Using Search Methods for Selecting and Combining Software Sensors to Improve Fault Detection in Autonomic Systems

Shevertalov, M.; Lynch, Kevin; Stehle, Edward; Rorres, Chris; Mancoridis, Spiros

doi:10.1109/ssbse.2010.23

Cited by 2 publications

(2 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…SBSE involves applying search-based techniques such as genetic algorithms, genetic programming, and simulated annealing to automate various aspects of software engineering processes including cost estimation and planning, requirements analysis, testing, deployment, as well as the maintenance and evolution of legacy systems. Our research group has applied search-based methods to solve various software engineering problems, most notably in the areas of automatic modularization [12], autonomic computing [13], software forensics [14], and network application detection [15].…”

Section: B Genetic Algorithms/programmingmentioning

confidence: 99%

“…In another example of using search-based methods in the area of autonomic computing, Shevertalov et al [13], represent measurements in an n-dimensional space and use genetic programming to combine metrics and reduce the dimensionality of their measurements while minimizing the loss of information. Instead of using one metric per dimension, each dimension is evolved to be an arithmetic expression that is a function of multiple metrics.…”

Section: B Genetic Algorithms/programmingmentioning

confidence: 99%

See 1 more Smart Citation

Reverse Engineering Utility Functions Using Genetic Programming to Detect Anomalous Behavior in Software

Wong

Aaron

Segall

et al. 2010

2010 17th Working Conference on Reverse Engineering

Self Cite

View full text Add to dashboard Cite

Recent studies have shown the promise of using utility functions to detect anomalous behavior in software systems at runtime. However, it remains a challenge for software engineers to hand-craft a utility function that achieves both a high precision (i.e., few false alarms) and a high recall (i.e., few undetected faults). This paper describes a technique that uses genetic programming to automatically evolve a utility function for a specific system, set of resource usage metrics, and precision/recall preference. These metrics are computed using sensor values that monitor a variety of system resources (e.g., memory usage, processor usage, thread count). The technique allows users to specify the relative importance of precision and recall, and builds a utility function to meet those requirements. We evaluated the technique on the open source Jigsaw web server using ten resource usage metrics and five anomalous behaviors in the form of injected faults in the Jigsaw code and a security attack. To assess the effectiveness of the technique, the precision and recall of the evolved utility function was compared to that of a hand-crafted utility function that uses a simple thresholding scheme. The results show that the evolved function outperformed the hand-crafted function by 10 percent.

show abstract

Section: B Genetic Algorithms/programmingmentioning

confidence: 99%

Section: B Genetic Algorithms/programmingmentioning

confidence: 99%

Reverse Engineering Utility Functions Using Genetic Programming to Detect Anomalous Behavior in Software

Wong

Aaron

Segall

et al. 2010

2010 17th Working Conference on Reverse Engineering

Self Cite

View full text Add to dashboard Cite

show abstract

Monitoring the Aging of Industrial Motors by Geometric Trending of Frequency Domain Signatures

Bayram

Şeker

Upadhyaya

2014

Journal of Testing and Evaluation

View full text Add to dashboard Cite

The characterization of the aging of electric motors using vibration measurements and a geometric interpretation of spectral domain signatures is presented. For comparison, two vibration signal records from a three-phase induction motor were acquired during degradation due to bearing fluting, following thermal and chemical aging sequences. Power spectral densities (PSD) of the vibration signals were calculated and linear approximations to the spectral signatures were used to observe the overall trend. The intersection point and slopes of these linear representations were used to extract certain critical frequencies in order to define convex regions (CR) and convex hulls (CH) as representatives of the aging (degradation) process. Furthermore, using these CRs and CHs, the functional readiness of motors could be determined by comparison of the signatures for initial and aged conditions.

show abstract

Using Search Methods for Selecting and Combining Software Sensors to Improve Fault Detection in Autonomic Systems

Cited by 2 publications

References 11 publications

Reverse Engineering Utility Functions Using Genetic Programming to Detect Anomalous Behavior in Software

Reverse Engineering Utility Functions Using Genetic Programming to Detect Anomalous Behavior in Software

Monitoring the Aging of Industrial Motors by Geometric Trending of Frequency Domain Signatures

Contact Info

Product

Resources

About