|
||||||||||||||||||||||||||||
|
||||||||||||||||||||||||||||
ABSTRACT
Debugging the timing behavior of real-time systems is notoriously difficult, and with a new generation of complex systems consisting of tens of millions of lines of code, the difficulty is increasing enormously. We have developed TuningFork, a tool especially designed for visualization and analysis of large-scale real-time systems. TuningFork is capable of recording high-frequency events at sub-microsecond resolution with minimal perturbation. Users can visualize system activity online in real-time and interactively explore the data. Data can be gathered from multiple layers and/or components and synthesized into visualizations that illuminate whole system interactions. Interactive exploration of hypothesis is naturally supported by direct manipulation to quickly build up complex visualizations. REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
INDEX TERMS
Primary Classification:
General Terms:
Collaborative Colleagues:
|
||||||||||||||||||||||||||||