Title | A systematic differential analysis for fast and robust detection of software aging |
Publication Type | Journal Article |
Year of Publication | 2014 |
Authors | R Matias, A Andrzejak, F Machida, D Elias, and K Trivedi |
Journal | Proceedings of the IEEE Symposium on Reliable Distributed Systems |
Volume | 2014-January |
Start Page | 311 |
Pagination | 311 - 320 |
Date Published | 01/2014 |
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). |
DOI | 10.1109/SRDS.2014.38 |
Short Title | Proceedings of the IEEE Symposium on Reliable Distributed Systems |