Failure Prediction based on Log Files Using Random Indexing and Support Vector Machines
MetadataShow full item record
SubjectFailure prediction; Random Indexing; Support Vector Machine (SVM); Event sequence data; Log files
Research problem: The impact of failures on software systems can be substantial since the recovery process can require unexpected amounts of time and resources. Accurate failure predictions can help in mitigating the impact of failures. Resources, applications, and services can be scheduled to limit the impact of failures. However, providing accurate predictions sufficiently ahead is challenging. Log files contain messages that represent a change of system state. A sequence or a pattern of messages may be used to predict failures. Contribution: We describe an approach to predict failures based on log files using Random Indexing (RI) and Support Vector Machines (SVMs). Method: RI is applied to represent sequences: each operation is characterized in terms of its context. SVMs associate sequences to a class of failures or non-failures. Weighted SVMs are applied to deal with imbalanced datasets and to improve the true positive rate. We apply our approach to log files collected during approximately three months of work in a large European manufacturing company. Results: According to our results, weighted SVMs sacrifice some specificity to improve sensitivity. Speci- ficity remains higher than 0.80 in four out of six analyzed applications. Conclusions: Overall, our approach is very reliable in predicting both failures and non-failures.
Showing items related by title, author, creator and subject.
Fronza I; Sillitti A; Succi G; Vlasenko J (SciTePress, 2011)Developing software without failures is indeed important. Still, it is also important to detect as soon as possible when a running application is likely to fail, so that corrective actions can be taken. Following the ...
Borgianni, Y; Rotini, F (Taylor & Francis (Routledge): SSH Titles, 2015)Kano's theory analyses only the ‘current situation’ concerning the extent of customer satisfaction, which results from fulfilling monitored product/service attributes. Such an issue hinders the exploitation of Kano surveys ...
Predicting the competitive advantage of design projects to dynamically support decisions in product development Borgianni, Y; Rotini, F (Inderscience, 2015)Many product development initiatives are planned on the basis of the supposed capability to generate customer satisfaction. However, market and technology conditions can undergo several transformations during the execution ...