Runtime Monitoring in Continuous Deployment by Differencing Execution Behavior Model.

Continuous deployment techniques support rapid deployment of new software versions. Usually a new version is deployed on a limited scale, its behavior is monitored and compared against the previously deployed version and either the deployment of the new version is broadened, or one reverts to the previous version. The existing monitoring approaches, however, do not capture the differences in the execution behavior between the new and the previously deployed versions. We propose an approach to automatically discover execution behavior models for the deployed and the new version using the execution logs. Differences between the two models are identified and enriched such that spurious differences, e.g., due to logging statement modifications, are mitigated. The remaining differences are visualized as cohesive diff regions within the discovered behavior model, allowing one to effectively analyze them for, e.g., anomaly detection and release decision making. To evaluate the proposed approach, we conducted case study on Nutch, an open source application, and an industrial application. We discovered the execution behavior models for the two versions of applications and identified the diff regions between them. By analyzing the regions, we detected bugs introduced in the new versions of these applications. The bugs have been reported and later fixed by the developers, thus, confirming the effectiveness of our approach.