Open AccessBehavior Trend Analysis Method of Software Runtime Environment Elements Based on ARIMA
Author(s) -
Qiuying Li,
Minyan Lu,
Tingyang Gu
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1815/1/012008
Subject(s) - autoregressive integrated moving average , computer science , software , development environment , time series , software engineering , operating system , machine learning
Behavior trend analysis method based on auto-regressive integrated moving average (ARIMA) is presented for software runtime environment elements (REEs). The history data of environment element behavior is collected to build behavior trend analysis model. Then, behavior trend of environment elements is predicted before the environment elements actually change. Thus, according to the analysis results, we can determine the corresponding adaptive strategy before the environment elements actually change, which provides a reference for the selection and implementation of active adaptive strategy for the self-adaptive software.