Handbook of software reliability engineering
Handbook of software reliability engineering
Probability and statistics with reliability, queuing and computer science applications
Probability and statistics with reliability, queuing and computer science applications
Whither Generic Recovery from Application Faults? A Fault Study using Open-Source Software
DSN '00 Proceedings of the 2000 International Conference on Dependable Systems and Networks (formerly FTCS-30 and DCCA-8)
Statistical non-parametric algorithms to estimate the optimal software rejuvenation schedule
PRDC '00 Proceedings of the 2000 Pacific Rim International Symposium on Dependable Computing
Software Rejuvenation: Analysis, Module and Applications
FTCS '95 Proceedings of the Twenty-Fifth International Symposium on Fault-Tolerant Computing
A Comprehensive Model for Software Rejuvenation
IEEE Transactions on Dependable and Secure Computing
Failure classification and analysis of the Java Virtual Machine
ICDCS '06 Proceedings of the 26th IEEE International Conference on Distributed Computing Systems
An Experimental Study on Software Aging and Rejuvenation in Web Servers
COMPSAC '06 Proceedings of the 30th Annual International Computer Software and Applications Conference - Volume 01
An Analysis of Competing Software Reliability Models
IEEE Transactions on Software Engineering
IEEE Transactions on Computers
Memory leak analysis of mission-critical middleware
Journal of Systems and Software
Analysis of service availability for time-triggered rejuvenation policies
Journal of Systems and Software
Using Accelerated Life Tests to Estimate Time to Software Aging Failure
ISSRE '10 Proceedings of the 2010 IEEE 21st International Symposium on Software Reliability Engineering
System Software Reliability
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This paper proposes an approach to examining how testing affects the operational behavior of aging software systems. Such an approach requires models for the testing phase and the operational phase that explicitly account for crash failures due to both aging-related and non-aging-related bugs. We develop appropriate semi-Markov models and derive expressions for computing the respective transient and steady-state probabilities needed. Our numerical examples suggest that disregarding the effects of non-aging-related bugs can result in wrong conclusions about the testing phase and the operational phase. Moreover, we show how to combine the two models for a joint analysis in which metrics of interest concerning the operational phase, such as the optimal rejuvenation rate, are random variables whose distributions are influenced by the potential outcomes of testing.