Fragmented Monitoring
Oscar Cornejo (University of Milan-Bicocca), Daniela Briola, (University of Milan-Bicocca), Daniela Micucci (University of Milan-Bicocca),, Leonardo Mariani (University of Milan-Bicocca)

TL;DR
Fragmented monitoring is a technique that records partial traces with annotations to reduce overhead and reconstruct likely full traces offline, enabling efficient field data collection without impacting user experience.
Contribution
The paper introduces fragmented monitoring, a novel approach that records partial traces with annotations to infer complete behavior, balancing data collection quality and overhead.
Findings
Reduces monitoring overhead significantly.
Enables reconstruction of likely full traces offline.
Maintains comprehensive behavior insights with less resource use.
Abstract
Field data is an invaluable source of information for testers and developers because it witnesses how software systems operate in real environments, capturing scenarios and configurations relevant to end-users. Unfortunately, collecting traces might be resource-consuming and can significantly affect the user experience, for instance causing annoying slowdowns. Existing monitoring techniques can control the overhead introduced in the applications by reducing the amount of collected data, for instance by collecting each event only with a given probability. However, collecting fewer events limits the amount of information extracted from the field and may fail in providing a comprehensive picture of the behavior of a program. In this paper we present fragmented monitoring, a monitoring technique that addresses the issue of collecting information from the field without annoying users.…
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