Research topic
This topic addresses the cost of collecting, storing, and analyzing large execution traces. The papers study reduction through abstraction, filtering, adaptive collection, feature selection, or targeted instrumentation, with the individual records documenting the retained evidence and the measured trade-offs.
Related search terms: trace volume reduction · trace compression · adaptive trace collection
6 papers in this topic, ordered newest first. The detailed paper records contain the evidence-grounded methods, tools, datasets, findings, and citation guidance.
2026 · Journal of Systems and Software
LMAT combines multi-task language models for kernel-event and event-duration prediction with online change detection, lightweight error-vector root-cause analysis, and adaptive tracing control.
Keywords: adaptive tracing · LTTng · kernel events · system-call sequences · event-duration modeling
2025 · IEEE/ACM International Conference on Software Engineering (ICSE)
The paper reconstructs missing system-call events in execution traces with diffusion and structured state-space generative models.
Keywords: execution trace reconstruction · trace imputation · diffusion models · DiffWave · SSSDS4
2024 · ACM/SPEC International Conference on Performance Engineering (ICPE)
ALS uses source-code features and reinforcement learning to recommend which Python functions to log and which log levels to use for performance-bug diagnosis.
Keywords: adaptive logging · ALS · reinforcement learning · log placement · log level selection
2024 · The 37th Canadian Conference on Artificial Intelligence
The paper uses gradient boosting and feature importance to reduce the amount of trace data needed for microservice performance modeling.
Keywords: trace data volume · feature importance · CPU demand · memory demand · Alibaba microservices
2024 · 2024 IEEE/ACM International Conference on Software Engineering: New Ideas and Emerging Results (ICSE-NIER)
The paper proposes an adaptive tracing loop that combines language-model prediction of kernel-event sequences and event durations with change detection and root-cause analysis, so detailed tracing is activated only around significant behavior shifts.
Keywords: adaptive tracing · LTTng · kernel events · system-call sequences · event-duration modeling
2017 · IEEE High Performance Extreme Computing Conference (HPEC)
The paper introduces a kernel-resident dynamic sampler that tracks virtual and physical memory usage while reducing the event volume generated by high-frequency memory activity.
Keywords: memory usage · dynamic sampling · enterprise applications · trace overhead · LTTng