Accelerated degradation tests applied to software aging experiments

Published

Journal Article

In the past ten years, the software aging phenomenon has been systematically researched, and recognized by both academic, and industry communities as an important obstacle to achieving dependable software systems. One of its main effects is the depletion of operating system resources, causing system performance degradation or crash/hang failures in running applications. When conducting experimental studies to evaluate the operational reliability of systems suffering from software aging, long periods of runtime are required to observe system failures. Focusing on this problem, we present a systematic approach to accelerate the software aging manifestation to reduce the experimentation time, and to estimate the lifetime distribution of the investigated system. First, we introduce the concept of aging factor that offers a fine control of the aging effects at the experimental level. The aging factors are estimated via sensitivity analyses based on the statistical design of experiments. Aging factors are then used together with the method of accelerated degradation test to estimate the lifetime distribution of the system under test at various stress levels. This approach requires us to estimate a relationship model between stress levels and aging degradation. Such models are called stress-accelerated aging relationships. Finally, the estimated relationship models enable us to estimate the lifetime distribution under use condition. The proposed approach is used in estimating the lifetime distribution of a web server with software aging symptoms. The main result is the reduction of the experimental time by a factor close to 685 in comparison with experiments executed without the use of our technique. © 2010 IEEE.

Full Text

Duke Authors

Cited Authors

  • Matias, R; Barbetta, PA; Trivedi, KS; Filho, PJF

Published Date

  • January 1, 2010

Published In

Volume / Issue

  • 59 / 1

Start / End Page

  • 102 - 114

International Standard Serial Number (ISSN)

  • 0018-9529

Digital Object Identifier (DOI)

  • 10.1109/TR.2009.2034292

Citation Source

  • Scopus