be correlated with test result variance, and that our suggested statistical forecasting technique can give more reliable detection of genuine performance changes than the one currently in use by Mozilla.
AB - In order to evaluate software performance and find regressions, many developers use automated performance tests. However, the test results often contain a certain amount of noise that is not caused by actual performance changes in the programs. They are instead caused by external factors like operating system decisions or unexpected non-determinisms inside the programs. This makes interpreting the test results difficult since results that differ from previous results cannot easily be attributed to either genuine changes or noise. In this paper we present an analysis of a subset of the various factors that are likely to contribute to this noise using the Mozilla Firefox browser as an example. In addition we present a statistical technique for identifying outliers in Mozilla's automatic testing framework. Our results show that a significant amount of noise is caused by memory randomization and other external factors, that there is variance in Firefox internals that does not seem to be correlated with test result variance, and that our suggested statistical forecasting technique can give more reliable detection of genuine performance changes than the one currently in use by Mozilla.
KW - Automated testing
KW - Performance evaluation
KW - Performance variance
UR - https://potanin.github.io/files/LarresPotaninHiroseACSC2013.pdf
UR - https://www.scopus.com/pages/publications/85003005245
U2 - 10.5555/2525401.2525402
DO - 10.5555/2525401.2525402
M3 - Conference Paper
AN - SCOPUS:85003005245
T3 - Conferences in Research and Practice in Information Technology Series
SP - 3
EP - 12
BT - ACSC '13: Proceedings of the Thirty-Sixth Australasian Computer Science Conference
A2 - Thomas, Bruce
PB - Australian Computer Society Inc.
CY - Darlinghurst, NSW
ER -