This course aims to teach learners how to debug performance issues in modern desktop applications using annotated causal tracing. The learning outcomes include understanding the challenges of diagnosing performance issues in desktop applications, learning about the inaccuracies of existing causal tracing techniques, and mastering the Argus tool for effective debugging. The course covers skills such as creating annotated tracing graphs, conducting causal search using a beam search-based algorithm, and comparing causal paths across different executions. The teaching method involves presenting key insights, workflow explanations, and real-world case studies. This course is intended for software developers, system administrators, and anyone interested in improving the performance of desktop applications.
Argus - Debugging Performance Issues in Modern Desktop Applications with Annotated Causal Tracing
Overview
Syllabus
Intro
Existing tools for diagnosing desktop apps
Desktop app diagnosis is under-investigated
An example of existing causal tracing
Existing causal tracing fails to diagnose desktop apps * It is hard to identify accurate execution segment boundaries in some threads Some execution segments have multiple incoming edges large search space
Where are the inaccuracies from? *Over-connections unnecessary searching paths
Why the inaccuracies happen to the desktop apps?
Key insights
Argus workflow
Annotated tracing graphs
Causal search: beam search based
Sub-graph comparison
diagnosis effectiveness
diagnosis cost Time cost of Argus on diagnosing the 12 real world performance issues Graph diagnosis Graph construction
tracing overhead
Conclusions
Related work
Taught by
USENIX
