TY - JOUR
T1 - Component-based modeling of cascading failure propagation in directed dual-weight software networks
AU - Li, Qiyuan
AU - Wang, Yumeng
AU - Tian, Donghai
AU - Yuan, Chong
AU - Hu, Changzhen
N1 - Publisher Copyright:
© 2024 Elsevier B.V.
PY - 2024/12
Y1 - 2024/12
N2 - Software vulnerabilities often lead to cascading failures, resulting in service unavailability and potential breaches of user data. However, existing models for cascading failure propagation typically focus solely on the static design's calling relationships, disregarding dynamic runtime propagation paths. Moreover, current network topology models primarily consider function calling frequency while overlooking critical factors like internal failure probability and component failure tolerance rates. Yet, these factors significantly influence the actual propagation of software cascading failures. In this study, we address these limitations by incorporating internal failure probabilities and calling frequencies as node and edge weights, respectively. This forms the basis of our component-based directed dual-weight software network cascading failure propagation model. This model encompasses the evaluation of cascading failure propagation through intra-component and inter-component propagation probabilities, alongside the constraint of component failure tolerance rates. Through extensive experiments conducted on six real-world software applications, our model has demonstrated its effectiveness in predicting software cascading failure propagation processes. This method deepens our understanding of software failures and structures, equipping software testers with the knowledge to make well-informed judgments regarding software quality concerns.
AB - Software vulnerabilities often lead to cascading failures, resulting in service unavailability and potential breaches of user data. However, existing models for cascading failure propagation typically focus solely on the static design's calling relationships, disregarding dynamic runtime propagation paths. Moreover, current network topology models primarily consider function calling frequency while overlooking critical factors like internal failure probability and component failure tolerance rates. Yet, these factors significantly influence the actual propagation of software cascading failures. In this study, we address these limitations by incorporating internal failure probabilities and calling frequencies as node and edge weights, respectively. This forms the basis of our component-based directed dual-weight software network cascading failure propagation model. This model encompasses the evaluation of cascading failure propagation through intra-component and inter-component propagation probabilities, alongside the constraint of component failure tolerance rates. Through extensive experiments conducted on six real-world software applications, our model has demonstrated its effectiveness in predicting software cascading failure propagation processes. This method deepens our understanding of software failures and structures, equipping software testers with the knowledge to make well-informed judgments regarding software quality concerns.
KW - Cascading failure propagation
KW - Component failure tolerance
KW - Component propagation probability
KW - Software networks
UR - http://www.scopus.com/inward/record.url?scp=85207088224&partnerID=8YFLogxK
U2 - 10.1016/j.comnet.2024.110861
DO - 10.1016/j.comnet.2024.110861
M3 - Article
AN - SCOPUS:85207088224
SN - 1389-1286
VL - 255
JO - Computer Networks
JF - Computer Networks
M1 - 110861
ER -