A systematic differential analysis for fast and robust detection of software aging

TitleA systematic differential analysis for fast and robust detection of software aging
Publication TypeJournal Article
Year of Publication2014
AuthorsR Matias, A Andrzejak, F Machida, D Elias, and K Trivedi
JournalProceedings of the Ieee Symposium on Reliable Distributed Systems
Volume2014-January
Start Page311
Pagination311 - 320
Date Published01/2014
Abstract

Software systems running continuously for a long time often confront software aging, which is the phenomenon of progressive degradation of execution environment caused by latent software faults. Removal of such faults in software development process is a crucial issue for system reliability. A known major obstacle is typically the large latency to discover the existence of software aging. We propose a systematic approach to detect software aging which has shorter test time and higher accuracy compared to traditional aging detection via stress testing and trend detection. The approach is based on a differential analysis where a software version under test is compared against a previous version in terms of behavioral changes of resource metrics. A key instrument adopted is a divergence chart, which expresses time-dependent differences between two signals. Our experimental study focuses on memory-leak detection and evaluates divergence charts computed using multiple statistical techniques paired with application-level memory related metrics (RSS and Heap Usage). The results show that the proposed method achieves good performance for memory-leak detection in comparison to techniques widely adopted in previous works (e.g., linear regression, moving average and median).

DOI10.1109/SRDS.2014.38
Short TitleProceedings of the Ieee Symposium on Reliable Distributed Systems